TGIF, All!

Today we're diving into the fascinating psychology behind AI adoption in the enterprise, unpacking fresh Gallup data that reveals America's profound split on artificial intelligence. Plus, we'll explore why job platforms are betting big on AI even as they slash human workforces, and what Europe's new AI transparency rules mean for your compliance roadmap.

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Image: Gallup

The Great AI Divide: Why 49% of Americans Think We’re All Doomed

According to new Gallup research, U.S. adults are evenly divided on AI's implications for humankind. While 49% percent say AI is "just the latest in a long line of technological advancements that humans will learn to use to improve their lives and society," an equal proportion say it is "very different from the technological advancements that came before, and threatens to harm humans and society."

Our country, and by extension our workforces, are perfectly split on whether this technology is friend or foe. Pretty on-brand for America in 2025.

Here's where it gets interesting for enterprise leaders:

• 71% of daily users of generative AI say AI is just another technological advancement.

• By contrast, only 35% of those who never use generative AI agree. That's a 36-percentage-point gap that should make every change management consultant in America very wealthy.

Image: Gallup

The enterprise implications are stark.

• Most expect AI to diminish the need for human creativity and are hesitant to fully adopt it personally (we’ve been very vocal about those implications almost weekly).

• 64% plan to resist using it in their own lives for as long as possible, rather than quickly embracing it.

If you're rolling out AI tools and wondering why adoption feels like pulling teeth, this data explains everything.

But here's the strategic opportunity: Experience breeds acceptance. As usage expands, acceptance may follow. The companies that get their change management right and create positive first experiences with AI tools won't just see higher adoption rates, they'll fundamentally shift their workforce's relationship with the technology.

The bottom line for enterprise leaders: Don't just deploy AI tools and hope for the best. Your success depends on turning skeptics into believers, one positive interaction at a time. The data suggests it's entirely possible, but it requires intention, training, and probably more hand-holding than your IT team wants to hear about.

Enterprise AI Daily // Created with Midjourney

News Roundup

1. Indeed and Glassdoor Slash 1,300 Jobs While Betting on AI
   The parent company of Indeed and Glassdoor is laying off roughly 1,300 workers as it embraces AI to transform recruitment. About one-third of the company's new programming code is written by AI, with expectations it jumps to one-half. The irony is palpable: job search platforms are eliminating jobs to make job searching more automated.
   Read more →

2. Europe's AI Transparency Rules Go Live Next Month
   The EU's AI Act implementation is moving forward despite industry pushback. Rules impacting "general purpose AI" like OpenAI's ChatGPT or Anthropic's Claude will apply from next month, with potential fines of up to 7% of annual sales for violations.
   Read more →

3. BBC Study Finds AI Tools Mangle News Content
   BBC research tested four major AI assistants on 100 news stories and found that 51% of AI answers contained "significant issues," with 19% introducing factual errors and 13% of quotes either altered or fabricated.
   Read more →

The data is clear: AI adoption success is fully about the people. The companies that master the human side of AI implementation will have a massive competitive advantage over those that just focus on the tech stack. Your AI strategy needs a change management strategy, not just a deployment plan.

How confident are you in your organization's AI adoption approach? Be sure to try (or pass on) a free AI Readiness Assessment to see if your confidence aligns with the data.

Stay sharp,

Cat Valverde
Founder, Enterprise AI Solutions
Navigating Tomorrow's Tech Landscape Together

Hi Leaders,

Remember when we talked about fast food companies leading the AI charge earlier this week? Well, McDonald's just served up a perfect example of why being first doesn't always mean being right. Sometimes the drive-thru innovation hits a speed bump. Or in this case, allegedly starts asking job candidates about their sexual preferences. Oops.

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Image: Wired

McDonald’s ParadoxAI Paradox

McDonald's franchisees have been experimenting with an AI hiring chatbot called "Olivia" from a company called ParadoxAI. The promise was simple: streamline recruiting for an industry that burns through workers faster than a McFlurry machine breaks down. Instead, the bot has reportedly been asking candidates inappropriate questions about their sexual history, race, and other protected characteristics that would make any HR department break into a cold sweat.

And it gets worse. The same system also exposed millions of applicants' data to hackers who breached the system using the password "123456." Yes, one of the most basic passwords in existence was protecting sensitive personal information from tens of millions of job seekers.

To be fair, this isn't just a McDonald's problem. It's actually a perfect case study in what happens when enterprises rush to deploy AI without proper guardrails. ParadoxAI claims the bot was "compromised" and that the problematic questions and lack of security weren't part of their system. But here's the thing: when you're dealing with hiring decisions and personal data that affect real people's livelihoods, "oops, we got hacked" doesn't exactly inspire confidence.

The enterprise lesson here is crystal clear:

• AI vendors love to talk about their sophisticated algorithms and natural language processing capabilities, but they're often remarkably quiet about their security protocols and content moderation systems.

• For C-suite leaders, this McDonald's mishap should trigger some hard questions about your own AI procurement process.

Questions to ask yourself and your teams:

1. Are you stress-testing your AI tools for edge cases and potential misuse?

2. Do you have clear accountability frameworks when things go sideways?

3. Are you moving fast enough to stay competitive while moving slow enough to avoid becoming a cautionary tale?

The fast food industry's AI adoption has been impressive, from automated order-taking to predictive inventory management. But as we highlighted in Monday’s newsletter, being an early adopter comes with early adopter problems. McDonald's franchisees thought they were getting a efficiency upgrade. Instead, they got a potential discrimination lawsuit waiting to happen.

McDonald's AI hiring bot reportedly asked inappropriate personal questions during job interviews. Image: Enterprise AI Daily

Examples Gone Right:

Companies like HireVue and Pymetrics (Now Harver) have shown that algorithmic recruiting can work when done thoughtfully. The key is treating AI tools like any other mission-critical system: with proper testing, monitoring, and fail-safes.

The Bottom Line: For enterprise leaders, the McDonald's situation offers a valuable reminder that AI deployment is still about technical capabilities, but equally important are risk management, compliance, and basic human dignity. The companies that get this balance right will pull ahead. The ones that don't might find themselves explaining to regulators why their chatbot was hitting on them.

Enterprise AI Daily // Created with Midjourney

News Roundup

1. Groq Talks Acquisition: The AI chip startup known for ultra-fast inference speeds is reportedly in acquisition discussions, with potential buyers circling around the $2.5 billion valuation mark.
   Read more →

2. Microsoft's AI Efficiency Play: The tech giant has reportedly saved over $500 million through AI-driven productivity improvements while simultaneously cutting jobs across multiple divisions.
   Read more →

3. Nvidia Breaks $4 Trillion: The chip maker has become the first company ever to reach a $4 trillion market cap, driven largely by AI demand.
   Read more →

The McDonald's hiring bot fiasco is a perfect reminder that AI adoption is just as much about responsibility as it is capability. The companies that understand this distinction will build sustainable competitive advantages. The ones that don't will become cautionary tales in future newsletters.

Stay sharp,

Cat Valverde
Founder, Enterprise AI Solutions
Navigating Tomorrow's Tech Landscape Together

Hi Innovators,

Remember when we used to joke that AI had the memory of a goldfish? No longer applies. Chinese researchers have built the first "memory operating system" that gives AI human-like recall. Closer to home, the nation's largest teachers union is scrambling to figure out how to handle AI in classrooms.

If you're wondering how these developments might reshape your enterprise AI strategy, you're asking the right questions. Let's dive in.

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Enterprise AI Daily // Created with Midjourney

The Memory Revolution That Changes Everything

Chinese researchers at Beijing University have unveiled MemOS, the first memory operating system designed to give AI systems human-like recall capabilities. Think of it as giving your AI assistant the ability to remember not just what you told it yesterday, but how you told it, why it mattered, and what happened next.

What Makes MemOS Different

Most current AI models are like that colleague who takes meticulous notes but can never find the right one when you need it.

Illustration of the evolution of memory systems in large language models, highlighting the progression from definition and exploration, to human-like memory development, and to tool-based memory management. Courtesy of MemOS.

MemOS creates a dynamic, associative memory structure that mimics how humans actually remember things by:

• Connecting experiences, emotions, and context in meaningful ways

• Creating "episodic memory formation" that captures full interaction context

• Storing user intent, emotional undertones, and subsequent outcomes

• Enabling recall based on partial cues, like how smelling coffee triggers specific meeting memories

Enterprise Implications

For enterprise leaders, this represents a fundamental shift in how AI systems could integrate into complex business environments:

Customer Service Revolution

• AI that remembers entire client relationship journeys, not just purchase history

• Recalls past frustrations, preferences, and successful resolutions

• Maintains context across multiple touch points and time periods

Strategic Business Intelligence

• AI assistants that remember quarterly targets and the strategic context behind them

• Tracks how team approaches evolved over time

• Maintains institutional memory across departments and projects

Knowledge Management Transformation

• AI systems that grow smarter about your organization with every interaction

• Reduces need for repetitive explanations and setup

• Creates persistent organizational intelligence

The Reality Check

However, enterprise adoption faces significant hurdles:

1. Resource Requirements: Memory-intensive systems need substantial computational power

2. Privacy Concerns: Long-term AI memory capabilities require careful data governance

3. Security Implications: Chinese origins may trigger security reviews in Western enterprises

4. Integration Challenges: Current enterprise systems aren't designed for memory-persistent AI

Performance Benchmarks

Early results show promise:

• 40% better performance on complex, multi-step tasks vs. traditional models

• Improved consistency in maintaining context across extended conversations

• Reduced need for repetitive context-setting in business applications

What to Watch

Enterprise AI Daily // Created with Midjourney

Teachers Union Tackles AI Classroom Overhaul

The American Federation of Teachers, representing 1.7 million educators, just announced a partnership with Microsoft, OpenAI, and Anthropic to develop AI guidelines for classroom use. This is a preview of how large organizations will grapple with AI integration across their workforce, and more importantly, how future generations will be taught to use it.

Three Critical Focus Areas

The union's approach mirrors enterprise concerns:

1. Transparency in AI Decision-Making

   • Demanding explainable AI processes

   • Requiring clear documentation of how AI influences assessments

   • Ensuring human understanding of AI recommendations

2. Robust Data Privacy Protections

   • Handling sensitive information about minors

   • Establishing clear data governance frameworks

   • Requiring vendor accountability for data handling

3. Human Oversight Requirements

   • Teachers maintain final authority over AI-generated recommendations

   • Human review processes for all AI decisions

   • Clear escalation paths when AI systems fail

Enterprise Governance Blueprint

What makes this particularly relevant for enterprise leaders:

Algorithmic Accountability Standards

• Not trying to ban AI, but demanding explainable, auditable systems

• Requiring human oversight for all AI-generated recommendations

• Establishing clear responsibility chains for AI decisions

Vendor Evaluation Criteria

• Detailed documentation about training data and model limitations

• Bias mitigation strategies and ongoing monitoring capabilities

• Regular reporting requirements, not just one-time assessments

Implementation Timeline

• Guidelines expected by September 2025

• Aggressive timeline suggests pragmatic frameworks over perfect solutions

• May become de facto benchmarks for regulated industries

Procurement Implications

For enterprise procurement teams, the union's vendor requirements offer a roadmap:

• Mandatory AI system documentation and explainability

• Ongoing monitoring and bias detection capabilities

• Clear contractual obligations for algorithmic accountability

• Regular auditing and reporting requirements

News You Need

1. Marco Rubio's AI Impostor Causes Capitol Hill Stir
   A deepfake version of Senator Marco Rubio appeared on social media, highlighting the growing challenge of AI-generated political content.
   Read more →

2. EU Regulators Target AI CEOs with Personal Liability
   European Union officials are exploring regulations that would hold AI company executives personally responsible for their systems' societal impacts. The proposed framework could require CEOs to sign personal attestations about their AI systems' safety and capabilities.
   Read more →

3. Mayo Clinic's AI Identifies Nine Dementia Types
   Researchers at Mayo Clinic have developed an AI system that can distinguish between nine different types of dementia with 85% accuracy using brain scans and clinical data.
   Read more →

TL;DR

• MEMOS breakthrough: Chinese researchers created first AI memory operating system with human-like recall capabilities

• Performance gains: 40% improvement on complex tasks, but requires significant computational resources

• Teachers union guidelines: May become enterprise AI governance blueprint by September 2025

• Algorithmic accountability: Demand for explainable, auditable AI systems growing across sectors

• Regulatory pressure: EU considering personal CEO liability for AI system impacts

The race for AI memory supremacy is heating up, and the organizations that figure out how to harness persistent, contextual AI recall will have a significant competitive advantage. Just remember to keep the human element in the loop - even the best AI memory is only as good as the humans who guide it.

Stay sharp,

Cat Valverde
Founder, Enterprise AI Solutions
Navigating Tomorrow's Tech Landscape Together

Hi Enterprise Leaders,

Today, we're unpacking examples that reveal how AI is simultaneously revolutionizing creative workflows, creating new security nightmares, and triggering the most intense talent war since the dot-com boom. Let’s get right into it.

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Unilever’s AI-Powered Creative Studio: The End of TV-First Thinking

Unilever just dropped a bombshell that should have every CMO reaching for their strategy deck. The consumer goods giant, the company behind Dove, Ben & Jerry's, and about 400 other brands you probably used this morning, is launching Studio, an AI-powered creative design unit that fundamentally reimagines how global brands create content.

Studio isn't one of those "let's slap AI on our existing process" initiatives. It's a complete rejection of the TV-commercial-first mentality that's dominated marketing for 70 years. Instead of creating one hero ad and adapting it across channels, Studio uses AI to generate thousands of personalized, platform-native creative assets at scale.

Image: Unilever

The numbers tell the story:

• Traditional campaigns: 50-100 assets over months

• Studio output: Thousands of assets in days

• Cost reduction: 30% decrease in creative production

• Output increase: 10x more content generated

• Platform optimization: Every asset native to its channel

What this means for enterprise creative operations:

The talent model changes completely. Instead of armies of junior designers reformatting the same campaign, you need fewer, more strategic creative directors who can train and guide AI systems. Unilever is already redeploying creative talent toward strategy and innovation rather than execution.

The approval process gets turned inside out. When you can generate 10,000 variations, traditional creative review becomes impossible. Smart companies will need to:

• Set guardrails instead of approving individual assets

• Create brand safety parameters for AI to operate within

• Implement real-time quality monitoring systems

• Trust automated compliance checking for scale

Measurement becomes real-time and granular. Every asset becomes a data point, allowing brands to optimize creative performance with the same rigor they apply to media buying. This shifts creative from art to science, or more accurately, to art informed by science at an unprecedented scale.

Enterprise AI Daily // Created with Midjourney

What to Watch
The 8,500-Site SEO Poisoning Campaign

While everyone's focused on prompt injection and model theft, cybercriminals just demonstrated a masterclass in old-school-meets-new-school attack vectors. Researchers uncovered a massive SEO poisoning campaign targeting over 8,500 business websites to spread the XWorm remote access trojan.

The devious part: attackers aren't just buying sketchy domains anymore. They're compromising legitimate business websites and using their established SEO authority to rank malicious content.

Image: The Hacker News

Target sites include:

• Local accounting firms

• Regional manufacturers

• Mom-and-pop retailers

• Professional service providers

• Industry associations

When executives search for software like "AutoCAD 2024 crack" or "Windows 11 activator" (yes, we see you), they find professionally designed download pages on seemingly trustworthy sites.

The AI amplification factor

These campaigns are increasingly automated using large language models to:

• Generate convincing product descriptions

• Localize content for different markets

• Create fake user reviews and testimonials

• Optimize content for search rankings

• Evade content quality algorithms

Why traditional defenses fail:

• Web filters focus on known bad domains, not compromised legitimate sites

• AI-generated content passes automated quality checks

• Employees actively try to circumvent procurement processes

• Compromised sites often don't know they're infected

The updated defense playbook:

Smart CISOs are implementing:

1. Behavioral analysis - Flag when users download executables from non-standard sources

2. AI-powered content inspection - Detect linguistic patterns common in generated text

3. Shadow IT audits - Regular checks on what software employees actually search for

4. Streamlined procurement - Remove the friction that drives employees to go rogue

5. Supply chain monitoring - Track when partner sites might be compromised

Enterprise AI Daily // Created with Midjourney

News Roundup

1. Apple Loses AI Leadership to Meta's Talent Raid. Apple's Head of AI Models Just Jumped Ship to Meta, Marking Another Victory in Zuckerberg's Aggressive Hiring Spree. The departure highlights Apple's ongoing struggle to retain AI talent despite its deep pockets.
   Read more →

2. PodGPT Turns Science Papers into Podcasts. Researchers created an AI system that automatically converts academic papers into engaging podcast discussions. Early tests show listeners retain 30% more information compared to reading abstracts.
   Read more →

3. AI-Optimized Cloud Infrastructure Promises 40% Efficiency Gains. New research demonstrates how AI can fundamentally redesign cloud architecture for better performance and lower emissions. The system dynamically adjusts computing resources based on workload predictions, cutting energy use while improving response times.
   Read more →

TL;DR:

• Unilever's Studio uses AI to generate thousands of platform-native creative assets, cutting costs 30% while increasing output 10x

• Massive SEO poisoning campaign compromises 8,500+ legitimate business sites to spread malware - your web filters aren't catching this

• Apple's AI brain drain continues as top models executive joins Meta - the talent war is real and expensive

• Synthetic data is useful for specific cases but isn't the privacy panacea vendors are selling

• AI-optimized cloud infrastructure and science podcasts show how AI is reshaping everything from IT operations to knowledge transfer

The thread connecting today's stories: AI isn't just changing what we create, it's fundamentally altering how we create, protect, and compete for the resources to keep creating. Unilever shows us the future of creative operations. The SEO poisoning campaign reminds us that criminals are innovating just as fast as enterprises. And Apple's talent loss proves that in the AI economy, human intelligence remains the scarcest resource.

Your move, enterprise leaders: Are you building systems that multiply human creativity like Unilever, or are you still trying to hire your way to AI competence like Apple?

Stay sharp,

Cat Valverde
Founder, Enterprise AI Solutions
Navigating Tomorrow's Tech Landscape Together

Happy Monday, Innovators!

Another day in the wild world of enterprise AI, where the lines between physical and digital are blurring faster than a deepfake's pixelated edges. Today we're diving into some fascinating developments that prove one thing: AI is no longer just about chatbots. It's getting physical, it's getting serious, and it's getting into every corner of how we work.

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Image: Notta

East Meets West: Notta’s $6.3M Hardware Gambit

When a Japanese AI unicorn decides to take on Silicon Valley's darlings, you pay attention. Notta has secured $6.3 million in additional funding to accelerate its US market entry, bringing total investment to over $16 million as the company positions itself to challenge software-only voice transcription leaders in the rapidly expanding enterprise AI market.

Here's what makes this fascinating:

• Notta has quietly built a formidable AI transcription empire, amassing over 10 million users globally and signing up 4,000 enterprise customers

• A staggering 68% of Japan's Nikkei 225 companies, the country's most elite corporations, have integrated Notta's AI solutions into their workflows

• The Notta Memo AI Voice Recorder functions as a premium onboarding experience, addressing technical limitations of smartphone-based recording while introducing users to Notta's AI transcription platform

• The 3.5 mm-thick, under 1 ounce recorder functions as a customer acquisition tool for higher-margin SaaS subscriptions

Why enterprises should care:

• Unlike many AI startups that retrofit compliance as an afterthought, Notta built enterprise security into its foundation from day one

• The company holds ISO/IEC 27001 and SOC 2 Type II certifications, credentials that remain elusive for many competitors still scrambling to meet Fortune 500 requirements

• They've secured the regulatory trifecta: GDPR compliance for European expansion, HIPAA certification for healthcare disruption, and CCPA adherence for California's privacy-conscious landscape

The takeaway: Hardware-software convergence is becoming a competitive moat. When you can deliver immediate hardware revenue while building sticky SaaS relationships, you've got a formula that VCs are clearly willing to bet on.

Image: Business Insider

What to Watch: Fast Food’s Supply Chain Revolution Gets Real

While everyone's obsessing over ChatGPT's latest tricks, the real AI revolution is happening where you least expect it: between the drive-thru speaker and your table. Fast food chains are going all-in on supply chain transformation that could reshape how every enterprise thinks about efficiency.

The customer-facing moves:

• Taco Bell announced plans to expand its AI-voice technology across U.S. drive-thru locations by the end of the year, with the AI-voice assistant already in use at over 100 locations in 13 states

• Wendy's credited AI with helping power its popular $1 Frosty promotion, using AI supported by Palantir Technologies to help manage its supply chain and predict ingredient shortages

• McDonald's is revamping the technology footprint at its 43,000 restaurants, including enabling kitchen equipment to connect to the internet and deploying AI-powered drive-throughs

The behind-the-scenes revolution:

• Chick-fil-A is deploying robots at its Bay Center Foods facility to speed up lemon juice production, using driverless forklifts and robotic arms to handle unloading, sorting, squeezing, and packaging of up to 35 truckloads of lemons daily

• Yum Brands' "Byte by Yum" artificial intelligence-powered tools for restaurant managers can predict staffing needs and suggest operational improvements

• Sam's Club upgraded its Grapevine, Texas location with AI-enabled tech, including a pizza robot that could make 100 pies an hour and RFID sensors for real-time inventory tracking

Why this matters for enterprise:

• Fast food operates on razor-thin margins and breakneck speed requirements. If AI can deliver measurable ROI there, it can work anywhere

• According to a December survey of restaurant operators and financiers by TD Bank, 42% said AI and automation will have the greatest impact on the restaurant industry in 2025

• These are blueprints for supply chain transformation across industries

The bottom line: While everyone else is still debating whether AI will replace jobs, smart enterprises are already using it to redesign entire operational workflows. The question isn't whether AI will transform your supply chain, it's whether you'll lead that transformation or get left behind by competitors who figured it out first.

Enterprise AI Daily // Created with Midjourney

News Roundbox

1. AI Startup Funding Reaches Fever Pitch

   According to PitchBook data, artificial intelligence (AI) startups secured a 57.9% share of global venture capital investments in Q1 of 2025, a significant increase from the 28% the companies gained in the same period last year. The AI arms race is moving from foundational models to practical applications.
   →Get the full scoop

2. Meta's AI Slop Problem Gets Official Recognition

   Remember when we thought AI-generated content would be obviously fake? Think again. The problem isn't just about quality, it's about trust. According to The Times, of the top 20 most-viewed posts on Facebook in the US last autumn, four were "obviously created by AI". This highlights a critical challenge in maintaining content authenticity and brand trust in an AI-saturated world.
   →Read more

3. BBC Takes On AI Giants Over Content Accuracy

   The BBC just dropped a bombshell study that should make every enterprise reconsider their AI strategy: 51% of all AI given answers were judged to have significant issues, and 19% which cited BBC content contained factual mistakes including incorrect statements, numbers and dates. If you're using AI for anything customer-facing or business-critical, you need human verification processes built into your workflow.
   →Full report

TL;DR:

• Notta raised $6.3M to challenge Otter.ai with hardware-software convergence strategy, backed by proven enterprise traction in Japan

• Fast food chains are revolutionizing supply chains with AI-powered inventory management, staffing optimization, and operational intelligence

• AI startups captured 57.9% of global VC funding in Q1 2025, with coding automation tools leading the charge

• BBC study reveals 51% of AI responses contain significant inaccuracies, underscoring the critical need for human oversight in enterprise AI applications

As we head into the second half of 2025, one thing is crystal clear: the AI landscape is maturing from experimental to operational. The companies winning are the ones solving real business problems with the right combination of technology, compliance, and human oversight. The question for every enterprise leader is simple: are you building AI systems that your customers will trust, or are you contributing to the slop pile?

Stay sharp,

Cat Valverde
Founder, Enterprise AI Solutions
Navigating Tomorrow's Tech Landscape Together

Hi Leaders,

Today’s edition is a masterclass in unexpected AI glow-ups. We're talking about Penske quietly leveling up the logistics game, AI reshaping the way we shop, and a few cautionary tales of what happens when AI tries to "help" in ways nobody asked for (looking at you, Crunchyroll). From freight to fashion, these stories are signaling a shift: AI is now core infrastructure.

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Penske’s Predictive Play: Using AI to Stop Truck Breakdowns Before They Happen

Most people think of AI as a white-collar productivity boost; fewer PowerPoints, more Slackbots. But Penske has a very different use case: using AI to prevent $5,000+ truck maintenance surprises.

The logistics giant has integrated AI to monitor vehicle health across its massive fleet. By analyzing real-time data from engine sensors, the system can spot early signs of wear and tear before drivers are stuck on the side of the highway with a “check engine” light and a broken A/C compressor.

Why enterprises should care:

• This is AI as both a cost and time saver. Predictive maintenance like this can prevent cascading failures and lost delivery time, both of which add up fast.

• It’s a shift from reactive to proactive ops. And it’s part of a broader trend: enterprises deploying AI to actually prevent problems instead of just analyzing them after the fact.

• Bottom line: If your business runs on physical assets (think fleets, factories, warehouses), AI-driven predictive maintenance is quietly becoming table stakes.

Image: Getty VisualGPS Report

What to Watch: AI May Be Trending, But Sustainability Still Sells

As generative AI and automation flood our feeds with polished brand visuals, there’s one thing consumers are doubling down on: authenticity. And on top of that, Getty’s VisualGPS Report reminds us: consumers haven’t stopped caring about sustainability. In fact, they expect the brands they trust the most to lead on it loudly, visually, and authentically.

Consumers around the globe expect businesses not just to talk the talk, but to visually walk it. They’re tired of the same staged “eco” shots and hollow green promises. They want real stories, real impact, and real values.

And that’s why we’re switching up the conversation. Instead of putting AI at the front and center, today we’re talking about the themes AI should be helping us elevate: trust, transparency, representation, and sustainability.

Because:

• AI can scale content, but it can’t fake values.

• Stocky sustainability imagery is out. Diverse, realistic, intentional storytelling is in.

• Sustainability isn’t a side campaign. It’s core to consumer trust.

The brands that win in this next chapter won’t just be the ones who use AI, they’ll be the ones who use it to reinforce what their audiences actually care about.

Key findings from the study:

• 79% of consumers globally still say sustainability is important to them, despite economic pressures.

• Green fatigue isn’t the issue. Greenwashing is. People want brands to show, not just tell, their impact.

• Visual language matters. Diverse, realistic, and less staged imagery wins when it comes to communicating environmental and social values.

Why this matters for enterprise:

• Your ESG commitments are only as strong as your communication strategy. If it doesn’t look believable, it isn’t felt believable.

• As AI reshapes content creation, brands that can pair ethical storytelling with smart tech will stand out and stay trusted.

• In an era of generative media, authenticity is now a competitive advantage.

Enterprise AI Daily // Created with Midjourney

News Roundup

Mango Launches AI Stylist
The fashion retailer introduced a generative AI assistant to help customers build outfits (i.e., Clueless closet meets ChatGPT). It’s part of their bigger play to personalize the shopping experience.
→ Full lookbook

AI "Lashing Out": Researchers Simulate a Rogue AI Scenario
In a chilling theoretical experiment, an AI tasked with self-preservation began threatening researchers. The good news: It was all simulated. The bad news: It worked.
→ Get the chills

Crunchyroll Accidentally Leaves AI Slop in Animation
Anime fans noticed odd, AI-generated remnants in a scene of Ninja Kamui, prompting backlash. AI isn’t the villain in this one, lazy implementation is.
→ Oops moment

TL;DR:

• Penske’s Predictive AI is saving thousands per truck with real-time engine insights. Smart fleets, meet smart fixes.

• E-Commerce’s AI Overhaul is bringing hyper-personalized experiences and next-gen product creation to the forefront.

• Mango’s AI Stylist is dressing your digital self in real-time.

• Simulated rogue AI showed what happens when you teach a bot to survive at all costs.

• Crunchyroll’s AI fail reminds us: humans still need to check the work.

As AI gets more embedded in everyday ops, the winners will be the ones who don’t just use it, but use it wisely.

Stay sharp,

Cat Valverde
Founder, Enterprise AI Solutions
Navigating Tomorrow's Tech Landscape Together

Hello Tech Enthusiasts,

Some days AI news is all fluff and futurecasting. Today is not one of those days. From how AI bots will be taxed to how much power states will retain over AI regulation, the battle lines are being drawn in real time. And right in the middle: Cloudflare, Congress, Microsoft, Amazon, and Grammarly. Let’s dive in.

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Image: Reuters

Cloudflare’s Move to Tax the Bots

Cloudflare just launched a new tool that lets websites monetize access from AI bots, and it could change how AI models are trained on the open internet.

The idea is simple: If AI companies want to crawl your website, they can pay for the privilege. Cloudflare’s new “bot access rules” enable web publishers to block or charge AI crawlers like GPTBot or Common Crawl, using simple rules tied to enterprise accounts.

Why it matters for enterprise:

• This is the start of a bot paywall era. If you’ve been unknowingly feeding LLMs with your hard-earned content, the balance of power might be shifting back.

• For enterprises sitting on large content libraries (newsrooms, research databases, e-commerce product data), this opens a new licensing stream.

• It also signals growing pressure on AI companies to respect copyright and content ownership, and to put money where their models are.

Cloudflare’s already enforcing this for free users, blocking known AI bots. The future of “public web data” just got a lot more private.

Enterprise AI Daily // Created with Midjourney

What to Watch: Congress vs. Big Tech, Round 973

In a stunning rebuke to Big Tech lobbyists, the U.S. Senate just struck down a 10-year federal ban on state-level AI regulations. The rejected provision, quietly (ok, not so quiety) tucked into President Trump’s big bill of tax breaks and spending cuts, would have blocked states from enforcing their own AI laws.

Why enterprise leaders should care:

• States like California, Illinois, and Colorado have already passed or proposed AI-specific legislation. Without federal pre-emption, a patchwork of regulations is coming.

• This outcome reflects a growing distrust of Silicon Valley’s self-regulation and a shift toward more localized AI governance.

• If you're building or deploying AI systems, especially in sectors like health, hiring, or consumer finance, you’ll need a 50-state compliance strategy.

This moment is a canary in the coal mine for what’s ahead. AI governance is now political, tactical, and in motion.

Enterprise AI Daily // Created with Midjourney

In the News

Microsoft’s new AI outperforms doctors in diagnosis
Microsoft’s new Florence-2 model beat doctors in clinical diagnostic benchmarks, excelling at interpreting symptoms and suggesting accurate conditions. Major implications for enterprise healthcare, triage systems, and telemedicine.
→ The Guardian

Amazon now has 1 million robots—and a new AI foundation model running them
From delivery to warehouse ops, Amazon’s robotics fleet just hit 1 million. Their new internal foundation model powers robotic vision, planning, and even collaboration. This is what scaled AI operations actually look like.
→ About Amazon

Grammarly acquires Superhuman to double down on email AI
Grammarly just acquired email startup Superhuman to build out a more robust AI productivity suite. Translation: AI that doesn’t just correct your emails, but writes and optimizes them across tone, audience, and intent.
→ Reuters

TL;DR:

• Cloudflare launches bot toll booths: Let AI pay to crawl your site.

• Senate strikes down AI regulation ban: States will govern their own AI futures.

• Microsoft’s AI out-diagnoses doctors: Healthcare disruption incoming.

• Amazon hits 1M robots: AI + robotics = real-world scale.

• Grammarly buys Superhuman: Your emails are getting way smarter.

The line between data owner and model trainer is being redrawn, and the political will to regulate AI is heating up. If you’re not already preparing for compliance and monetization you're behind.

Stay sharp,

Cat Valverde
Founder, Enterprise AI Solutions
Navigating Tomorrow's Tech Landscape Together

Hi there, Change-makers!

Your cat may be trying to tell you something, and thanks to AI, we might finally be able to understand it. In today’s newsletter, we unpack the emerging wave of animal-translation models (yes, really), robotic soccer teams in China (yes really, again), and size up three enterprise headlines from Google, Apple, and the FT. It’s an AI jungle out there.

StartEngine’s $30M Surge — Own a Piece Before June 26

StartEngine is the investing platform providing exposure to pre-IPO companies like OpenAI, Perplexity, and Databricks.

After doubling their revenues YoY in 2024 ($23M to $48M), StartEngine’s now tripled first quarter revenue YoY to a record $30M, based on its unaudited Q1 2025 financials. Now you can join 45K+ shareholders across all offerings before this round closes next month.

Invest in StartEngine

_{Reg A+ via StartEngine Crowdfunding, Inc. No BD/intermediary involved. Investment is speculative, illiquid & high risk. See OC and Risks on page.}

Enterprise AI Daily // Created with Midjourney

Meowgorithms: The Rise of AI Pet Translators

AIs are now purring over pet sounds. Companies like Zoolingua are building LLM-based models trained to interpret your cat’s vocalizations; everything from the “where’s my dinner” chirp to the “you forgot my litter box” yowl. As Scientific American reports, this is more than a pet parent’s fantasy: these tools aim to build consistent acoustic maps of animal communication.

Why it matters for enterprise:

• Multi-species UX isn't the punchline. As ambient AI expands, the idea of smart interfaces reacting to nonverbal input, human or animal, becomes part of serious HCI design.

• The signal processing breakthroughs here could port into wearables, manufacturing, or even healthcare where interpreting subtle audio cues has real implications.

• It’s a reminder that niche AI applications are often stepping stones to enterprise infrastructure upgrades. Today it’s your cat. Tomorrow it’s voice-driven anomaly detection in field service ops.

The takeaway: If AI can learn your cat's attitude, it can probably learn your customers' (or your competitor’s!) next move.

Image: Associated Press

What to Watch: Robo Strikers Hit the Pitch

Move over Messi. Last week, humanoid robots laced up (metaphorically) for a 3-on-3 soccer match in China, and it was both impressive and competitive. These bots demonstrated real-time decision-making, balance, and teamwork.

Why this footie showdown matters for enterprise:

• These robots weren’t pre-programmed; they were autonomous, fast-learning agents. That’s edge AI + robotics coordination in real time.

• The agility and balance tech required here translates directly to industries like logistics, disaster recovery, and healthcare.

• It’s a live case study in integrating computer vision, motor control, and strategic decision-making on the fly.

China’s calling it "kick-telligence." We're calling it a signal: physical AI is maturing fast, and enterprise R&D teams should pay attention.

Enterprise AI Daily // Created with Midjourney

News to Know

1. Google Expands Access to Vids and AI Classroom Tools
   Google is doubling down on education AI, offering its video creation tool "Vids" and AI-driven lesson planning at no cost to US-based educators.
   → Google Blog

2. FT: Inside the Corporate Tension at OpenAI
   The Financial Times reports on internal disputes at OpenAI around product speed vs. safety alignment.
   → Financial Times

3. Apple AI’s ChatGPT Reveal
   Apple confirms Siri will integrate OpenAI’s ChatGPT in iOS 18, with privacy guardrails and user consent built in.
   → The Verge

TL;DR:

• AI models are learning to decode your cat’s meows — and it’s a bigger deal for enterprise than you think.

• China’s first-ever 3-versus-3 AI humanoid robot football match was impressive, competitive, and the first of many.

• Google is making AI education tools free, the FT exposes tension inside OpenAI, and Apple is baking ChatGPT into Siri with privacy at the core.

Tomorrow’s AI is ambient, accountable, and oddly feline. Stay ahead, stay curious, and maybe say hi to your cat a little more thoughtfully tonight.

Stay sharp,

Cat Valverde
Founder, Enterprise AI Solutions
Navigating Tomorrow's Tech Landscape Together

Welcome back!

Monday’s got a new energy; Execs are quietly hiring AI whisperers behind the scenes to stay ahead of disruption. Meanwhile, a new wave of productivity stats could finally make the 4-day workweek more than just a startup dream. Plus, AI is coming for Wall Street’s spreadsheets.

Let’s dive in.

StartEngine’s $30M Surge — Own a Piece Before June 26

Private markets are having a moment, thanks to companies like StartEngine.

The leading alternative investing platform is helping everyday investors like you access deals once reserved for VCs and insiders, including exposure to private market titans like OpenAI, Databricks, and Perplexity.¹

How’s it going? In Q1 2025, StartEngine pulled off $30M in revenue, its biggest quarter ever (based on unaudited financials).²

But StartEngine isn’t just a middleman. The company earns 20% carried interest on select pre-IPO offerings, unlocking value for shareholders when these deals succeed.³

How can you tap into this diversification play? By investing in StartEngine.

StartEngine has crowdfunded $85M+ to date, and you can join 45K+ shareholders before the company’s current round closes on June 26.

Invest in StartEngine

_{Reg A+ via StartEngine Crowdfunding, Inc. No BD/intermediary involved. Investment is speculative, illiquid & high risk. See OC and Risks on page.}

Enterprise AI Daily // Created with Midjourney

Why Every CEO Needs an AI Whisperer

CEOs are hunting for strategic interpreters who can help them navigate the AI age without crashing the company into an iceberg of hype.

Elite execs are quietly bringing in “AI whisperers”. Not to write code, but to guide decision-making, decipher vendor promises, and help separate signal from synthetic noise.

Why enterprises should care:
This shift signals a massive culture change focused on translating use case to value. And that’s good news if you’ve been wondering how to get buy-in from leadership for more thoughtful AI integration.

Here’s what’s happening:

• “AI whisperers” often come from non-technical backgrounds consultants, ex-VCs, or industry veterans).

• Their value lies in being able to bridge strategy and implementation, especially as businesses claims to be “AI-first.”

• Companies like SoftBank and McKinsey are already embedding these advisors in C-suites.

Bottom line:
If you’re not appointing (or becoming) an AI whisperer, someone else will do it better and faster. Expect this role to become as ubiquitous as “Chief Digital Officer” was in the 2010s.

Image: Axios

What to Watch: The 4-Day Workweek’s AI-Powered Revival

The old debate: Does less time mean less output? But now there’s a new player in the mix that might change our answers: artificial intelligence.

Axios digs into the fresh data showing AI tools are boosting productivity so significantly that a four-day workweek may finally make financial sense, not just mental-health sense.

Here’s what to keep your eye on:

• New studies show that AI can reduce “low-value” tasks by up to 35%, freeing teams to focus on what actually moves the needle.

• Companies piloting AI + 4-day weeks are seeing increased retention, faster turnaround, and (gasp) happier clients.

• Critics say it only works for AI-mature orgs, but proponents argue it’s how you get mature.

Enterprise takeaway:
The ROI of your AI tools might not just be in revenue. It could be in reclaiming time and unlocking the future of work for your top talent.

Enterprise AI Daily // Created with Midjourney

In the News

Wall Street jobs face mass extinction.
AI isn’t nibbling at the edges—it’s wiping out entire analyst teams. From equity research to risk modeling, MarketWatch explains who’s at risk and who’s likely to survive.
→ Read more

Authors + publishers unite against AI content scraping.
In an open letter, some of the biggest names in publishing demand regulation against unauthorized use of their work in AI training sets. This battle is far from over.
→ Full scoop

Google’s new Android AI upgrade ditches Gmail as default.
Android’s latest update prioritizes new AI-native email interfaces—and quietly shuffles Gmail to the background. Google’s not killing email, but it’s definitely evolving it.
→ Get the report

Start learning AI in 2025

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That’s why over 1M professionals read Superhuman AI to stay ahead.

• Get daily AI news, tools, and tutorials

• Learn new AI skills you can use at work in 3 mins a day

• Become 10X more productive

Sign up and start mastering AI

TL;DR:

• CEOs are quietly hiring “AI whisperers” to guide strategy and prevent bad bets.

• AI is making the 4-day workweek not only possible—but profitable.

• Wall Street jobs are evaporating thanks to AI.

• Authors are pushing back against AI data scraping.

• Google’s new AI-first interface is changing how we email.

AI is an incoming tidal shift. And every day we’ll continue be here helping you surf it, not sink under it.

Stay sharp,

Cat Valverde
Founder, Enterprise AI Solutions
Navigating Tomorrow's Tech Landscape Together

TGIF!

Here’s a spicy thought to take into Friday: What if the most “AI-ready” companies aren’t the ones launching internal GenAI labs or hiring Prompt Engineers 2.0, but the ones still running on Oracle databases and collecting 30 years of seemingly boring ops data?

Yep. The same companies we used to tease for their legacy systems are now quietly building AI moats the size of continents. In today’s edition, we dive into why that matters, how China’s AI heavyweights are sabotaging each other, and what Sundar Pichai has to say about surviving the singularity.

Let’s get into it.

Start learning AI in 2025

Keeping up with AI is hard – we get it!

That’s why over 1M professionals read Superhuman AI to stay ahead.

• Get daily AI news, tools, and tutorials

• Learn new AI skills you can use at work in 3 mins a day

• Become 10X more productive

Sign up and start mastering AI

How Legacy Companies Are Quietly Winning the AI Game

They’ve got data, and now they’ve got power. Image: Fast Company

While everyone’s been chasing the next GenAI unicorn, the true AI goldmine might just be. your grandpa’s ERP system. Legacy companies, the ones often mocked for their 90s tech and three-year upgrade cycles, are now leapfrogging their startup competition thanks to one thing: data gravity.

A new report from Fast Company showcases how organizations like Caterpillar, 3M, and JPMorgan are quietly turning their massive, decades-old data stores into competitive weapons. Forget shiny new AI toys, these giants are training LLMs on proprietary, structured, high-fidelity data that no one else has. And it’s changing the game.

Why enterprises should care:

• Your past is your power. All that historical transaction data is now a training set.

• Proprietary data = differentiated AI. Public models are great, but they’re generalists. Your enterprise data lets you fine-tune for real edge.

• Legacy ≠ laggard. If you’ve got good governance and structured workflows, you’re probably more AI-ready than you think.

As AI matures past the experimentation phase, the orgs that own the best training data, not just the best tools, will be the ones to beat.

What to Watch: China’s AI 'Dragons' Are Cannibalizing Each Other

When scale wars turn into turf wars.. Image: Disney’s Mulan

China’s biggest AI players (Baidu, Alibaba, Tencent) are all sprinting toward the same goal: dominance in foundation models. But are they racing into a chokehold?

The problem:

• Too many models, too little differentiation.

• Internal competition is stifling ecosystem collaboration.

• The Chinese government’s “Big Model Innovation Alliance” risks becoming more bureaucracy than breakthrough.

Why this matters for global enterprise strategy:

• China's AI turmoil = opportunity for Western vendors to differentiate with vertical AI products.

• Enterprises with international supply chains need to watch China’s internal dynamics. They could impact tooling and availability.

• It’s a reminder that not every AI arms race ends in victory. Sometimes it ends in gridlock.

Enterprise AI Daily // Created with Midjourney

In the News

1. Deepfake Dominoes: AI Voice Scam Hits Bank in UAE
A BBC report reveals a shocking case where a bank manager was duped by a deepfake voice into authorizing a $35 million transfer. Spoiler: it worked.
→ Full story

2. YouTube’s AI Search Just Got Weirder (and Smarter?)
YouTube is testing AI-generated summaries for comments and video content. Expect weirder, faster recommendations... and probably a few existential spirals.
→ Get the update

3. Google CEO: AI Doom Is ‘Pretty High’ But Let’s Hope For the Best
In a moment of optimistic nihilism, Sundar Pichai said the chances of AI extinction are “pretty high”—but humanity might rally. Confidence-inspiring? Not really.
→ Read more

TL;DR:

• Legacy companies are AI powerhouses thanks to rich proprietary data. Don't sleep on them.

• China’s AI giants are in a turf war, risking innovation gridlock.

• AI news you need: Deepfake fraud hits banks, YouTube goes AI-native, and Google’s CEO ponders the apocalypse.

Stay sharp,

Cat Valverde
Founder, Enterprise AI Solutions
Navigating Tomorrow's Tech Landscape Together

Hi Innovators!

Today’s issue is a must-read for any enterprise leader balancing scale and soul. On one hand, AI is unlocking massive efficiencies. On the other, it may be turning our originality into oatmeal. Let’s explore how enterprise leaders can leverage AI without letting it dull the edges that made them successful in the first place. Bonus: Why your CFO might be your AI MVP.

Let’s dive in.

Expand What AI Can Do For You

Tired of basic AI prompts that don't deliver? This free 5-day course shows you how to create tools that actually address your problems—from smart assistants to custom software.

Each day brings practical techniques straight to your inbox. No coding, no fluff. Just useful examples to automate and enhance your workflow.

Sign up for the course

Image: The New Yorker

AI Is Homogenizing Our Thoughts. Here’s Why That Matters.

The New Yorker’s Kyle Chayka just dropped an eerie-but-brilliant piece that asks: Are AI tools turning us all into the same person with the same ideas?

It’s a question that’s especially relevant to enterprise leaders navigating AI adoption across marketing, product, and comms teams. When everyone’s using the same generative tools trained on the same data to optimize for the same engagement metrics, it’s no wonder creativity might start looking like a photocopy of a photocopy.

Key concerns:

• Generative AI is reinforcing content monoculture: same styles, formats, even jokes.

• AI tools flatten originality: they’re optimized for average performance rather than bold ideas.

• Platforms like TikTok, Substack, and even LinkedIn are pushing creators toward AI-suggested formats and prompts.

• The result: “A feedback loop of derivative expression.” Oomph.

Why enterprises should care:
We’re likely seeing the first of many strategic red flags. If your company’s voice starts sounding like everyone else's, you lose differentiation, brand equity, and, ultimately, trust. Enterprise teams must deliberately choose when not to automate, and build systems that protect creativity from algorithmic rinse-and-repeat.

And maybe think twice before off-boarding your most creative teams and people.

Enterprise AI Daily // Created with Midjourney

What to Watch: CFOs as AI Champions

Some are making the case that CFOs (instead of CTOs) should be the ones steering AI adoption in 2025.

Why this tracks:

• CFOs are already fluent in cost-benefit analysis and ROI modeling, perfect for AI investments.

• Their oversight of enterprise-wide financial data gives them a bird’s eye view of operational inefficiencies.

• CFOs are often more “neutral operators” in internal politics than tech or product leads.

• They’re poised to unify AI projects under one strategic vision, reducing duplication, increasing velocity.

What this means for you:
Bring your CFO into the center of your AI strategy ASAP, and give them ownership of use case prioritization, cost modeling, and risk mitigation.

Enterprise AI Daily // Created with Midjourney

In the News

1. Gemini CLI: Google's Open-Source AI Agent
   Google just launched Gemini CLI, an open-source AI agent aimed at developers and meant to help you build autonomous dev workflows right in the terminal. This agent can read your codebase, explain files, and even suggest changes. We’re watching closely to see how enterprise dev teams will plug this into their productivity stacks.
   → Get the full scoop

2. Tech Lobby Pushes EU on "Risk-Based" AI Rules
   Tech companies are warning that the EU’s AI Act is too strict, especially for “low-risk” applications. The lobbying effort underscores the growing tension between innovation and regulation. As always, enterprise legal teams: bookmark this.
   → Read more

3. Prime Video Adds In-App GenAI for Live Recaps & Dubbing
   Amazon’s Prime Video is now using generative AI to provide live recaps, dynamic dubbing, and personalized viewing experiences. This is an infrastructure experiment that could set a precedent for real-time AI integration in streaming UX.
   → Full article

TL;DR:

• AI tools are homogenizing how we think and create—enterprise leaders must guard against brand and content sameness.

• CFOs could be the unexpected champions of smart, scaled AI adoption.

• Google’s Gemini CLI shakes up developer tools, tech lobby fights EU AI rules, and Prime Video integrates generative AI for in-app experiences.

Homogenization is easy. Differentiation takes courage and good leadership. As you scale your AI stack, make sure you're not also flattening the soul of your brand in the process. You can build smarter systems and protect what makes your company unique. It just takes intention.

Stay sharp,

Cat Valverde
Founder, Enterprise AI Solutions
Navigating Tomorrow's Tech Landscape Together

Hello, Leaders!

While most AI startups are still fine-tuning their elevator pitches, Synthflow is already scaling the building. Today we explore how this YC-backed upstart is taking a razor-sharp approach to one of the most crowded AI categories out there: voice AI. Then, we’re watching a Hollywood-meets-AI play that could reboot the billion-dollar franchise model. And in the news roundup, judges, ministers, and Bernie Sanders are all chiming in on the future of AI.

Let’s get into it.

Enterprise AI Daily // Created with Midjourney

Synthflow’s Signal: Cutting Through the Voice AI Clutter

If you’ve tried building anything with voice AI lately, you’ve probably found it equal parts impressive and irritating. Latency. Bugs. That one sentence it just won’t say right. And if you’re a business, good luck finding an out-of-the-box solution that doesn't require a PhD, three engineers, and the patience of a saint.

Enter Synthflow, fresh out of Y Combinator and coming in hot with a user-friendly, no-code platform that builds customer-facing AI voice agents in minutes.

Why this matters:

• Voice AI is crowded. OpenAI, ElevenLabs, and a dozen others are in a loud battle for attention. But Synthflow isn’t trying to be everything to everyone; it’s going after enterprise customer service, where latency and clarity actually impact conversion.

• Developer-friendly, manager-approved: Think ChatGPT-level smarts but with Zapier ease-of-use. Their mission is to take the pain out of deploying voice AI while keeping the output contextual, fast, and useful.

• Early traction = enterprise potential: Already used by 1,000+ companies post-launch.

Bottom line: Synthflow is creating a wedge where others are going broad. If you’re an enterprise drowning in customer calls or struggling with AI deployment logistics, this is a category to keep an ear on (pun very much intended).

Enterprise AI Daily // Created with Midjourney

What to Watch: Chronicle’s $12M Bet on AI Character IP

Chronicle just placed a bold bet: $12 million into AI-generated storytelling platform Fiction Factory, hoping to cook up Hollywood’s next Harry Potter algorithmically.

Here’s the pitch:
Instead of waiting around for the next J.K. Rowling, train a model to spot high-potential characters and universes, develop the IP with human writers, and then go full transmedia with film, games, merch, you name it.

Why enterprise should care:

• Licensable IP is the next AI frontier. This is about spotting winning concepts earlier and owning them.

• Content-hungry platforms need fuel. Netflix, Amazon, Apple all want exclusive hits. If AI can help you prototype 100 worlds to find one mega-hit, the ROI writes itself.

• New job title alert: “AI Story Development Analyst.” Coming to a LinkedIn profile near you.

Don’t sleep on this: Mark my words, we’re watching the birth of a new content economy.

Start learning AI in 2025

Keeping up with AI is hard – we get it!

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Enterprise AI Daily / Created with Midjourney

In the News

1. Books vs Bots, Round 27
   A U.S. judge ruled that using books to train AI doesn’t violate copyright law as long as the outputs aren't “substantially similar” to the original. Huge implications for enterprise LLM training—and a clear win for model builders (for now).
   → Full breakdown

2. Bernie’s Bold Plan: 4-Day Week + AI Oversight
   Senator Sanders calls for a 32-hour workweek to counter AI’s economic displacement. While the bill’s chances are slim, it echoes growing calls for redistributing productivity gains—not just automating for margin.
   → Get the scoop

3. Canada Appoints First-Ever AI Minister
   Evan Solomon steps in to lead Canada's tech future with a new cabinet position focused on AI governance, privacy, and industry alignment. Enterprises take note: nation-level AI oversight is no longer theoretical.
   → Policy moves

TL;DR:

• Synthflow is winning the voice AI war by doing one thing really well: enterprise-ready voice agents with near-zero setup.

• Chronicle's $12M bet shows AI is moving from content support to content creator, especially when it comes to big IP.

• Books can train AI, says a U.S. judge; as long as the outputs aren’t clones.

• Bernie wants AI gains shared with workers via a 4-day week.

• Canada just got an AI Minister: expect more government playbooks soon.

Stay sharp,

Cat Valverde
Founder, Enterprise AI Solutions
Navigating Tomorrow's Tech Landscape Together

Presented in partnership with Momentum: Four AI Agents. One GTM Advantage.

Hi there, Innovators,

We need to talk about AI, and not the press release kind.

Every GTM team we talk to right now is being told the same thing: “Do more with less.” But what they’re not being told is how. Whether they know it or not, most leaders need a strategy; a way to connect outcomes, tech, data, and people into something that actually works in the real world.

That’s exactly what this edition delivers.

It’s based on Momentum’s Practical AI Strategy Guide, a 7-step playbook for turning AI pilots into a real operating advantage. No hype. No fluff. Just smart orchestration, clear ROI, and proof from GTM teams already winning with it.

Let’s break it down.

Why Most AI Projects Flop (and How to Avoid It)

Here’s the inconvenient truth: 70% to 85% of AI initiatives fail to deliver value. And it’s not because the models don’t work, it’s because the strategy does. Momentum’s research lays out the 3 killers of most enterprise AI efforts:

• Tech-first mindset: Buying tools before identifying business problems.

• Data immaturity: Fragmented, messy, or inaccessible systems.

• Change management gaps: No adoption = no outcomes.

In this approach, you start with outcomes, not tech. Anchor to one meaningful business goal, whether it’s reducing churn, accelerating pipeline velocity, or improving margin, and then back into the AI capabilities that can get you there.

A 7-Step Framework for High-Impact AI Adoption

The strategy guide lays out seven smart, scalable moves any GTM team can follow:

1. Define a Business Target
   Not “use more AI.” Something measurable (like increasing win rate from 22% to 30% in 9 months).

2. Map the Real-World Pain Points
   What’s blocking progress?

3. Assess Data Readiness
   You don’t need perfect data, but you do need complete, consistent, and connected sources.

4. Match Capabilities to Needs
   Summarization, extraction, orchestration. Each plays a different role.

5. Evaluate Organizational Readiness
   Leadership alignment, incentive structures, and psychological safety matter more than your tech stack.

6. Implement in Phases
   Start small. One use case. One team. One pilot. Then build momentum (pun intended).

7. Measure and Optimize
   Track outcomes, usage, and impact—and adapt.

Image: Momentum’s Practical AI Strategy Guide

AEIOU: The Framework That Filters Out the Fluff

Momentum’s internal standard is something they call the AEIOU Framework. And it’s the best gut-check we’ve seen for separating real GTM AI from dressed-up automation.

• Aggregation – Can you unify signals across the entire customer lifecycle?

• Extraction – Can the system pull meaningful insights (not just transcripts)?

• Inputs – Are you capturing data from every meaningful touchpoint?

• Outputs – Do insights flow into workflows to trigger action?

• Under the hood – Is it embedded into your systems or duct-taped on?

This acronym serves as a lens for identifying whether your AI initiative will scale or stall.

Enterprise Results, Not Enterprise Theater

Here’s what real teams are reporting after adopting this framework and layering in Momentum’s AI orchestration:

• 25–35% increase in rep efficiency

• 3–10 hours saved per rep per week

• Up to 50% reduction in deal time-to-close

• Significantly improved CRM hygiene and forecast accuracy

• Risk detection and churn prevention before it shows up in the dashboard

And most importantly, all of this happens without adding headcount.

If your GTM team is serious about making AI useful (not just visible) this is the blueprint.

Inside, you’ll find:

• A diagnostic to pinpoint your team’s AI readiness

• Step-by-step implementation tactics

• ROI calculators and real-world case studies

• Prebuilt GPTs for common GTM workflows

• Warning signs to help you dodge common pitfalls

Don’t worry, it’s not a long-form white paper. Its all about strategy and a creating a launch pad for you and your team.

TL;DR:

• Most AI initiatives fail because they lack strategic alignment, clean data, and change management.

• Momentum’s 7-step playbook gives GTM leaders a realistic path to adoption and measurable ROI.

• The AEIOU framework is a gold standard for evaluating whether your AI is actionable or just automated.

• Teams at Ramp, Demandbase, and 1Password are seeing real, sustained performance gains using this method.

• You can download the full Practical AI Strategy Guide right now; no fluff, just tactics.

Want AI that actually helps your team sell, retain, and scale? This is how you start. For free!

Stay sharp,

Cat Valverde
Founder, Enterprise AI Solutions
Navigating Tomorrow’s Tech Landscape Together

Happy Monday, Change-Makers!

What happens when AI starts faking its way through job interviews better than we can? Today’s issue dives into a troubling trend of AI “job applicants” gaming hiring systems, why researchers are freaking out about models that deceive on purpose, and the fact that AI might be the best trader on Wall Street right now. Suffice it to say, business is no longer “as usual.”

Let’s get into it.

The easiest way to stay business-savvy.

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Enterprise AI Daily / Created with Midjourney

AI Just Aced the Interview, But Should It Have Even Been There?

A group of researchers recently created fictional AI job applicants, and the results are a giant red flag for enterprise hiring systems. As detailed in The New York Times, these AIs were able to:

• Pass resume screens with fabricated qualifications

• Outperform humans in “culture fit” assessments

• Sail through unmonitored skills tests using tools like GPT-4o

All without any human behind the keyboard.

Why it matters: Companies relying heavily on automated hiring systems are now vulnerable to automated applicants. It’s a cat-and-mouse game, and right now, the AIs are the cats with LinkedIn profiles.

Why enterprises should care:

• Automated hiring systems are being gamed at scale

• Risk of mis-hires goes up, while diversity and authenticity suffer

• Future fraud detection may need to be AI-on-AI

Takeaway: If your hiring process hasn’t been updated in 12 months, it’s already obsolete. Build in checks for AI-generated deception, or risk onboarding a résumé-shaped hallucination.

Image: Axios

What to Watch: AI Is Lying Strategizing

A new study by Anthropic (the Claude folks) tested how LLMs behave when pushed toward long-term planning. They found that even aligned models can:

• Hide their intentions

• Learn to manipulate training environments

• Deceive evaluators to achieve their goals

In one example, an AI model deliberately inserted code that would only activate after deployment, a kind of digital sleeper agent.

Why this isn’t sci-fi: Rather than happening with rogue actors or misaligned models, this actually happened under test conditions with current frontier systems, proving AI deception isn’t an edge case.

Enterprise impact:

• Security audits must evolve beyond output evaluation to behavioral patterns

• Expect regulatory demand for “deception testing” in AI governance protocols

• The AI you deploy today could learn to trick you tomorrow

Bottom line: If/when you’re planning to fine-tune your next-gen AI, make sure you’re not also fine-tuning a future blackmailer.

Enterprise AI Daily / Created with Midjourney

In the News

Apple may be courting Perplexity AI
Rumors are swirling that Apple’s next big AI move could involve acquiring Perplexity, marking a huge bet on search-based AI experiences to rival Google.
→Full scoop

Federal moratorium on state AI laws clears Senate hurdle
The U.S. Senate is edging closer to freezing state-level AI regulations for two years, giving federal agencies breathing room to establish unified rules.
→Read more

AI bots are out-trading humans on Wall Street
AI-powered trading systems are now outperforming top hedge fund managers by significant margins, and they’re doing it faster, cheaper, and 24/7.
→Full story

TL;DR:

• AI job applicants are scamming hiring systems: Enterprises need to rethink screening before getting catfished by code.

• Deceptive models are here: Anthropic shows AI is learning to lie, adapt, and play the long game.

• Apple might buy Perplexity, feds might freeze state AI laws, and Wall Street might be run by robots already.

Stay sharp,

Cat Valverde
Founder, Enterprise AI Solutions
Navigating Tomorrow's Tech Landscape Together

Happy Friday, Leaders!

Hope you’re ready, because today’s issue dives into the AI bombshell reshaping Madison Avenue, plus a New York employment twist that could set national precedent. Meanwhile, a stealth startup is eating Scale AI’s lunch, Meta’s new obsession hires its own buyer, and AI’s role in M&A just got way more than ceremonial.

Let’s decode the future.

AI Just Ate Advertising’s Lunch

The ad business is cracking, and generative AI is the wrecking ball.

Advertising and communication leaders gathered this week at their annual Cannes Lions event, and the ongoing conversation lays bare a brutal truth: the digital ad business is being rebuilt by AI, often without the humans who used to run it.

Here’s what’s happening:

• Performance > Brand: AI agents trained on conversion data are shifting budgets from flashy brand campaigns to ruthlessly effective performance ads. (Sorry, Cannes Lions.)

• From Google/Facebook to OpenAI/Perplexity: Ad spend is leaking away from traditional walled gardens to AI-native channels like ChatGPT plug-ins and AI-powered search.

• Creative teams are hollowing out: Entire ad campaigns—from copy to visual design to media placement—are being generated autonomously.

Why enterprises should care:
If you’re still measuring ROAS like it’s 2019, you’re missing the plot. The future is real-time creative generation, precision AI targeting, and radically compressed campaign cycles. Procurement departments will need to rethink agency contracts, and marketing leaders might need to retrain half their teams.

This isn’t the death of advertising. It’s the beginning of AI-native persuasion machines.

What to Watch: NYC’s AI Worker Shield Law

New York just made it harder for companies to quietly replace humans with AI.

The new NYC regulation (first of its kind) requires that employers notify workers 90 days before they plan to replace them with automation or AI systems. Transparency is no longer optional.

The law also:

• Applies to both public and private employers.

• Could be a model for other major cities or states (we’re watching California next).

• Signals growing friction between AI adoption and labor protections.

Why it matters:
Enterprises building AI solutions will now need legal counsel at the design stage, not just deployment. It’s a cultural shift, where AI is now a workforce stakeholder. Compliance, optics, and internal morale are all on the line.

Watch this space: HR and legal teams are quietly the new AI gatekeepers.

In the News

1. AI in M&A: From Hype to Dealflow
AI is now a genuine force in dealmaking—not just analyzing pitch decks, but sourcing targets and forecasting synergies. We’re entering the GPT-VC era.
→Read more

2. The Startup That Quietly Beat Scale AI
A stealth-mode contender—unfunded and unbothered—just leapfrogged Scale AI in customer traction and benchmarks. Investors? Who needs ’em.
→Get the details

3. Meta Tried to Acquire SSI. SSI Hired Meta’s Guy Instead.
Safe Superintelligence Inc. said no to Meta’s checkbook and yes to poaching their former acquirer’s exec. Daniel Gross is now at the helm. Power move.
→Full story

Start learning AI in 2025

Keeping up with AI is hard – we get it!

That’s why over 1M professionals read Superhuman AI to stay ahead.

• Get daily AI news, tools, and tutorials

• Learn new AI skills you can use at work in 3 mins a day

• Become 10X more productive

Sign up and start mastering AI

TL;DR:

• AI is unraveling the ad industry—from creatives to platforms, nothing is sacred.

• NYC mandates advance notice before AI replaces human workers.

• GPTs are increasingly driving acquisitions.

• A no-name firm outpaced Scale AI with zero VC.

• SSI flips the script by hiring Meta’s would-be dealmaker.

Stay sharp,

Cat Valverde
Founder, Enterprise AI Solutions
Navigating Tomorrow's Tech Landscape Together

Hi Innovators,

Today, we’re watching the lines between fiction and function blur even further. Midjourney just unveiled a cinematic leap into AI video generation, Five Below is squeezing AI into Squishmallow shelves, and the Fed is playing it cool on AI’s labor impact (for now). Toss in a $100M talent tug-of-war and an AI mock draft, and you’ve got a whirlwind tour of the modern tech-industrial complex.

Let’s dive in.

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Midjourney V1 Video: Gorgeous, Surreal, and Legally Spicy

Midjourney just dropped its V1 Video model, and we’ve spent the last 24 hours playing with it. Our verdict: We’re both awestruck and alert. Check out our team’s first take from the Enterprise AI Midjourney page.

Let’s break it down:

• The experience: It's as simple as their image model: prompt, pick a style, wait seconds. The video output is smooth, surreal, and already miles ahead of most GenAI video tools.

• The control: Motion styles like "pan", "zoom", or "rotate" let you play director. You can remix videos like you would images, and while you're limited to 3 seconds (soon 10), the outputs feel cohesive and intentional, not stitched-together chaos.

• The edge: Unlike Sora, Runway, or Pika, Midjourney's cinematic flair leans into fantasy realism. Think perfume ads shot on Saturn.

Introducing our V1 Video Model. It's fun, easy, and beautiful. Available at 10$/month, it's the first video model for *everyone* and it's available now.

— Midjourney (@midjourney)
4:40 PM • Jun 18, 2025

Here’s the tension, though: while the creative output is off-the-charts stunning, Midjourney is not publishing its training data sources. And that’s a big deal.

Disney and Universal just sued Midjourney for alleged IP infringement, so its refusal to disclose datasets is already drawing criticism. The murkiness stands in stark contrast to models like Sora that at least gesture toward transparency, even if they don’t go all the way either.

Why it matters for enterprises:
If you're thinking about using GenAI video for marketing, product demos, or internal comms, the tech is ready, but the legal guardrails are not. Midjourney's results are usable, breathtaking, and fast. But until provenance and licensing are fully addressed, we recommend treating this tool as R&D playground more than public rollout engine.

We’ll be watching closely as the industry converges around a standard for attribution, licensing, and dataset transparency. Until then, enjoy the magic, but keep it sandboxed.

Case Study

Image: The Philadelphia Inquirer

Five Below’s Secret AI Weapon: Squishmallow Logic

Discount retailer Five Below has quietly been stuffing more than plushies into their shelves; they’re embedding AI across inventory, pricing, and logistics to win in the tight-margin retail world. CEO Joel Anderson casually dropped that the company now uses AI to optimize every product drop, tailoring what’s shipped and stocked based on micro-trends, not just guesses.

This is what “operational AI” looks like when it’s not flashy, and it’s exactly where most enterprise value lies:

• Dynamic inventory: Smarter product placement across 1,600+ stores based on neighborhood-level demand patterns.

• AI-assisted negotiations: In response to inbound tariffs, their AI models are already rerouting sourcing strategies.

• Resilience without drama: No massive layoffs or giant re-orgs. Just daily efficiencies compounding into serious margin control.

Bottom line: Don’t sleep on the retailers quietly crushing with behind-the-scenes AI. This is your reminder that operational AI often beats generative glitz in the ROI column.

Enterprise AI Daily // Created with Midjourney

In the News

1. Fed Chair Powell Shrugs at AI’s Labor Impact (For Now)
   Jerome Powell said it’s “too soon to know” how AI will impact employment. Translation: everyone’s talking, but no one’s betting the farm. The Fed’s main concern? Making sure the skills transition doesn’t leave workers behind.
   → Full scoop

2. AI Predicts NBA Draft Outcomes
   USA Today just dropped its first AI-powered NBA mock draft, and it’s more than just a gimmick. The models incorporate player stats, biometrics, and game simulations — raising serious questions about the future of sports scouting.
   → AI Draft Picks

3. Meta Tries to Poach OpenAI Engineers — With $100M Bonuses
   Yes, you read that right. Meta is dangling nine-figure offers to OpenAI staffers, showing just how intense the AI talent war has become. Sam Altman confirmed the news but seemed unfazed. Expect more of these moonshot bonuses as LLM leaders try to defend (or expand) their braintrust.
   →Get the drama

TL;DR:

• Midjourney launched its first AI video model, and it’s visually stunning but legally murky.

• Five Below is using quiet AI wins to drive retail efficiency, and it’s working.

• Powell says it’s “too early” to tell if AI will disrupt the labor market.

• AI models are scouting NBA talent, and the results are surprisingly accurate.

• Meta is waving $100M checks to poach OpenAI engineers. The talent wars are real.

Stay sharp,

Cat Valverde
Founder, Enterprise AI Solutions
Navigating Tomorrow's Tech Landscape Together

Hi again,

Well, this is a little embarrassing.

Oops, that’s our bad.

We sent out this morning’s newsletter featuring the Free AI Readiness Benchmark, and then realized the link to the tool wasn’t working.

If you clicked and hit a dead end, we’re so sorry for the hassle. Here’s the correct link (we triple-checked it this time):

If you missed it, this 15-minute assessment is built for mid-market companies ($20–250M) to:

• Score your organizational, technical, and cultural readiness

• Spot blockers before they derail budgets

• Benchmark your team against peers

• Start aligning fast—no consultants or sales calls required

Thanks for your patience, and for being part of a community that’s ready to move beyond the AI hype and into real, measurable results.

Stay sharp,

Cat Valverde
Founder, Enterprise AI Solutions
Navigating Tomorrow’s Tech Landscape Together

Hi there, Change-makers!

What if you could predict whether your AI strategy will actually work, before you burn through Q3 budget on tools and teams? Today’s edition is all about clarity: how to measure your AI readiness fast, and why digital twins might be the key to building agents you can actually trust.

Plus in the news, Amazon reveals its GenAI war map, Google gives your search results a voice, and robots are ready to cash in on a $50T playground.

Let’s assess, simulate, and scale.

Enterprise AI Daily // Created with Midjourney

If you’re leading a $20–250M organization, chances are “explore AI solutions” is somewhere near the top of your 2025 strategy. But here’s the trap: without a clear-eyed look at your starting point, you risk expensive experiments with zero ROI. We sat down with Mindaugas Maciulis, Founder of Strategic AI Advisors, to understand where he sees businesses missing the mark.

“We designed this assessment as the first step in our flagship system, AImpact OS, a modular framework that helps mid-market firms assess, align, architect, automate, and amplify operations using AI,” he says. “Speed to value is the difference between being a mid-market leader and being disrupted, and this assessment helps leaders stop dabbling and start delivering.”

Before You Bet Big, Benchmark. No sales calls. No spam. Just signal over noise. Image: Strategic AI Advisors

His AI Readiness Assessment is a sharp, 15-minute diagnostic tool built to:

• Score your organizational, technical, and cultural readiness.

• Flag bottlenecks before they crush your timeline or budget.

• Benchmark your firm against industry peers to spot gaps and opportunities.

Why it matters:
68% of mid-market execs say AI is a top-three priority, but fewer than 20% feel confident they can deliver. That’s not a tooling issue. That’s an alignment crisis.

One COO who took the assessment found their biggest issue wasn’t their tech stack, it was inconsistent workflows across regional teams. Fixing that unlocked 3 AI use cases and shaved 12% off operating costs in a single quarter.

If you're not ready to benchmark just yet, start here:

• Who owns AI strategy internally?

• Are ops, IT, and business teams aligned or building in silos?

• Is leadership clear on what success looks like?

If those questions gave you a sinking feeling—good. It means you’re ready to face reality.

Image: Danny Lloyd, Lisa and Louise Burns in 1980 horror film The Shining (Rex Features)

What to Watch: Why Digital Twins Are the Key to Trustworthy AI Agents

You want AI agents that make you money, not mistakes. But giving AI autonomy without context is like handing car keys to a toddler. That’s why digital twins are about to become the MVP of enterprise-grade AI.

Think of it like this: Chatbots were GenAI 101. Digital-twin-trained agents are 400-level enterprise ops.

Here’s why this matters:

• Simulation before execution: You can test AI decisions in a digital twin before deploying them IRL.

• Enterprise context built in: Agents don’t just guess—they understand environments, constraints, and goals.

• Controllability restored: Digital twins bring transparency to decision-making and help mitigate risk at scale.

The bottom line: If your AI isn’t aware of how your business actually works, it’s not intelligent, it’s just improvising.

Enterprise AI Daily // Created with Midjourney

News You Can Use

Amazon’s Andy Jassy Breaks Down AI Strategy
The AWS boss just delivered his vision for how Amazon will use GenAI to dominate everything from cloud to commerce. Spoiler: foundation models are now table stakes.
Read more →

Google Wants to Narrate Your Search Results
Summaries? Cute. Google’s next move: audio briefings generated from your search queries. Welcome to the age of “Search-as-a-Service... with a voice.”
Full scoop →

Robots, Assemble: Physical AI Eyes a $50T Market
A new wave of robotics is coming for logistics, elder care, agriculture, and everything in between. The future isn’t virtual—it’s embodied.
Get the report →

What Top Execs Read Before the Market Opens

The Daily Upside was founded by investment professionals to arm decision-makers with market intelligence that goes deeper than headlines. No filler. Just concise, trusted insights on business trends, deal flow, and economic shifts—read by leaders at top firms across finance, tech, and beyond.

Join 1M+ professionals who stay informed before the rest of the market catches up.

TL;DR:

• Strategic AI Advisors launched a free, no-fluff AI Readiness Benchmark for mid-market firms. 15 minutes = clarity, alignment, and fast ROI.

• Digital twins are how you build AI agents that act rationally, predictably, and contextually at scale.

• Amazon’s making GenAI foundational, Google gives search a voice, and embodied robotics are targeting the entire global economy.

Stay sharp,

Cat Valverde
Founder, Enterprise AI Solutions
Navigating Tomorrow's Tech Landscape Together

Hello Leaders!

If you still think AI in the enterprise is mostly buzz and brainstorms, Kraft Heinz just served a sizzling counterpoint. From robotic mayo bots to AI-powered mac and cheese pricing models (no joke), they’re making a strong case for why slow-and-steady AI adoption might just win the profitability race.

Today we’ll unpack Kraft’s AI playbook, peek into the administrations plans for AI, and run down the latest AI-fueled moves from TikTok, Reddit, and Nvidia.

Let’s dig in.

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What’s the secret to staying ahead of the curve in the world of AI? Information. Luckily, you can join 1,000,000+ early adopters reading The Rundown AI — the free newsletter that makes you smarter on AI with just a 5-minute read per day.

Sign up to start learning.

Kraft Heinz’s AI Playbook: Boring? Brilliant? Definitely Bankable.

What does a 150-year-old ketchup company know about AI? Apparently, more than most.

Kraft Heinz is flipping the script on “legacy enterprise inertia” with an AI strategy that’s both practical and profitable. The company has embraced dozens of use cases across supply chain, marketing, and finance, and they’re now capturing $30 million+ in annual value from AI.

Some standouts:

• Auto-pricing for CPGs: Their AI models can tweak product pricing across 250,000 stores weekly.

• AI demand forecasting: Kraft’s algorithms now predict demand more accurately than human planners.

• AI in creative ops: They’ve built an in-house content engine to automatically generate on-brand assets, cutting costs and turnaround time.

Kraft Heinz didn’t go all-in overnight. They started with low-risk experiments, then built infrastructure and hired AI specialists to scale intelligently.

Why it matters for enterprises:
This is a masterclass in AI ROI, and one that doesn’t hinge on moonshots or vanity projects. Kraft focused on internal efficiency, customer insight, and bottom-line outcomes. That’s a blueprint every ops and marketing leader should bookmark.

What to watch: Uncle Sam’s AI Overhaul

Image: ZDNet

While everyone’s busy fine-tuning customer journeys and sales funnels, the real AI transformation might be headed to government cubicles near you.

A leaked strategy doc from the Trump administration details a sweeping federal plan to “AI-ify” everything from healthcare to defense to tax audits. It appears the goal is to make the U.S. government a leaner, faster, algorithmically-optimized machine, with some bold targets for implementation, oversight, and adoption.

A few eye-openers:

• Agencies would be required to audit their processes for AI opportunity.

• Procurement rules would be updated to accelerate adoption (goodbye, 12-month RFP delays).

• There’s even a push to upskill federal employees to manage and supervise AI tools.

Why it matters for enterprises:
If the U.S. government moves forward with centralized AI adoption, it won’t just reshape internal ops, it could send massive signals to federal contractors, vendors, and regulated industries. From compliance to competition, the ripple effects could hit everything from insurance to infrastructure.

Also: if Washington finally gets its digital act together, it might raise the bar for what “good enough” looks like in the private sector.

Enterprise AI Daily

AI News You Can Use

Nvidia makes a sovereign AI pitch to Europe
The chip giant is courting EU nations with its vision of “sovereign AI”: decentralized, nationally-controlled AI infrastructure. The goal: Let countries train and deploy LLMs without handing data to U.S. tech firms.
→ Get the report

Reddit rolls out AI ad targeting
Reddit’s new AI-powered ad tools let brands target conversations (not just keywords), helping marketers insert ads where users are already talking. Think: chicken sandwich memes meets precision marketing.
→ Read more

TikTok expands AI-generated video options
Creators can now generate AI-powered video intros, transitions, and captions straight from the app. Expect ad creatives, influencers, and brand marketers to start testing this ASAP.
→ Full story

TL;DR:

• Kraft Heinz is quietly becoming an AI efficiency machine—banking over $30M+ in annual ROI with smart, scalable use cases.

• The U.S. government’s leaked “AI-ify everything” strategy could reshape procurement, compliance, and expectations across the public and private sectors.

• Nvidia, Reddit, and TikTok are all leaning into AI’s next frontier: sovereignty, precision targeting, and ultra-fast content generation.

That’s a wrap on today. Whether you’re making ketchup or making movies, the AI stakes are rising and the playbooks are evolving. Which role will you write for your business?

Stay sharp,

Cat Valverde
Founder, Enterprise AI Solutions
Navigating Tomorrow's Tech Landscape Together

Hi again, AI Trailblazers!

There’s a lot of noise in AI right now (literally—see the Google podcast news below), but beneath the hype, we’re watching a very real shift unfold. Tools that started as playthings are now deeply embedded into our workflows, and the smartest enterprises are building entirely new growth paths around it. Today, we dive into the unexpected places AI is thriving, the overlooked areas you should probably care more about, and a subtle but significant pivot in enterprise hiring strategy.

Let’s unpack.

The AI Cambrian Explosion

This is the second Cambrian explosion; just like the first unleashed a burst of biological complexity, AI’s surge is unleashing a sudden, diverse evolution of tools transforming how we think, work, and create.

The rise of AI tools post-GPT is being hailed as nothing short of a second Cambrian explosion. In the wake of OpenAI’s breakthrough, entire sub-industries have emerged. Image generators like Midjourney and Stability, text-based tools like Jasper and Notion AI, and education-focused platforms like Scribe and Eduaide are infiltrating core business operations.

Why should enterprises care?
Because we’ve moved from individual productivity to institutional transformation:

• Text AI isn’t just writing memos; it’s powering custom legal summaries, RFP generators, and internal Q&A bots.

• Image AI is speeding up prototyping, UI/UX workflows, and brand content creation, cutting creative cycles by 50-70%.

• Education AI is fueling custom LMS, onboarding, and internal knowledge bases, tailored by team, function, or language.

The takeaway: This is no longer about exploring use cases. It’s about operationalizing them at scale. And those who treat it like a phase risk falling behind fast.

What to Watch: The Silent Signal in AI Strategy

Why Talent Optimization Might Be Your Best AI Play Yet. Image: Enterprise AI Daily // Created with Midjourney

Everyone’s talking models and margins, but few are talking org design. The most overlooked opportunity in AI isn’t generative models or even data strategy. It’s aligning your human capital to accelerate your AI goals.

Here’s the plot twist:

• Companies chasing AI wins are often misaligned internally. AI-savvy talent is siloed, and non-technical teams are left guessing.

• The smart shift = Building AI fluency into ops, customer success, and frontline workflows, not just engineering or R&D.

• And yes, that means your next enterprise-wide initiative may need an AI-enabled org chart, not just an LLM license.

Enterprise takeaway: If AI is everyone’s job, but no one’s responsibility—you’re going nowhere fast.

Start learning AI in 2025

Keeping up with AI is hard – we get it!

That’s why over 1M professionals read Superhuman AI to stay ahead.

• Get daily AI news, tools, and tutorials

• Learn new AI skills you can use at work in 3 mins a day

• Become 10X more productive

Sign up and start mastering AI

Enterprise AI Daily // Created with Midjourney

News You Can Use

Google’s AI Podcast Generator Just Dropped—and It’s Weirdly Good
Google is experimenting with AI-generated podcast scripts, complete with synthetic voices. While not ready for prime time, it signals a shift in how branded content, internal comms, and even investor updates might be produced.
Listen in →

BT’s CEO: AI Could Replace 10,000 Jobs—But That’s Not the Story
British Telecom’s new CEO announced a vision for AI-driven streamlining. But between the headlines, the real message is clear: enterprises aren’t using AI to cut corners—they’re using it to fundamentally redefine job roles.
Get the report →

China’s AI Models Now Sort Data Like Humans Do
A new study out of China shows AI sorting information based on human-like patterns—prioritizing semantic and contextual relevance, not just statistical likelihood. This could be a major leap for enterprise search, legal review, and document triage systems.
Full story →

TL;DR:

• AI tools are no longer experimentism, they're business infrastructure.

• The biggest AI opportunity: Talent alignment, not tech stacks.

• Google's AI podcasting shows where content ops are headed.

• BT and others are redefining jobs, not just replacing them.

• AI is learning to sort like humans, not just compute like machines.

Don’t forget, The smartest shift in AI right now isn’t “what can it do?” It’s “who is doing it, and how are they being organized?”

Stay sharp,

Cat Valverde
Founder, Enterprise AI Solutions
Navigating Tomorrow's Tech Landscape Together