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.

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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.

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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!

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

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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.

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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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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.

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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

TGIF!

It’s Friday, and while the rest of the world is clocking out, AI is…well, cloning Steph Curry and reviving Barbie's career. This week’s headlines had everything: generative ads at the NBA Finals, OpenAI cozying up with Mattel, and researchers making more than NBA rookies. We’ve got your wrap-up of enterprise AI’s wildest moves, and what to watch before Monday hits like a Slack notification from legal.

Let’s dive in.

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AI’s Big League Debut:
Kalshi’s AI-Generated Ad Made It to the NBA Finals. Here’s Why That’s a Big Deal.

If you blinked during Game 1 of the NBA Finals, you might’ve missed history in the making. Not a buzzer-beater, an ad, created by AI startup Kalshi using Google’s Veo 3, featuring generative AI footage of Steph Curry in a surreal, slo-mo, semi-dystopian arena. The message: Bet on real-world events, not games.

Why this matters for enterprises:

• Generative AI is moving beyond meme fodder. This ad is proof that major brands are taking AI seriously as a creative partner, not just a novelty.

• Google Veo 3’s debut shows we’re entering a new phase of video AI; think less "deepfake uncanny valley," more "Hollywood visual effects on-demand."

• Regulated industries are finding new storytelling lanes. Kalshi, a federally regulated prediction market, is using AI to make complex products pop on screens where attention is gold.

Bottom line: Your brand’s next flagship ad campaign might not need a director, it may just need a prompt.

What to Watch
OpenAI x Mattel = Plastic Fantastic Meets AI Magic

Enterprise AI Daily

Back in April, we told you about Barbie’s business model with Google. Now she’s back with more iconic partnerships and biz strategy. OpenAI just dropped a case study that’ll make any enterprise toy with nostalgia-fueled IP take notice. The partnership with Mattel is bringing iconic brands, Barbie, Hot Wheels, UNO, etc., into the ChatGPT ecosystem. You can now roleplay as a Barbie astronaut or race Hot Wheels through conversational AI. The dream.

Why it’s more than playtime:

• This is enterprise-grade brand extension. Mattel is using AI not just to delight kids but to build interactive, story-rich ecosystems that double as product funnels.

• OpenAI’s GPTs-as-IP-experiences model is gaining traction. Think of it as the “Disney+ for AI”: a branded world where fans interact directly with characters and stories.

• It’s data gold. Every chat fuels insights into how consumers engage, shop, and imagine.

Takeaway: If you have characters, stories, or fanbases, there’s a GPT-shaped sandbox waiting for you to play in.

I know when that botline bling, that can only mean one thing.

Botline Bling:

1. AMD Drops New AI Chips, Altman Approves
   With OpenAI’s Sam Altman onstage, AMD revealed its next-gen Instinct MI325X chips. They're gunning for Nvidia’s throne with faster performance and more memory for enterprise-scale models.
   → Read more

2. Meta Is Paying AI Researchers NBA-Level Salaries
   Mark Zuckerberg is dropping seven figures to keep top AI minds at Meta. When AI engineers start making more than quarterbacks, you know the enterprise AI war chest is in full swing.
   → Full scoop

3. AI Fertility Tech Is Now a Thing
   Star Sperm? AI-powered fertility models are here to improve conception rates—and they’re learning from 40,000+ IVF cases. Early data shows higher success rates in early-stage trials.
   → Get the report

TL;DR:

• Kalshi’s AI ad hit the NBA Finals using Google Veo 3, changing the game for generative brand storytelling.

• OpenAI + Mattel means Barbie just got a chatbot. Enterprises with IP should be paying attention.

• AMD’s new AI chips, Meta’s million-dollar hires, and AI fertility tech are redefining speed, talent, and even family planning.

What a week! Stay hydrated, get some rest, and we’ll see you back here Monday.

Stay sharp,

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

Welcome back, Leaders!

When it comes to rolling out AI across your org, it’s not just the tech stack that needs an upgrade. It’s the trust stack. In today’s issue, we dig into a game-changing mindset shift from a Fortune 100 giant that’s quietly winning at AI adoption. Plus, Hollywood swings at generative AI (again), and Amazon makes your Prime Day shopping even more predictive. Let’s unpack the big levers and legal dramas.

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How TIAA is Winning the AI Mind Game
Employee trust isn't a vibe. It's a strategy.

Rashmi Badwe of TIAA Wealth Management at this week's Fortune COO Summit. Image: Fortune

In a rare peek behind the enterprise AI curtain, TIAA’s Wealth Management Chief Operating Officer shares what’s actually moving the needle on adoption: psychological safety. According to Rashmi Badwe, it’s not just about teaching employees how to use AI, it’s about making them feel safe enough to explore it without fear of replacement or ridicule.

The key is in reframing AI as a “co-pilot,” not a competitor. That small semantic shift opens the door for experimentation, and in turn, innovation. The company even deploys internal "prompt libraries" so workers can play without pressure.

Why enterprises should care:

• No adoption = no ROI. Period.

• Psychological safety drives curiosity, which drives iteration, which drives outcomes.

• Leaders must set the tone, or risk building unused tools.

This isn't a soft skill story. It’s a scale skill story. And it’s a reminder that your biggest transformation lever might not be code; it might be culture.

What to Watch
Disney & Universal vs. Midjourney: The Showdown Begins

If your generative AI outputs are even adjacent to someone else’s IP, you could be in hot water. Image: Enterprise AI Daily

Back in March, we reported on The Ghibli Effect after OpenAI’s latest demo featured stunning AI-generated images “inspired by” Studio Ghibli, a Japanese animation studio based in Koganei, Tokyo. Now, two titans of entertainment dropped the legal hammer on Midjourney, the AI image generator.

Their claim: It’s gobbling up copyrighted character images to fuel its creations, without consent, without compensation, and with massive implications for content ownership.

Why it matters for enterprises:

• If you’re using generative AI for marketing, visuals, or content—take note. The copyright line is still blurry, but lawsuits like this one are redrawing it in real-time.

• Midjourney’s defense could shape fair use precedents across creative industries.

• It signals a larger reckoning: When does inspiration become infringement?

Your legal team should probably start warming up.

Enterprise AI Daily // Created with Midjourney

In the News

1. FDA Clears First-Ever AI for Drug Development
   The FDA has approved a drug that was discovered with AI from start to finish. The approval sets a new precedent and may speed up timelines across the pharmaceutical industry.
   → Read more

2. Amazon Launches 3 AI Tools to Turbocharge Delivery
   Amazon's latest AI suite predicts demand, reroutes packages on the fly, and even adjusts warehouse staffing in real time. Smarter logistics = faster shipping.
   → Full scoop

3. Meta’s ‘AI World Model’ Could Be Key to Smarter Robots
   Meta dropped a massive new AI model built to simulate the real world, aimed at training self-driving cars and autonomous robots. It’s basically a sandbox for smart machines.
   → Get the report

TL;DR:

• TIAA’s secret to AI adoption: Create psychological safety and stop scaring employees with Skynet metaphors.

• Disney and Universal are teaming up to sue Midjourney. Expect ripple effects for all AI-generated content.

• FDA approves AI-discovered drug, Amazon speeds up delivery with new tools, Meta simulates the world for robots.

Before onboarding any new AI tools, Enterprises need alignment. Between teams. Between humans and machines. Between innovation and responsibility. Today’s stories are a reminder that great AI strategy starts with culture, not code.

Stay sharp,

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

Hi there, Change-makers!

Who said tech rivalries couldn’t come with a side of...collaboration? Today we’re diving into a surprising OpenAI-Google cloud pact, spotlighting the AI-ification of your Google searches, and tracking a high-stakes game of AI musical chairs.

Let’s get into it.

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Enterprise AI Daily // Created with Midjourney

OpenAI x Google Cloud: Enemies With Benefits?

File this under “co-opetition” with a capital “Huh?”—OpenAI has inked a massive cloud deal with Google, tapping Google Cloud for AI workloads despite being, well, direct rivals.

The deal is unprecedented and adds Google to OpenAI’s already complex infrastructure cocktail of Microsoft Azure and Oracle. What makes this even juicier, Google’s DeepMind has been racing OpenAI on general intelligence and model performance for years.

Why this matters for enterprises:

• Cloud costs are rising. Even OpenAI is hedging its compute bets.

• Multicloud is in. If you’re still single-cloud loyal, it might be time to rethink your vendor strategy.

• AI infra is the new arms race. Whoever controls the chips and GPUs wins— and OpenAI’s moves suggest flexibility beats loyalty.

Bottom line: When even AI giants need all the friends they can get, your enterprise strategy should prioritize resilience over exclusivity.

Image: Vox

What to Watch: Google’s AI Eats the Search Engine

Google’s AI Overview is now officially default behavior for many queries. Type in something like “how to clean suede shoes,” and instead of a wall of links, you’re served a shiny Gemini-generated answer (whether you asked for it or not).

Why you should care:

• SEO as we know it is dying. Enterprises that relied on organic search for discovery are in for a rude algorithmic awakening.

• Consumer trust in answers is up for grabs. Google’s AI summaries have been caught hallucinating everything from poisonous pizza recipes to very questionable health tips.

• Pay-to-play becomes dominant. If AI frontloads content, expect ads and partnerships to become the only way through the fog.

What’s next: Google has reportedly slowed the full rollout after user backlash, but the long-term trend is clear: AI is not just in your search, it’s replacing your search.

Enterprise AI Daily // Created with Midjourney

News Roundup

Meta grabs Scale AI’s Alexandr Wang to lead its new Superintelligence Lab
Scale’s prodigy CEO is heading to Meta to build AGI. Think of it as Zuck’s Hail Mary pass in the intelligence race.
→Full scoop

Vast Data eyes a $25B valuation for its AI-native storage platform
The next infrastructure gold rush is in smart storage — and Vast is leading the charge.
→Read more

Mistral drops Europe’s first AI Reasoning model
France says “bonjour” to AGI ambitions with a model built for next-gen inference and logic.
→See the model

TL;DR:

• OpenAI is using Google Cloud, proving cloud monogamy is overrated.

• Google’s AI-generated summaries are becoming the new face of search, and not everyone’s happy.

• Meta hires Scale AI’s CEO to helm a new AGI lab, Vast Data makes storage sexy, and Mistral flexes European AI muscle.

Stay sharp,

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

Hi Innovators!

Today, we’re cracking open a fresh batch of AI tea, served Apple-style, spiced with hallucinations, and chased with rabbit-hole wanderings and geopolitical games. From academic shade to existential design flaws, we're pulling no punches.

Let’s dig in.

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Enterprise AI Daily

Apple’s AI Research: Burn Book or Big Warning?

In a deliciously timed paper, Apple’s AI researchers just dropped a truth bomb about their rivals’ large language models: they’re “easily quitters.” According to Apple, popular LLMs (cough ChatGPT cough) struggle to stay coherent when prompted to reason through multiple steps. They hallucinate. They give up. They spiral.

Sound familiar?

Meanwhile, Axios is digging into the same issue, pointing out that these so-called hallucinations aren’t random glitches, they’re the inevitable result of how these models are built. LLMs aren’t logic engines. They’re pattern predictors. That means asking them to “reason” is like asking a fortune cookie to explain philosophy: fun, but fundamentally broken.

Why enterprises should care:

• If you’ve got complex workflows that require step-by-step reasoning, don’t bet the farm on current LLMs.

• Apple’s critique is a signal that reliability and reasoning will define the next AI arms race.

• We may be nearing the limit of “bigger is better.” Now it’s about “smarter is safer.”

Enterprise AI Daily // Created with Midjourney

What to Watch: ChatGPT’s Rabbit Holes, Explained

Ever asked ChatGPT one simple question and ended up four scrolls deep into a dissertation on Venetian trade routes, a Wikipedia knockoff, and an unsolicited poem?

Apparently there’s a scientific reason behind ChatGPT’s tendency to go full Alice in Wonderland on your queries. It all comes down to the training data: the model tries to maximize “usefulness,” but it interprets that as more words = better answer. That means you get a deluge of semi-relevant but tangential info. Hello, rabbit hole.

Enterprise takeaway:

• Be strategic in prompt design: brevity is your friend.

• Use guardrails, especially in customer-facing apps. No one wants a 5-paragraph essay when they asked for store hours.

Enterprise AI Daily // Created with Midjourney

In the News

1. Britain vs. Getty: AI Copyright Smackdown
The UK is proposing new AI copyright rules, and Getty is not amused. The stock image giant says the proposed law gives AI firms a free pass to scrape its content.
Get the report
→ Read more

2. Meta Goes Bigger, Again
Meta just pumped billions more into scaling its AI infrastructure. Zuckerberg’s betting on model-size supremacy—again—despite increasing skepticism about scalability vs. usability.
→Full story

3. Who Wins at AI Diplomacy?
Anthropic, OpenAI, Meta, and Gemini just went head-to-head on a new Diplomacy benchmark. Spoiler: Gemini didn’t dominate.
Read more
→Guess who

TL;DR:

• Apple says other LLMs "collapse and quit" at reasoning.

• Hallucinations aren’t bugs, they’re the blueprint.

• ChatGPT’s long-winded answers are the design, not a glitch.

• UK copyright laws are ruffling Getty’s feathers.

• Meta doubles down on “big AI.”

• Diplomacy benchmark test throws curveballs at top LLMs.

That’s all for today, friends. Whether you’re scaling models, watching for hallucinations, or just trying to keep your AI from turning into a verbose philosopher, remember: smart beats shiny every time.

Stay sharp,

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

Happy Monday!

The days of digging through endless folders, mislabeled files, and mystery PDFs are numbered. AI is gunning for your company’s document chaos, and finally winning. In this issue, we explore how smart document AI is becoming the silent productivity hero across sectors, why mathematicians are secretly scrambling to outsmart AI, and what Meta’s rumored $10B investment signals for the enterprise stack.

Let’s dive in.

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Smart AI Is Decluttering Enterprise Document Chaos

From burden to brilliance: how intelligent document processing is becoming mission-critical. Image: Enterprise AI Daily // Created with Midjourney

Organizations are seeing document AI shift from a “nice-to-have” to an operational must. AI is now summarizing legal briefs, validating invoices, and even predicting compliance risks. For industries like insurance, healthcare, and finance, where regulatory documents flow faster than coffee at a Monday morning board meeting, it’s a game changer.

Key points:

• One insurer used AI to process 5 years of claims in 3 months—slashing review times by over 80%.

• AI-driven classification tools are improving accuracy rates beyond human-level benchmarks.

• Enterprise adoption is accelerating due to LLMs trained on internal, domain-specific data.

Why it matters: Enterprises sit on mountains of unstructured data. Smart document AI converts paper pain into strategic leverage. This isn’t automation for automation’s sake; it’s operational clarity at scale.

What to Watch: The Secret Meeting to Outsmart AI

When math minds meet the AI menace. Image: Scientific American

In a story that sounds like the plot of a Christopher Nolan movie, Scientific American reports on a hush-hush gathering of mathematicians aiming to design puzzles and proofs that AI can’t solve. The motive: preserve the sanctity of mathematical creativity and safeguard knowledge work that could soon be eclipsed.

What’s going on:

• The gathering, called the "Maths and Machines" summit, tackled AI’s growing success in solving Olympiad-level math problems.

• Researchers debated how to test true understanding in machines, not just pattern mimicry.

• Some proposed designing problems with abstract leaps that require “aha” intuition, currently out of reach for even the best models.

Why it matters: As LLMs inch closer to advanced reasoning tasks, the boundary between "assistive tool" and "replacement threat" blurs. This secretive summit underscores a growing tension: how do you innovate without letting the machines steal the show?

Enterprise AI Daily // Created with Midjourney

In the News

1. OpenAI’s Secret Video Tool Leaks Early
   OpenAI’s internal pitch deck for “Video-to-Anything” was leaked over the weekend, revealing a new generative tool capable of real-time video transformation. Think Runway, but on steroids—and with enterprise-level integrations. Expect marketing departments everywhere to start hyperventilating.
   → Full scoop

2. Meta Eyes $10B Stake in Scale AI
   Meta is in advanced talks to invest over $10 billion in Scale AI, the data-labeling giant fueling the next generation of AI models. The move would give Meta a deeper grip on training data pipelines—aka the lifeblood of AI systems.
   → Read more

3. Alexa Goes Premium (and Surprisingly Human)
   Amazon just launched early access for “Alexa Plus,” a $5.99/month premium voice assistant that remembers past conversations, offers proactive recommendations, and doesn’t sound like a toaster. Will consumers finally pay for a smarter assistant? Will enterprises follow suit with branded AI voices?
   → Get the review

TL;DR:

• Smart document AI is reducing clutter, speeding up compliance, and unlocking buried insights.

• Mathematicians are secretly plotting to keep AI from outsmarting human intuition.

• OpenAI’s leaked tool hints at a new era of generative video—brace yourself, Adobe.

• Meta’s $10B play into Scale AI signals a race to control the most valuable asset: clean training data.

• Alexa’s subscription model could foreshadow how we all interact with enterprise AI in the near future.

Welcome to the post-chaos era, where AI is rewriting how you operate at scale. And while the machines learn math, enterprise leaders would do well to learn how to build smarter stacks.

Stay sharp,

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

TGIF!

AI might be inching toward automating everything from your inbox to your boardroom, but one space still clings to the grip of human nuance: legal deals. DocJuris just dropped a fresh survey, and the message is loud and clear: AI can prep the paperwork, but it’s people who bring the pen to the dotted line.

Today, we’re diving into why enterprises can’t automate away everything just yet, how central banks are stepping into real-time AI fraud monitoring, and the shifting tides in higher ed, finance search, and AI policy regulation.

Let’s roll.

Enterprise AI Daily

AI Can Draft Your NDA, But It Can’t Close the Deal

Despite the surge in enterprise legal AI tools, a new DocJuris survey shows that 79% of corporate legal teams still believe the final negotiation and approval process must involve humans.

Here’s the kicker:

• 86% of respondents said AI helps reduce time reviewing contracts.

• 64% use AI to assist in redlining and flagging risk.

• But only 12% would let AI lead negotiations or close a deal.

AI is transforming the prep work, but trust and nuance still demand human judgment, especially when it comes to regulatory implications, relationship dynamics, and high-stakes clauses. For legal and compliance teams trying to scale, it’s not about removing people from the process, it’s about reallocating them to where they matter most.

Why enterprises should care:
This is your cue to stop thinking about AI as a full replacement and start investing in it as an accelerator. Scale smarter by using AI for prep, not decision-making, in legally sensitive workflows.

Bottom line: Your legal stack should support the humans, not sideline them.

Image: The Bank of England

What to Watch: The Bank of England’s AI Fraud Watchdog

The Bank of England is piloting an AI system to monitor real-time payments and flag potential fraud across the UK’s banking system.

Why it matters:

• Real-time payments are exploding in volume, and fraudsters love speed.

• The new system aims to spot suspicious patterns mid-transaction before money moves.

• It also tests how AI can be integrated securely into the national payment infrastructure.

Enterprise takeaway:
If the BoE’s experiment goes well, expect similar moves from the Fed, ECB, and beyond. For companies processing payments at scale, this could mean more fraud checkpoints, as well as faster fraud detection and fewer chargebacks.

Watch this space, especially if you’re building or integrating payment platforms.

Enterprise AI Daily // Created with Midjourney

News You Can’t Miss

1. Higher Ed’s AI Future Begins With the Right Questions
A new Forbes piece reminds us that colleges can’t just slap AI onto outdated models and expect magic. The smarter schools are rethinking everything, from curriculum design to admissions, with AI in the loop.
Read more →

2. Google’s AI Mode Adds Finance-Savvy Visualizations
Google just gave its AI search experience a financial facelift. Users can now get data visualizations (think graphs and charts) when searching things like “Apple stock vs. Tesla over 5 years.”
Full scoop →

3. AI Law Freeze? The Proposed Moratorium You Should Know About
A new proposal could halt the rollout of state-level AI regulations across the U.S. The argument: we need a coordinated federal strategy. The backlash: local innovation and protections might get squashed in the process.
Get the report →

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TL;DR:

• AI in legal deals: Automate the prep, but let humans seal the deal.

• This day in tech history: WWII's war tech paved the way for modern digital deception.

• BoE tests real-time fraud AI: National banks are quietly going cyberpunk.

• Higher ed needs a mindset shift: It’s not about using AI—it’s about rethinking systems.

• Google gets graphy: AI search gets more visual, especially for finance nerds.

• AI laws in limbo: State rules may be paused, and federal policy is in the hot seat.

That’s a wrap on another week. See you Monday!

Stay sharp,

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

Hello, Leaders!

Today’s lineup reads like a digital age fable: whispered Slack threads turn into sales leads, AI startups get sued by Reddit, and Geoffrey Hinton's out here launching a nonprofit to save us all. Whether you’re building tools, guiding policy, or just trying to decipher the AI alphabet soup, it’s clear the stakes are getting higher, the players more powerful, and the margins tighter.

Enterprise AI Daily // Created with Midjourney

Can AI Turn Slack Banter into Cold, Hard Cash?

Short answer: Yes. Long answer: Just don’t let it be your compliance officer’s nightmare.

Companies like Workheld, Gong, and SlackGPT are tapping into the goldmine of internal workplace chatter: mining conversations for signals about customer intent, product pain points, and market insights. Why? Because your sales team’s water cooler chat is more honest (and possibly more predictive) than your quarterly pipeline reports.

Here’s the enterprise playbook unfolding:

• Workheld is turning engineer chats into potential upsells and missed revenue flags.

• Gong and ZoomInfo are decoding CRM and meeting data to alert sales to hidden buying signals.

• Slack and Microsoft Teams could become your next-gen sales intel platforms (assuming you get buy-in from legal).

But don’t forget the fine print:

• Enterprises must be extremely cautious about privacy, consent, and internal comms monitoring.

• These tools are only as good as the guardrails you put in place. Otherwise, you risk turning helpful AI into creepy corporate spyware.

• And let’s be honest—if employees even suspect their casual Slack banter is being analyzed for sales potential, you're not just risking moral, you’re teeing up a trust crisis. The vibe quickly shifts from “collaborative” to “surveilled,” and suddenly, no one’s talking unless it’s in all caps.

Bottom line: If done right, workplace AI can nudge teams toward revenue without nudging them into a lawsuit, or a mutiny. But if you're serious about deploying conversational intelligence, start with a culture audit first. Respect, transparency, and a clear opt-in go further than any predictive model.

What to Watch: U.S. Health Advisory Calls Out AI's Youth Impact

Image: American Psychological Association

The U.S. Surgeon General just stepped in with a formal advisory: AI could be harming young people, and it's time for developers to design for their mental health, not just engagement metrics.

Why this matters:

• Most AI tools today—LLMs, recommender systems, image generators—weren’t built with teens in mind, yet they’re heavily used by them.

• The advisory urges ethical design practices, age-specific testing, and greater transparency.

Enterprise takeaway: If you’re in health tech, edtech, social platforms, or even retail, this will affect product compliance. Think GDPR meets Surgeon General meets AI.

The next frontier of AI regulation may start with protecting kids, and quickly spill over to enterprise user ethics.

When you realize the humans are still in beta.

AI News Not to Be Ignored

1. Geoffrey Hinton (aka "Godfather of AI") Launches Safety Nonprofit
   Hinton’s new org will focus on creating AI systems aligned with human values and reducing existential risk.
   Read more →

2. Amazon's New 'Agentic AI' Division Is Official
   They’re building proactive, autonomous agents—like Siri, if Siri got a promotion. Think customer service bots that don’t wait for input.
   Full scoop →

3. Reddit Sues Anthropic Over Alleged AI Training
   The lawsuit claims Anthropic trained Claude on Reddit data without permission. This could set new precedent for user-generated content rights.
   Get the report →

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TL;DR:

• Companies are mining internal chats for revenue signals. Smart…if legally airtight.

• The U.S. is signaling the start of AI safety rules—especially for protecting kids.

• Amazon’s launching “Agentic AI” systems. Autonomy, meet accountability.

• Geoffrey Hinton’s building the AI safety net he wishes already existed.

• Reddit’s lawsuit could change the game for training data permissions.

Your AI stack is now a culture call, a legal question, and increasingly, a moral one. If your AI strategy doesn't include people-first guardrails, consider this your invitation to evolve—before regulation (or Reddit) comes knocking.

Stay sharp,

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

Hi there, Innovators!

There’s a quiet shift happening in enterprise corridors across America, and it’s no longer just about adopting AI, it’s about mandating it. In today’s issue, we unpack the new corporate mantra: “Use AI or lose your edge (or maybe your job).” Meanwhile, Meta’s nuclear energy play hints at the massive power demands of tomorrow’s models.

No AI? No Job. Why More Companies Are Mandating AI Use

The AI adoption curve is now a hiring filter. Source: The Washington Post

A growing list of companies, from finance to customer service to marketing, aren’t just nudging employees toward AI tools, they’re making adoption non-negotiable. We’re talking about mandatory ChatGPT onboarding sessions during new hire training, internal “prompt certification” tests as part of promotion criteria, and job descriptions that sound more like they’re hiring prompt engineers than account managers.

While many of us debate about AI’s role, others are making it as an important performance benchmark. Duolingo’s Chief Engineering Officer Natalie Glance outlined what the AI-first strategy meant in practice. AI, she emphasized, should now be the default approach for tackling problems—and as a result, productivity expectations would rise. Her guidance to the team: dedicate 10% of your time to exploring and experimenting with AI tools, approach every task with AI first, and actively share your findings across teams to accelerate collective learning.

Here’s why this matters:

• AI is the new Excel. Mastering AI tools is now table stakes, the same way spreadsheets became a non-negotiable business skill in the early 2000s. Those who don’t adapt will be outpaced (or outplaced).

• Enterprise risk has flipped. Not using AI isn’t neutral anymore. It’s seen as a missed opportunity, a cost inefficiency, and—depending on your sector—a potential compliance or security risk if teams are operating inefficiently or going rogue with unsanctioned tools.

• Training gaps are widening. Teams without formal AI training are falling behind fast, creating new tiers of productivity within the same org. The result is a quiet but growing internal divide between AI-native employees and AI-avoidant ones.

Enterprise takeaway:
If you’re not building structured, ongoing AI upskilling into your org strategy, you’re not future-proofing your talent, or your competitiveness. Think beyond workshops: build internal AI enablement teams, create usage benchmarks by role, and don’t be surprised if “AI literacy” audits soon become part of HR reviews, performance check-ins, and even board-level reporting.

Digital transformation just became digital expectation.

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What to Watch: Meta’s Nuclear Power Play

Zuck’s data-hungry empire just made a bet on the atom. Source: Meta

Meta is now backing a nuclear-powered energy startup to fuel its AI future—because, apparently, the cloud needs a reactor now. As AI models become energy super-consumers (hello, 500x power growth), Big Tech is looking for ways to keep the lights on without incinerating their ESG goals. And don’t forget, Microsoft did something similar, and some might say more shocking, when they bought Three Mile Island as their next power source.

Why this is big:

• AI energy demand is unsustainable without innovation or risk (see: rolling brownouts).

• Enterprises might follow Meta’s lead, exploring on-site generation, energy hedging, or datacenter redesigns.

• Nuclear investment is about power control in a data economy.

Bottom line: Energy is now a core AI infrastructure strategy. And CIOs might need to start reading Popular Mechanics alongside Wired. The rest of us should stay on top of where this goes to keep a temperature (no pun intended) on the real world climate.

Quick Hits: AI News You Shouldn't Miss

1. California Senate Goes Full Safety Mode on AI Chatbots
   A new bill mandates clearer disclosures, safeguards for minors, and oversight protocols. This could set the precedent for state-level AI governance.
   → Full scoop

2. Smart Collars Meet AI: Now Your Dog Can Text You (Kinda)
   Fi’s AI-powered dog collar integrates with Apple Watch to detect behavioral changes. Corporate surveillance, but fluffy.
   → Get the report

3. Google Quietly Pauses “Ask Photos” AI Rollout
   The much-anticipated image search AI was pulled back after early hiccups, signaling internal caution on deploying consumer-facing LLMs.
   → Read more

TL;DR:

• Use AI or else: More companies are mandating AI use as a job requirement.

• Buzzword alert: “AI hygiene” is the new hot phrase. Build your protocols now.

• Meta goes nuclear: AI energy demands are so high, Meta’s investing in reactors.

• News to know: California pushes AI chatbot regulation, smart collars go AI-native, Google pauses photo AI search.

Welcome to the era of “must-use AI.” The lines between tech skill and job skill are disappearing fast, and energy may just be the next enterprise chokepoint. It’s time to operationalize, regulate, and scale, or risk watching your edge get automated away.

Stay sharp,

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

Hi there, Change-makers!

It’s easy to get swept up in the shiny promise of AI, but implementing it successfully is where companies trip, fumble, and faceplant. Today, we’re unpacking what not to do when onboarding AI, calling BS on some buzzwords, making sense of marketing hype, and peeking into the future of AI-powered humanitarian aid and advertising. Let’s go.

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Avoiding the AI Faceplant

Why most enterprise AI flops, and how to avoid being the cautionary tale. Image: Inc.com

If you’ve ever thought, “We need AI,” and then sprinted to the nearest vendor like it’s Black Friday at Best Buy in 2006, you’re not alone. And that’s exactly the problem. Integrating AI into a company is less about the tech itself and more about strategy, alignment, and change management.

While there’s no shortage of bold ambition when it comes to AI adoption, enthusiasm without strategy is how you end up with a chatbot no one uses, “automated” reports that misreport, or a pilot project that quietly dies in someone’s Google Drive.

The top reasons companies fail with AI come down to five very human mistakes:

1. Not defining the business problem. Hint: “We want to use AI” is not a problem statement.

2. Relying too much on vendors. Your vendor may know their product—but they don’t know your workflows, team, or KPIs.

3. Skipping the change management piece. If your people aren’t trained, engaged, and excited, your AI tools won’t get used.

4. Neglecting your data. Garbage in, hallucination out.

5. Treating AI like a plug-and-play tool. It’s not. It’s a system shift.

Enterprises don’t fail because the tech doesn’t work. They fail because they didn’t treat AI like a transformation.

Enterprise takeaway: Before buying that shiny new tool, ask: “What is the actual outcome we’re trying to drive?” Then build backwards—from culture to process to tech.

What to Watch

While marketing AI tools are booming, confusion reigns over what’s truly smart versus what’s just “fancy automation with better branding.” Image: Forbes

AI in Marketing: Help or Hype?

Why generative content isn't the whole picture (and how to play the long game).

Marketers have never had so many tools, or so much confusion. AI can now write, design, analyze, predict, and personalize. But the future of AI in marketing isn’t about automating output, it’s about augmenting insights.

Here’s what to watch:

• From Generation to Strategy: Generative AI is the front door, not the whole house. Strategic deployment means combining human creativity with predictive targeting, channel optimization, and iterative testing.

• Data Isn’t Optional: Marketers need to embrace first-party data stewardship like never before. AI only works if it’s trained on real signals, not vibes.

• The Rise of “Intelligent Orchestration”: AI that can adjust spend, swap creatives, and allocate across platforms in real time is coming fast—and it’s performance marketers’ new best friend.

Enterprise takeaway:
AI won’t replace marketers, but marketers who master AI will replace those who don’t. Stop thinking “content machine,” start thinking “intelligence engine.”

Bonus Insight: Stop asking “How do we use AI?” and start asking, “Where are we guessing, and how can we use AI to stop guessing?” That’s your strategic entry point.

News You Can Use

Three headlines worth more than a skim.

1. AI for Good: Crisis Answers in Real Time
   A nonprofit’s AI-powered tool is helping aid workers respond faster during humanitarian disasters—by answering critical questions like “Where can we find clean water?” using language models trained on emergency response data.
   Read more → MSN

2. Sora + Bing = AI Video for All
   Microsoft just added a free, Sora-powered video generator to Bing. Text-to-video tools are officially mainstream, and enterprise content creation just got weirder (and potentially cheaper).
   Full scoop → TechCrunch

3. Meta’s AI Ads Are Coming in 2026
   Meta announced its next wave of AI-powered ads that write themselves based on user signals and goals—expected to roll out next year. This could change how teams handle copy, creative, and spend across Meta’s entire ad suite.
   Get the report → The Verge

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TL;DR:

• AI fails aren’t tech issues, they’re people and planning problems.

• “Cognitive AI” = buzzword. Add salt.

• AI in marketing is evolving from content spam to strategy augmentation.

• Humanitarian tools, video gen, and self-writing ads are heating up this week.

Stay sharp,

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