AI feels like it is accelerating in every direction at once and the pressure to keep up is real. I talk through what I am seeing on the ground while speaking with CPAs, financial advisors, lawyers, and business owners, and why the “slow down” message from AI leaders is worth taking seriously. When hundreds of billions in venture capital floods the AI industry, those companies have to find customers fast, and that turns into a constant stream of tools, pitches, and urgency landing on your team. 

I make the case for slowing down to go fast: getting your leadership team aligned, naming what is already happening inside your organization, and choosing a clear starting point you can actually control. Instead of letting a third party vendor define your roadmap, we focus on building an AI strategy that fits your business, your risk profile, and your real workflows. We also get practical about why long range plans are shaky right now and why a three to six month planning window often beats a multi year bet in a fast changing generative AI market. 

We also zoom in on accountability. AI can help with decision processing and speed, but it will never be accountable for the decision. Humans are, which means leaders need clear ownership, thoughtful guardrails, and a realistic way to measure adoption and ROI. If you have been projecting confidence while feeling backstage stress, you are not alone, and you do not need to have everything figured out today. 

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If your competitor can buy the same AI models you can, what’s left that actually sets you apart? We start with that uncomfortable question and land on a simple truth: the edge has never been the tool, it’s the people using it. Customer service, responsiveness, delivery, logistics, sales execution, and the way your team shows up day after day still matter, even with powerful generative AI on every laptop.

We go deeper into the real differentiator most leaders are at risk of giving away: judgment. That instinct for what matters, what’s missing, and what will break later is earned through years of wins, failures, job changes, and hard calls. AI can summarize and suggest, but it doesn’t own your lived experience. The problem is that many leaders are starting to hand over decisions to the model too quickly, skipping the “wonder” and reflection that used to shape better answers.

Then we draw a personal parallel that makes the warning hit harder: surrendering control can happen slowly, one decision at a time, until something else is driving. The story of quitting alcohol and taking life back becomes a framework for how to use AI without letting it run your leadership, your culture, or your company. We also share why our workshops with the Vistage Network, and our push on building value from the foundation: who you are and how your team thinks.

If you want to use AI to become more competitive without losing the human strengths that made you successful, hit play. Subscribe, share this with a leader who needs the reminder, and leave a review with your take: where should AI advise, and where must humans decide?

AI pressure is everywhere right now and the easiest mistake is letting that pressure push you straight into tools, demos, and expensive pilots that never stick. We share why we launched Teleos Technology Partners and what we’ve learned after hearing hundreds of real AI journeys: the teams that win are not the ones chasing the newest model, they’re the ones that get aligned, collaborate deeply, and build with their people instead of around them.

We walk through a practical three-part recipe for successful AI implementation. First is leadership alignment that cascades through the organization, grounded in a clear acknowledgment that AI will reshape your business and your competitors. Then we zoom in on how to find the real friction across people, process, and systems so your AI strategy targets work that is manual, error-prone, and frustrating. Second is choosing an AI partner who treats the work as true collaboration, challenges assumptions, and invites your team into the design so what you deploy feels like your company, not a generic template.

From there we get tactical about deployment: why a strong feedback loop matters, how simple signals like thumbs up and thumbs down can drive continuous improvement, and how to keep the system learning what “good” looks like for your workflows. We also look ahead to the risk that’s quietly growing in the market: AI vendor lock-in. With so many startups and so much money flooding the space, you need transparency, a transferable architecture, and the option to bring AI in-house when the time is right.

If you’re trying to move fast without wasting money or control, this is for you. Subscribe for more, share this with a leader who’s feeling the AI heat, and leave a review with your biggest AI question.

The AI tool you’re excited about today could be acquired, reshuffled, or gone six months from now and that possibility can make any business owner hesitate. I unpack a question I hear constantly from leaders investing in AI for workflow automation and team support: what happens if the company we partner with gets bought by private equity, purchased by a strategic, or simply doesn’t make it?

We zoom out from the logo and talk about what you’re actually buying when you “buy AI.” The real value usually comes from execution: the people who learn your business, map your processes, build the integrations, and collaborate with you until the system is genuinely useful. When you take time to know the engineer doing the work and the team responsible for delivery, you reduce AI vendor risk in a way that contracts alone can’t. Those relationships create continuity, because the knowledge of your workflows and decisions lives with people, not a brand name.

I also share a simple mindset for AI due diligence that fits the reality of venture-backed AI startups: accept that not everyone wins, then protect your project by prioritizing trust, documentation, and the humans behind the build. If you’re trying to scale AI implementation without getting trapped by uncertainty, this conversation will help you move forward with clearer eyes and a steadier plan.

Subscribe for more practical AI leadership insights, share this with a friend who’s choosing an AI vendor, and leave a review with your biggest question about AI adoption.

Enjoying the show? Subscribe, share this with a leader in your organization, and leave a review with the biggest AI question your team is wrestling with.

I'm Craig Francisco, CEO , Vistage Speaker and 30 year Operator. I help privately held and family businesses turn their hard-earned domain intelligence into an advantage AI can't hand your competitor down the street. If your team is wrestling with where to start, the best place to begin is a conversation: www.craigfrancisco.com 

AI is getting so smooth that it can feel like “help” even when it’s quietly replacing your instincts. After a Vistage workshop with executives and business owners, we walk through a simple idea that keeps showing up in real organizations: reclaim your judgment before you scale anything with AI.

We talk about what we’re watching leaders do day to day with ChatGPT and other frontier models, how a few quick prompts can send you down a totally different path, and why that’s dangerous when you’re making high-stakes calls. Your experience, your failures, your wins, and your client context are not “nice to have” extras. They’re the asset. That human wisdom is what keeps AI from turning into generic advice that makes every company sound the same.

A standout story brings it to life: a business owner who nearly always wins proposals loads her work into an AI model for “a quick opinion” and almost edits away the very choices that make her proposals effective. We unpack why AI can be super confident with super limited context, and how leaders can set the tone so teams use generative AI responsibly without losing craft, voice, or customer understanding.

If you care about AI leadership, executive decision making, and building an AI strategy that actually creates a competitive advantage, this is a practical mindset reset. Subscribe for more, share this with a leader who needs it, and leave a review with your answer: where do you draw the line between AI help and AI control?

Enjoying the show? Subscribe, share this with a leader in your organization, and leave a review with the biggest AI question your team is wrestling with.

I'm Craig Francisco, CEO of AI23. I help privately held and family businesses turn their hard-earned domain intelligence into an advantage AI can't hand your competitor down the street. If your team is wrestling with where to start, the best place to begin is a conversation: www.craigfrancisco.com 

AI has a weird way of failing: not with a loud crash, but with quiet drift. You start with a promising idea, then weeks go by as everyone keeps “making it better” without a clear finish line, a real workflow target, or a definition of success. We’re talking about the pattern we’re seeing across companies that actually get results from AI and what the best leaders do differently from day one.

We share a hands-on story from a small business with 20 years of history, loads of data, steady inbound demand, and processes that must be documented with care. The breakthrough isn’t a magic prompt or a trendy tool. It’s the owner stepping up like a program manager: guiding development, testing what’s built, and giving consistent feedback so the system matches the messy reality of how work gets done. We also explain why the classic “I want this tool, tell me when it’s ready” approach almost guarantees disappointment with AI implementation.

We dig into why custom AI tools are more achievable now, how to think about frontier models versus closed or proprietary models, and how to keep your voice at the center so you’re steering the ship. If you’re serious about AI strategy, AI transformation, and practical business automation, this is a mindset shift worth stealing. Subscribe, share this with a teammate, and leave a review with the workflow you most want AI to improve.

Enjoying the show? Subscribe, share this with a leader in your organization, and leave a review with the biggest AI question your team is wrestling with.

I'm Craig Francisco, CEO of AI23. I help privately held and family businesses turn their hard-earned domain intelligence into an advantage AI can't hand your competitor down the street. If your team is wrestling with where to start, the best place to begin is a conversation: www.craigfrancisco.com 

Everyone can get AI now, so “we’re using AI” isn’t a strategy anymore. After a talk with HR leaders at the University of Toledo Family Business Center, we’re stuck on a bigger question: what actually makes a family business or privately owned company win when the same tools are available to your competitor down the street?

We dig into the human reality behind AI adoption inside organizations. The CEO or president feels the urgency to drive strategy. The people doing the work feel the risk, and sometimes real fear, about what changes mean for their jobs. Then HR leaders, CHROs, and talent directors sit right in the middle, trying to translate vision into action while keeping trust intact. That tension isn’t a side note, it’s the work.

The heart of the conversation is knowledge versus information. Information is abundant. Knowledge is judgment, especially when the manual runs out and a decision still has to be made. That judgment lives in your domain intelligence: the hard-earned context in your people’s heads, the patterns your teams learned over decades, and the “moat” that helped your business survive tough cycles. We end with a grounded way to approach AI: go back to what made you successful, get clear on what makes you unique, then start small, earn early wins, and let the results compound.

Enjoying the show? Subscribe, share this with a leader in your organization, and leave a review with the biggest AI question your team is wrestling with.

I'm Craig Francisco, CEO of AI23. I help privately held and family businesses turn their hard-earned domain intelligence into an advantage AI can't hand your competitor down the street. If your team is wrestling with where to start, the best place to begin is a conversation: www.craigfrancisco.com 

AI is getting cooler by the week, but I think the next big shift has nothing to do with the newest model or the slickest demo. After spending time at a packed AI event in downtown Cleveland where 500 people chose between four different workshops, I walked away with a clear takeaway about what leaders want today and what they’ll desperately need tomorrow.

Right now, most attention goes to the technology. People gravitate toward sessions with “Gen AI” energy because it’s thrilling, tangible, and it feels like a shortcut to transformation. Meanwhile, human centered conversations about how teams actually partner with AI tend to get less love, even when the content is practical and grounded. I get it. The tech is impressive. But the moment companies try to scale beyond experimentation, the real friction shows up fast.

My prediction: within the next 12 months, that preference flips. Organizations are going to feel overwhelmed by AI implementation and start “starving for support” on the human side. How do you get teams to understand the tools, trust them, and use them well? How do you structure the organization for adoption, governance, and real value? That is the work that determines whether AI becomes a competitive advantage or an expensive curiosity.

If you’re navigating AI strategy, change management, or scaling AI across your business, this short episode is built to challenge your assumptions and sharpen your focus. Subscribe, share it with a leader who’s wrestling with AI adoption, and leave a review with your take: are we heading toward a human first AI era?

AI is moving so fast that even seasoned leaders are admitting something they rarely say out loud: this is hard to get your arms around. I’m recording from my car for this quick return, and I want to be candid about why the show went quiet for five months. The acceleration in AI tools, products, and company claims wasn’t just “a lot to track” it was genuinely unsettling, and I needed time to process what it means for real businesses making real bets.

What I keep hearing from CEOs and operators is the same double fear: nobody wants to get left behind, but nobody wants to make the wrong move forward. Add the nonstop stream of “new AI workflows” for accounting firms, customer service centers, and every other function, and you get confusion instead of clarity. So we talk about the mindset shift that matters most right now: getting comfortable saying, “I don’t know,” and using that honesty to ask better questions, test smarter, and lead teams through uncertainty.

Going forward, I’m committing to practical information over theory. You’ll hear real stories from conversations with companies that are implementing AI, debating AI adoption, and learning where it truly helps and where it doesn’t. Episodes may be short, and they’ll come more frequently only when they bring you clear value.

If you want grounded AI leadership insights without the hype, subscribe, share this with a colleague, and leave a quick review. What’s the one AI decision you’re wrestling with right now?

The room buzzed with possibility at the Great Lakes AI Conference, held on the beautiful campus of Bowling Green State University and that energy sparked a message leaders need right now: the fastest way to harness AI is to slow down, listen, and design it around your people. We, at AI23, call this shift the Potential Era—a move from rigid processes to adaptive systems where humans and AI partner to amplify judgment, creativity, and speed.

I share the story of AI23 that chose research and learning over rushing products, and why that discipline builds better instincts for real-world impact. We map a pragmatic path for executives and operators: clarify outcomes, observe how great work actually happens, co-design pilots with domain experts, and scale what sticks. Instead of jamming shiny tools into fragile processes, we focus on culture, shared literacy, and human-in-the-loop guardrails that protect quality and trust.

You’ll hear how leaders can signal courage and curiosity, how to avoid the trap of complexity theater, and where to start with narrow, high-friction workflows that benefit most from augmentation. We get practical about metrics—cycle time, error rates, employee sentiment, and customer value—and about building cross-functional squads that bring legal, data, and frontline operators together from day one. The result is a workplace where people do more of what only humans can do, while AI carries the repetitive load that kept their best ideas stuck.

If you’re a CEO, team lead, or builder wondering how to bring AI in without breaking what already works, this conversation offers a clear blueprint and a cultural north star. Subscribe, share with a colleague who’s wrestling with AI adoption, and leave a review with the one change you’ll make this quarter. What’s your first step into the Potential Era?