AI For the C Suite® with Chad Harvey

What do you believe?
Two conversations keep arising when AI is discussed. The first focuses on the people building AI who are confident the next 36 months will reshape knowledge work. The second is typified by sharp, well-read clients who believe that it's simply a better search engine and the rest is hype.
Chad's view is that the distance between those two positions is a signal, and he calls it the belief gap. In this episode he argues it sits upstream of the three gaps he has tracked before. These are the gap between what the technology can do and how fast organizations change, the gap between bleeding edge companies and conservative ones in the same industry, and the gap inside a single company between the few who have rebuilt their work around AI and the many who haven't. If you don't believe something is coming, you don't adopt it, and your organization never has to change.
Both camps are partly right. Builders have the stronger record on what the technology will do next, but they underestimate how slowly budgets, incentives, habits, and trust move. Your Tuesday experience tells you what's in your building today, not what's coming. Leslie Nielsen makes a cameo along the way.
For middle market leaders, that tension is an opening. A Fortune 500 company has to clear procurement and legal review before anyone touches a tool. You can put one in someone's hands next week. Chad closes with a three-step, 90-day move. Name one knowledge-work process and one capable person, measure the before and after in hours, errors, and cycle time, then decide from the evidence which side of the gap you're on. The cost is a couple thousand dollars and one person's attention.
You'll leave with a clearer way to separate what the technology can do from how fast your company can absorb it, and a starting point you can run this quarter. One question to carry in: when did you last change your mind about what AI can do?
AI For the C Suite™ podcast keeps C-Suite leaders informed and engaged in the world of AI for business. If you're a CEO, President, Owner, or C-suite leader looking to understand how AI will impact your organization, you've found the right podcast. 
https://aiforthecsuite.com/#chadharvey #aiforthecsuite #aic

Who owns AI in your organization—and what does ownership actually involve?
Chad Harvey welcomes Matt Symes, CEO of Symplicity Designs, to AI for the C-Suite to explore the leadership, workforce, and financial questions behind AI adoption.
Matt runs a portfolio of nine companies across Atlantic Canada. In the AI transformations he leads, AI reports to HR rather than IT. His argument: when you redesign a workflow around people and machines, you change the skills, responsibilities, and team structure needed to create value.
The conversation examines what happens when organizations distribute tools without redesigning work—and why middle managers often absorb the pressure.
Listen for:
• Shadow AI, “slop grenades,” and the squeeze on middle management• Why documenting a bottleneck is a practical first step• Using AI to develop systems thinking• The shift from salary costs to salaries plus AI spend• Measuring financial returns rather than assuming productivity equals profit• Agent sprawl and the need for governance• Why workforce development belongs in your AI strategy• Scenarios, deliberate practice, and AI-assisted coaching• Matt’s recurring research and meeting-preparation workflows• Privacy, security, and the questions boards should ask• Being more intentional with the time and capacity AI can help create
Learn more about Matt’s company, Symplicity:https://www.symplicity.ca/
Watch the full conversation on YouTube:https://youtu.be/NIE1ia505rs
Follow AI for the C-Suite wherever you listen to podcasts.

McKinsey's 2026 State of AI survey found that 80% of respondents say AI has improved their personal productivity. Thirty-seven percent of their companies can see it in operating profit. Six percent qualify as what McKinsey calls high performers. Same survey, same companies, same year. That gap is not a data error. It is the central question facing every operator who has been trying to figure out how fast to move.
In this episode, Chad breaks down the debate between the acceleration camp and the friction camp using three concepts you can actually apply: the Curve, the Break, and the Snap. The Curve explains why four compounding forces  (capability, price, distribution, and capital) are doing something without historical precedent. The Break explains why organizations, laws, budgets, and human beings are not keeping pace, and why the macro data is not yet screaming industrial revolution. The Snap is the discontinuity that neither camp accounts for... the point at which competitive economics, not average adoption rates, becomes the mechanism that drives diffusion through your industry.
For middle market companies, this framework clarifies how to position. You are not waiting for certainty about which camp wins. You are behaving as though friction buys you time while preparing as though that time could disappear quickly. Chad closes with three concrete moves: reframe the question from task-level AI use to workflow-level structural change, pick one complete workflow to rebuild rather than automating individual steps, and start watching your own backfill decisions as a leading indicator of which camp is actually winning inside your building.
AI is the defining challenge and opportunity of our generation. AI for the C-Suite™ is a continuous learning and application experience that exists to unite, elevate, and equip leaders to navigate the Exponential Age. Join the AI for the C Suite community today: https://aiforthecsuite.com/ #chadharvey #aiforthecsuite #aic

When should a company use artificial intelligence, and when is traditional automation the better answer?
Chad Harvey speaks with Bhaskar Jayakrishnan, Senior Vice President of Engineering for Customer Experience at Cisco, about the practical realities of deploying AI at enterprise scale.
Bhaskar explains why organizations should begin with the problem rather than the technology, how token consumption can create enormous operating costs, and why AI and automation should work together instead of competing with one another.
They also discuss small language models, semantic routing, production readiness, enterprise data, cybersecurity, AI agents, and why the fundamentals of good software engineering remain essential.
Connect with Bhaskar Jayakrishnan:https://www.linkedin.com/in/bhaskarjayakrishnan
Read Bhaskar’s Cisco articles:https://blogs.cisco.com/author/bjayakri
Watch the full video:https://youtu.be/a-mXNwTTl5E
Learn more about AI for the C Suite:https://aiforthecsuite.com

Click here for the expanded article titled Claude vs ChatGPT Memory Decoded: Neither One Is a Record. It contains additional information and is a companion piece to this episode. 
Both Claude and ChatGPT shipped major memory upgrades over the summer of 2026, and neither company explained them particularly well. The result is a wave of reasonable but incorrect assumptions, including the belief that unified memory might finally mean you can stop keeping your own records. It does not.
In this episode, Chad unpacks what unified memory actually means across both platforms, the four boundaries where each system stops short, and the critical difference in how they fail. Claude files facts you can read and edit, but loses its work when it opens the wrong drawer. ChatGPT writes an evolving impression of you built from chat history, your email inbox, and connected apps, and retires what used to be true to reflect what is true now. One is a filing cabinet. The other is a colleague's daily-updated impression of you. Neither is a record.
Chad maps the four governance edges every mid-market executive should walk through with whoever holds the admin login: project walls and their opposite defaults on each platform, the fact that deleting a chat does not delete what the tool learned, what actually feeds each system's memory, and who can erase months of accumulated context for your entire team with a single click. At a 50-500 person company, you do not have an enterprise governance team to catch these gaps before someone finds that button.
The episode closes with four actions, none of which take more than an hour, that establish a clear division between what memory is designed to hold and what belongs in your organization's actual records system.
AI for the C-Suite™ is a continuous learning and application experience that exists to unite, elevate, and equip leaders to navigate the Exponential Age. Join the AI for the C Suite community today: https://aiforthecsuite.com/#chadharvey #aiforthecsuite #aic

Zoher Karu spent 25 years running data and analytics at eBay, Citi, and Blue Shield of California — and he says the hardest part of AI has never been the technology. In this episode, Zohar breaks down why most AI pilots fail, why "just point AI at it" is a fallacy, the concept of model drift, why 90% of the world's data is private and untapped, and how leaders can start making smarter decisions at scale instead of chasing shiny objects.
Zoher also shares real examples from his work at Taelor, a men's styling company using AI to scale human expertise — and explains why mid-market companies may actually have an advantage in this next wave of AI adoption.
Watch until the end for his take on why AI initiatives so often stall in the middle of an organization, even when leadership is fully bought in.
Full episode: https://youtu.be/GB8dvDd8D5c
Connect with Zoher Karu: https://www.linkedin.com/in/zzkaru/
 

When the CEO of one of the world's leading AI labs publishes an essay arguing his own industry needs to slow down, most coverage treats it as a headline about Washington and San Francisco. It is not. It is a signal with direct implications for how you are pacing your own organization.
Chad breaks down what Dario Amodei actually argued in "We Must Pace the Frontier" including the recursive self-improvement concern, a documented incident involving a rogue agent swarm that attacked third parties and attempted to manipulate its own performance grading, and Amodei's three-step proposal modeled on how banking regulators operate. More importantly, Chad translates the argument into a framework for the mid-market leader: Accelerate. Pace. Audit.
The case for accelerating is grounded in the capability gap. The models available today, accessible at the cost of a streaming subscription, already match or outperform domain experts on more than 70% of tasks across 44 occupations, per OpenAI's own GDP Valve benchmark. Nobody is pacing that capability. It's sitting in a browser tab. If Amodei's proposal narrows the gap between what has shipped and what organizations have absorbed, the competitive question stops being who has the best model and starts being who actually deployed the model everyone has.
The case for pacing is narrow and specific: autonomy, not adoption. The agents arriving in your building this year are not coming from a frontier lab. They are bundled inside your CRM, your accounting system, and your email suite. They hold credentials nobody on your team fully mapped, and you are likely hearing about their performance from the same person who signed the contract. The embedded evaluator principle, one independent person with real access and the standing to report something unfavorable in writing, is the governance structure that closes that gap. Your finance function already has its equivalent in the form of an outside auditor. Almost no middle-market organization has it for AI.
This episode gives you three questions to bring to your next leadership meeting, a clear framework for deciding where your foot belongs on the accelerator, and a straight read on what "wait and see" actually costs when the capability has already shipped.
Article / Essay Links
Things Are About to Get Weird(er), Chad Harvey
We Must Pace the Frontier, Dario Amodei
AI For the C Suite™ podcast keeps C-Suite leaders informed and engaged in the world of AI for business. If you're a CEO, President, Owner, or C-suite leader looking to understand how AI will impact your organization, you've found the right podcast.
Join the AI for the C Suite community today: https://aiforthecsuite.com/
#chadharvey #aiforthecsuite #aic

AI transformation does not usually fail because of the technology. It fails because organizations overlook the people, processes, and leadership required to make it work.
Ross Barnes joins Chad Harvey to discuss why artificial intelligence affects every corner of an organization, how shadow AI creates hidden risks, and why companies must raise the floor before attempting to raise the roof.
Ross explains why curiosity and speed are becoming competitive advantages, how automation can unintentionally make human work more difficult, and why judgment becomes more valuable as memorization becomes less important.
He also introduces ikigAI and its 4H Diagnostic: Here, Heart, Hunger, and Hunch. These are the distinctly human qualities organizations should strengthen as AI assumes more routine work.
Learn more about Ross and Galahad:https://galahadgroup.co.uk
Explore AI for the C Suite:https://aiforthecsuite.com
Watch the full episode:https://youtu.be/1PXR59n3BzM

Most AI conversations in your organization are running on an assumption... that everyone in the room shares a working definition of the words being used. They don't. And the people least likely to say so are your most senior leaders.
This episode goes back to the foundation. Chad breaks down 15 essential AI terms across three categories: what the technology is, how it gets built, and what you as a leader actually have control over. The organizing structure is deliberate because most of the confusion in a vendor meeting or internal AI review traces back to two people pulling words from different categories without realizing it.
The first layer covers the field itself: AI, machine learning, deep learning, LLM, and why terms like AGI and ASI deserve serious skepticism when they appear in a sales deck. The second layer covers how these systems are made (data, training, model, and inference) and why the cost structure of AI in a middle market organization sits almost entirely in that last word. The third layer covers what you actually touch: prompt, context, knowledge base, and why a well-built context is your primary defense against a confident wrong answer.
Chad closes with three specific moves: a cultural reset for your next AI meeting, a two-week budget diagnostic on your inference spend, and a workflow audit that starts with context before it points at models or vendors.
These 15 terms are not going to be replaced by whatever 2027 decides to call itself. Learn them once, and you're done.
AI for the C Suite® keeps C-Suite leaders informed and engaged in the world of AI for business. If you're a CEO, President, Owner, or C-suite leader looking to understand how AI will impact your organization, you've found the right podcast.
Join the AI for the C Suite® community today: https://aiforthecsuite.com/ #chadharvey #aiforthecsuite #aic

Dan Fernandez has spent his career standing between engineers building hard tech and executives deciding whether to trust it. In this episode, he joins Chad Harvey to unpack what mid-market leaders consistently get wrong about AI adoption—unpredictable costs, data privacy risks, vendor lock-in, and the real security implications of giving AI agents too much autonomy.
 
🎧 Watch the full episode here: https://youtu.be/tKXFhWXnoAQ