Friday, March 20, 2026
FRIDAY — AI FOR THE C SUITE
Read time: 10-11 min · Read online
Hi, it’s Chad. Every Friday, I serve as your AI guide to help you navigate a rapidly evolving landscape, discern signals from noise and transform cutting-edge insights into practical leadership wisdom. Here’s what you need to know:
1. Sound Waves: Podcast Highlights
This past Monday my most recent solo episode dropped, and this one’s practical. I sat in a room full of mid-market CTOs recently (more on that below), and what I kept hearing was a gap between what leadership expects from IT and what IT has the resources to deliver. So in this episode I break down specific recommendations for how to equip your IT department for growth instead of continually reacting: how to structure the conversation with your CTO, where to find capacity without blowing up headcount, and why the evaluate-for-three-months, pilot-for-six, deploy-in-nine playbook is now a liability. Tune in.
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2. Algorithmic Musings: Your CTO Was Built for a War That’s Already Over
I sat in a room with a group of mid-market CTOs recently. Smart people. Experienced. Capable of building and maintaining the technology infrastructure that keeps their companies running. And every single one of them is drowning.
Not because they lack talent or ambition. Because they’ve spent their entire careers being rewarded for exactly the wrong thing.
“Keeping costs low has been beat into me my whole career,” one of them told me. He runs IT for a mid-market company with hundreds of employees and multiple locations. “We run a really tight ship. But now we have all this other stuff that’s supposed to be done, and we don’t have the resources to do it.”
That sentence should give every mid-market CEO and business owner significant pause. Because that tension (the one between “run lean” and “transform everything”) is about to become a defining strategic challenge of your organization. And if you don’t address it, you’re going to lose your technology leaders, fall behind competitors who moved faster, or both.
The Signals Are Converging
If you’ve been paying attention over the last 60 days, you’ve noticed something shift. Three significant pieces dropped within a week of each other in February. The first two I covered in my February 20th newsletter: Matt Shumer’s viral blog post “Something Big Is Happening” (now viewed over 80 million times), in which the AI startup founder wrote an open letter to his non-tech friends and family about how wide the gap has become between what AI insiders see and what the public understands; and Josh Tyrangiel’s Atlantic cover story, “America Isn’t Ready for What AI Will Do to Jobs,” which examines how AI is already reshaping the labor market for entry-level knowledge workers.
The third piece arrived days later: Citrini Research published what amounted to an economic postmortem written from the perspective of 2028. That one will keep you up at night if you let it.
These aren’t fringe voices. A prominent D.C. think tank is spinning up a bipartisan commission (Republicans, Democrats, multiple policy organizations) to map out scenarios and contingencies for AI’s impact on the workforce this year. Not 2030. Not “someday.” Q2, Q3, Q4 of 2026. Their working range for job attrition in knowledge-work sectors sits between 30 and 40 percent. Anthropic just launched a new economic research institute and staffed it with heavyweights from Yale Law, Google DeepMind, and academic economics. Companies don’t invest in high-salary policy thinkers unless they have a pretty good idea of what’s coming down the pipe.
And what’s coming is an acceleration curve that makes the last three years look like a warm-up lap. The jump from Claude 4.5 to 4.6 wasn’t incremental. I ran identical prompts on identical client projects, swapping only the model. The difference in output quality was staggering. Both Anthropic and OpenAI are now publicly stating that they ship production code written entirely by AI, with zero human editing. If that’s what they’re admitting today, imagine where internal development sits.
The Hourglass Is Coming for the Middle
A research paper making the rounds right now describes something called “the headless firm.” Think of your organization’s structure as an hourglass: a strategic executive layer at the top, an execution layer at the bottom (composed of individual contributors and AI agents doing the work), and a radically compressed middle.
That middle is where most of your middle management, your middle-income knowledge workers, and a significant chunk of your institutional memory currently reside. It’s the translation layer between strategy and execution. And if the headless firm model plays out (and the leading indicators suggest it will, at least in part), you’re going to need technology, data infrastructure, and AI-powered workflows to fill that gap. You can’t replace human interpretation with Power BI dashboards alone.
Which brings us back to the person you’ve charged with making all of this happen.
The Budget Trap
Your CTO (or VP of IT, or Director of Technology, whatever the title) was hired into a system that measured success by cost containment. Every performance review, every budget cycle, every strategic conversation reinforced the same message: keep the lights on, keep costs down, don’t break anything. For decades, that was the right answer.
It isn’t anymore.
I’m embedded with mid-market companies right now, and what I’m seeing across the board is the same pattern. AI initiatives get dumped onto IT. IT doesn’t have the capacity. Leadership grows frustrated that things aren’t moving fast enough. Meanwhile, the CTO is sitting in a room thinking, “You trained me to run a tight ship, you gave me a skeleton crew, and now you want me to also transform the entire business?”
I’ve now heard variations of the same story from multiple CTOs: leadership brings in an outside consultant to evaluate the IT organization’s future. If you’ve seen Office Space, you know the scene where the Bobs roll in with their clipboards and start asking people “What would you say you do here?” Same energy, except nobody’s laughing. In a few of these cases, the CTO leaned in and made the consultant an ally. But the fact that they weren’t part of the original conversation tells you everything about how many organizations view their technology leadership right now.
And what these assessments keep revealing is a massive investment gap. I’m working with mid-market companies whose IT spend sits at single-digit percentages of revenue in a world where industry benchmarks now suggest the number should be several multiples of that. You can’t bridge that gap by telling someone to “be more nimble.”
What Actually Needs to Happen
If you’re a mid-market leader reading this, I want you to think about three things.
First, speed is now a competitive advantage, and it has a shelf life. I watched a commercial construction company implement an AI-powered estimating solution that fundamentally changed their throughput. They’re cranking right now. But that advantage only lasts until their competitors do the same thing. If you’re not moving, you’re falling behind. And if a private equity firm figures this out in your industry segment before you do, they’ll roll up your competitors, drive prices down, and squeeze you out. Speed isn’t a “nice to have” right now. It’s survival.
Second, you need process mappers more than you need programmers. One of the most consistent recommendations I make to companies right now is this: hire (or develop) people who can sit with a department for 90 minutes, identify the friction points in an eight-step workflow, and say, “Step 3.5 and Step 7. We can save you five hours a week if we automate right there.” They don’t need to know how to build the solution. They need to be able to see the problem. That skill (process mapping combined with facilitation) is the bridge between “we know AI can do something” and “we’ve actually changed how we work.”
Third, free your CTO from the budget trap or hire the person who can run alongside them. Your technology leader cannot simultaneously maintain all existing infrastructure, drive AI transformation, develop governance policies, evaluate every shiny object the C-suite brings home from conferences, and do it all with the same headcount and the same shoestring technology budget. Something has to give. Either invest in dedicated AI capacity (an internal champion, a small team, an external partner), or explicitly reprioritize what your IT organization is responsible for. Telling them to “figure it out” while cutting their legs out from under them isn’t a strategy. It’s a slow-motion failure.
The Year Things Get Real
I’ve been reluctant to make sweeping pronouncements about timelines. But I’ll say this: we are sitting at the end of Q1 2026, and the convergence of what I’m hearing from Washington policy circles, from Silicon Valley, from the thought leaders I respect, and from the mid-market leaders I sit with every month tells me this is the year the mid-market wakes up. Enterprise has been investing for two to three years. The productive gains from those investments are starting to show. The economic impact (both positive and negative) is becoming visible. And the political implications of displacing an educated, connected, lever-pulling workforce are going to surface in ways we haven’t seen before.
Your CTO knows all of this. They read the same articles, attend the same conferences, and lose sleep over the same scenarios. The question is whether you’re going to keep them chained to a budget philosophy that was built for a world that no longer exists, or whether you’re going to give them the resources and the organizational permission to help you navigate what’s coming.
I know which option I’d choose.
If you’re wrestling with how to structure your AI strategy, align your technology leadership, or just figure out where to start, drop me a line at chad@chadharvey.com. I’m always up for a conversation about how to stop managing to the budget and start managing toward what’s next.
3. Research Roundup: What the Data Tells Us
AI Coaching Works… with a Catch
Your company spends five figures per head on executive coaching. Yet a new randomized trial just showed an AI chatbot produced comparable goal-progress gains in two weeks at near-zero marginal cost. But the real finding isn’t about cost savings. It’s about what actually made it work.
The numbers that matter: 517 working adults were randomly assigned to AI coaching, a structured written exercise, or no support. The AI group showed significantly more goal progress at two weeks, right in line with meta-analytic benchmarks for professional coaching. The written exercise? No significant effect. Same reflective content, different delivery, totally different outcome.
What this means for your Monday morning: The mechanism wasn’t better goal quality or deeper self-reflection. It was accountability. The chatbot’s conversational follow-ups made people feel answerable to it, and that feeling drove the entire effect. Static tools covering the same ground didn’t move the needle.
The catch: That accountability faded significantly by the two-week mark. A single AI session won’t sustain behavior change. You need ongoing check-ins built into the design.
Action item: When evaluating AI coaching or development platforms, stop asking about content libraries. Instead, start asking how the tool creates ongoing accountability loops: follow-up prompts, scheduled check-ins, progress tracking. That’s the feature that actually produces results.
Read the paper · Read our full analysis of this and all other analyzed research papers at AI for the C Suite.
4. Radar Hits: What’s Worth Your Attention
The NYT talked to 70+ developers about how AI is changing their jobs. The headline numbers: at startups, AI now generates close to 100% of the code, with humans serving as architects and reviewers. At Google, the gains are real but more measured, around a 10% increase in engineering velocity across 100,000+ engineers. That gap matters. If you’re greenlighting a new software build, the math on team size and timelines has fundamentally changed. If you’re maintaining legacy systems, the gains are real but slower. Either way, your next dev hiring plan should reflect a world where teams of 30 are becoming teams of six.
Anthropic interviewed 81,000 Claude users across 159 countries. This was the largest qualitative AI study ever conducted, and the finding that should get your attention: entrepreneurs and independent workers consistently described the most transformative economic impact from AI, using it to build businesses, compete above their weight class, and perform at levels previously out of reach. Meanwhile, employees inside larger organizations reported more modest gains. That’s a signal your org structure might be the bottleneck, not the technology. If your people aren’t seeing productivity gains, the problem is likely workflow design and adoption strategy, not the tools themselves.
5. Elevate Your Leadership with AI for the C Suite
This week’s newsletter was long. (I’m aware.) But if the CTO conversation hit close to home, that’s probably because you’re living some version of it right now. My Q2 calendar is filled, and a good chunk of it is exactly this kind of work: helping mid-market leadership teams figure out how to restructure their technology investment, align their CTO with the AI opportunity, and stop running a 2019 IT budget in a 2026 world. If that’s a conversation worth having, reach out at chad@chadharvey.com and let’s talk about what we can do for you in Q3.
And if you know another executive who needs to read this one, forward it. That’s still the best way this newsletter grows.
Stay safe. Stay healthy. Be strong. Lead well.
Chad