Friday, December 26, 2025
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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. This is our final Friday AI newsletter of 2025 so we’re keeping it tight. Here’s what you need to know:
1. Sound Waves: Podcast Highlights
On Monday, 12.29.25, I’m joined by Drew Falkman for my final podcast of 2025. Drew is a product strategist who’s led strategy for HP, Adobe, and Geico, and whose LinkedIn Learning courses have reached over 100,000 professionals. We’ll discuss how one person with vibe coding tools can now do the work of a four-to-five person dev team, getting functional prototypes with databases and authentication built in about a month. The executive takeaway: the ROI calculus on build-vs-buy is shifting faster than most org charts can keep up. Or, for a shorter listen, tune into my final solo episode “What 2025 Actually Taught Us About AI Leadership.” Check them both out:
Subscribe for free today on your listening platform of choice to ensure you never miss a beat. New episodes release every two weeks.
2. Algorithmic Musings. Why CEOs Need to Understand the Difference Between General and Universal Intelligence
Machines are getting “smarter.” You’ve heard this a hundred times. What you haven’t heard: there are two completely different kinds of smart, and confusing them leads to expensive mistakes. What matters isn’t whether AI is becoming more intelligent. It’s what kind of intelligence we’re actually talking about.
Two terms worth knowing:
General intelligence is the ability to perform well across a wide range of tasks and domains, adapting knowledge from one context to another. Universal intelligence is the theoretical ability to achieve goals across all possible environments, regardless of context, values, or constraints.
AI is rapidly improving in the first. It’s nowhere near the second. And frankly, it doesn’t need to be.
Why This Distinction Matters
Most of the hype and fear around AI assumes an inevitable slide from general to universal intelligence. Think HAL 9000 quietly locking the pod bay doors. That makes for gripping cinema, but it leads to poor leadership decisions.
A generally intelligent system can analyze, summarize, predict, generate, and recommend across many domains. What it cannot do is understand meaning, responsibility, legitimacy, or moral consequence in the way human institutions require.
When leaders blur this line, three things tend to happen:
- Authority drifts to the machine. AI moves from “advisor” to “decider.” Judgment gets outsourced. Accountability gets fuzzy. Who made that call? The algorithm? The person who approved the algorithm? Good luck sorting that out when something goes sideways.
- Risk is misunderstood. The real danger isn’t sentient machines. It’s confident systems making plausible-sounding recommendations that quietly erode trust, culture, or ethics.
- Organizations get designed incorrectly. Leaders flatten decision structures assuming AI can replace human sense-making. It can’t. And the damage doesn’t show up on dashboards until it’s too late.
What This Means for Mid-Market CEOs
AI will soon be capable enough to touch nearly every function in your organization. That’s valuable, but only if you architect it correctly.
Think of AI as a competence multiplier. Not a governance authority.
Let AI analyze, draft, model, and recommend. Keep humans responsible for judgment, exceptions, values, and narrative. Preserve clear decision ownership, especially in hiring, firing, pricing, ethics, and strategy.
AI can optimize decisions. Only humans can legitimize them.
There’s a reason we don’t let calculators sign contracts.
The Bottom Line
General intelligence scales efficiency. Universal intelligence would imply authority. AI is delivering the first. Leadership must retain the second.
The CEOs who win in the next decade won’t be the ones who delegate the most to AI. They’ll be the ones who understand exactly where delegation must stop.
Wrestling with where to draw those lines in your organization? I’ve helped three clients build decision frameworks for exactly this in Q4. Let’s talk.
3. Research Roundup
No Research Roundup this week.
4. Radar Hits: What’s Worth Your Attention
AI users save one full workday per week, LSE finds. New research from a survey of nearly 3,000 workers puts hard numbers on AI productivity: 7.5 hours saved weekly, worth roughly £14,000 per employee per year. The hidden opportunity? 68% of employees have received zero AI training in the past year. Trained workers are twice as productive with AI as untrained ones, and age has nothing to do with it. Your move: Audit your AI training investment this quarter. The 68% of employees with zero training represent your fastest path to productivity gains.
Wharton’s 2025 AI Adoption Report shows Gen AI hitting enterprise scale. Year three of this benchmark study reveals 82% of enterprise leaders now use Gen AI weekly (up from 37% in 2023), and 72% are formally measuring ROI. Three in four report positive returns. Yet here’s the gap worth noting: 88% plan budget increases while capability building lags behind ambition. Translation: if you’re competing for AI-skilled talent or building internal training programs, you’re not early anymore. Your move: If you haven’t formalized AI ROI measurement yet, you’re competing with 72% of enterprises who have. Q1 priority: establish baseline metrics.
5. Elevate Your Leadership with AI for the C Suite
As we close out 2025: Thank you for reading, engaging, and occasionally hitting reply to argue with me. (I love those emails.) If the Friday AI has earned a spot in your inbox this year, would you forward this edition to one colleague who’s wrestling with AI strategy? That’s how this thing grows.
And if 2026 is the year you’re getting serious about AI governance and adoption, let’s have a conversation in January. I’ve got three client slots opening up in Q2.
Here’s to a sharp, strategic new year.
Chad