Friday, December 19, 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. Here’s what you need to know:
1. Sound Waves: Podcast Highlights
Our most recent episode features David Ebner, President and Founder of Content Workshop – a 14-year B2B content agency that’s produced over 30,000 assets for tech brands – and author of the Amazon bestseller Kingmakers, where we discuss something that’ll make CFOs everywhere take notice: his ‘20% rule’ for AI deployment that keeps quality high without gutting creativity. Plus: why his team is betting on custom AI agents over off-the-shelf tools. Hit one of the below links to check it 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. Three Ways to Actually Use AI (That Aren’t Just Fancy Googling)
Last week I threw some high-level strategic thoughts your way about Anthropic’s “soul overview” and what it means for your organization’s AI deployment. This week, I’m counterbalancing that piece with something more tactical.
Here’s the uncomfortable truth: most leaders who claim they’re “using AI” are really just tinkering around the edges, treating these tools like glorified search engines or, at best, a way to polish up their emails before hitting send.
That’s like buying a Ferrari to drive to the mailbox.
So let me ask you: what’s the wildest thing you imagine you could leverage AI to accomplish? If your answer involves “summarizing documents” or “drafting responses,” you’re thinking too small.
Here are three non-obvious ways to put AI to work right now.
Build a Shadow Executive Team
Most founders carry strategic weight alone. Pricing decisions, org design tradeoffs, succession planning, M&A curiosity. It all lives in your head.
AI can become a persistent, multi-persona team that pressure-tests your thinking before you bring it to your real team or board. Think of it as a skeptical CFO, a growth-hungry CMO, a risk-aware COO, and a future-focused board member, all available on demand without politics or agendas.
Create three to five persistent AI roles, feed each one your industry context and strategic priorities, then ask: “What would each of you push back on if this were on a board agenda?”
You get better decisions without the ego-driven positioning that slows real teams down.
Turn Tribal Knowledge Into a Living Operating System
Most mid-market companies run on oral tradition. “That’s just how we do it here.”
AI can convert scattered know-how (emails, SOPs, Slack threads, meeting notes) into a queryable company brain that new leaders and successors can actually use. This isn’t documentation. It’s decision memory.
Start with one domain: sales handoffs, customer escalation, or hiring decisions. Upload past decisions and the reasoning behind them. Let leaders ask: “How do we usually handle this, and why?”
The biggest constraint to scale isn’t capital. It’s knowledge concentration.
Use AI as a Signal Detector
Most leaders misuse AI to go faster. The real opportunity? Using AI to notice what you’re currently missing.
AI can scan customer feedback, sales calls, support tickets, and market news to surface weak signals before they become problems, or opportunities your competitors catch first.
Pick one signal stream. Run a recurring analysis asking: “What is changing slowly but consistently that leadership isn’t discussing yet?” Review monthly at the exec level.
Fewer “we should’ve seen that coming” moments. Better strategic timing.
The Meta-Lesson
The highest-value use of AI in mid-market organizations isn’t automation. It’s better judgment, better memory, and better foresight. AI doesn’t replace leadership. It amplifies the quality of it.
If you’re ready to move beyond fancy Googling, drop me a line. Let’s figure out which of these approaches fits your world.
3. Research Roundup: What the Data Tells Us
AGI and Your Workforce: A Framework for What Gets Automated First
Yale economist Pascual Restrepo just gave us something valuable: a framework for predicting which jobs AGI will target first. Spoiler: it’s not about skill level. It’s about whether the work is essential for growth.
The numbers that matter: Global computing power has grown a million-fold since 1980, and we’re nowhere near the ceiling. The research projects these constraints easing within 5-10 years as infrastructure expands… at which point human brainpower becomes a rounding error.
What this means for your Monday morning: The research divides work into two buckets: “bottleneck” tasks that must expand for your company to grow (logistics, financial analysis, operational decisions) and “supplementary” work that adds value but isn’t growth-limiting (customer support, hospitality functions). Here’s the counterintuitive part: bottleneck work gets automated first because it’s where the economic pressure is highest.
The catch: This isn’t a prediction about next quarter. It’s a planning framework for the next decade. The transition could be gradual or sudden depending on whether compute availability or algorithmic breakthroughs drive adoption in your industry.
Action item: Map your organization’s functions into bottleneck versus supplementary categories. The bottleneck column is your automation priority list, whether you’re building capabilities or defending against competitors who do.
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
OpenAI launches GPT-5.2 amid competitive pressure from Google and Anthropic. The “code red” at OpenAI is actually good news for buyers. Competitive heat from Gemini 3 and Claude is accelerating improvements. More useful: OpenAI claims average Enterprise users save 40-60 minutes daily. That’s a testable benchmark for your pilot programs. If you’re not measuring time savings that specifically, you’re not evaluating these tools properly.
Anthropic testing new Agentic Tasks Mode for Claude. This matters because it signals how AI assistants are evolving from Q&A chatbots to workflow delegation tools. Research with source preferences, analysis with validation controls, output format options. If you’re still thinking of these as “fancy search engines,” you’re underestimating where this category is heading. Worth revisiting your use case assumptions.
5. Elevate Your Leadership with AI for the C Suite
Ready to move beyond “fancy Googling”?
If you read those three use cases and thought “we should be doing that,” let’s talk. I help middle-market executives build AI capabilities that actually change how they lead, not just how they search.
Reply to this email to schedule 30 minutes to discuss which approach fits your organization.
Until next week, Chad
P.S. Know another executive who’s still treating AI like a smarter search bar? Forward this their way.