It’s not the tech bro. It’s the lack of strategy. The fix requires a shift from shiny tools to growth levers you can actually pull.
A few weeks ago, I joined a Google Meet with a frustrated potential client.
Camera on. Shoulders slumped. Tabs everywhere.
They had copilots, dashboards and chatbots running in every corner of their org. The spend was real. But his opener cut through the noise:
“We’ve spent millions on AI, and nothing’s moving the needle.”
Busy team. Flat ROI. Same revenue curve.
And here’s the hard truth: I hear this weekly in DMs and calls. Different industry, same story. AI without strategy is noise.
The Prospect Problem: Activity Without Outcomes
- Dashboard fatigue → More screens, not more clarity.
- Shiny-object churn → Last quarter’s pilot is already gathering dust.
- Pilot purgatory → Teams are “experimenting” endlessly, but nothing crosses into impact.
What they needed wasn’t one more tool. They needed a map. One that reveals where revenue leaks, which workflows matter and how AI should actually be wired into the business engine.
The Industry-Wide “Gen AI Paradox”
Turns out, this is bigger than any one company.
McKinsey’s latest CEO playbook defines the issue bluntly: nearly 8 in 10 companies report using gen AI, yet just as many report no material impact on earnings.
They call it the Gen AI paradox.
Horizontal tools (like copilots and chatbots) have scaled the fastest. They’re easy to switch on, but deliver diffuse, hard-to-measure gains.
Vertical use cases (embedded in core processes like underwriting, claims, or supply chain) are far more transformative. But 90% remain stuck in pilot mode.
Translation: orgs are scaling tools, not outcomes.
Adoption (78%) ████████████████████
No ROI (~80%) █████████████████████
Most companies deploy gen-AI, but most also see no earnings impact. It’s the Gen-AI paradox.
Why Your AI Pilots Stall
Horizontal copilots are plug-and-play. That’s their appeal. But the value spreads too thin to show up on the P&L.
Meanwhile, the high-value stuff, the workflows tied to revenue or cost get trapped by:
- Fragmented initiatives
- Siloed AI teams
- Data quality gaps
- Risk fears
- Legacy workflows never reimagined for AI
It’s like building extra lanes on a highway without fixing the bottleneck at the toll booth. Traffic still piles up, and drivers don’t get where they need to go faster.
That’s how quarters slip away while competitors quietly widen the gap.
The Strategic Shift: From Chatbots to Agents
McKinsey’s research points to the way forward: AI agents.
Agents aren’t just reactive copilots. They can:
- Plan across multi-step workflows
- Act autonomously
- Adapt to real-time feedback
- Integrate with systems end-to-end
Think of them less as “chat assistants” and more as virtual coworkers.
Proof points:
- A global bank cut modernization timelines by ~50% using hybrid squads of engineering agents.
- A financial institution restructured credit-memo workflows, gaining 20–60% productivity improvements.
- Multi-agent systems unlocked millions in savings by cleaning and interpreting messy data.
But here’s the catch: you can’t bolt agents onto legacy steps. The big gains only come when you redesign processes around them.
┌─────────────────────────┬────────────────────────────┐
│ Horizontal (Copilots) │ Vertical (Core Workflows) │
├─────────────────────────┼────────────────────────────┤
│ + Easy to turn on │ + Direct revenue/cost KPI │
│ - Thin, diffuse gains │ - 90% stuck in pilots │
│ - Hard to see in P&L │ + Highest enterprise value │
└─────────────────────────┴────────────────────────────┘What Leaders Must Do Now
McKinsey lays out the CEO playbook:
- Prioritize vertical domains tied to KPIs. Not experiments, revenue or cost levers.
- Shut down low-impact pilots. Free up resources for “lighthouse” workflows.
- Redesign around agents. Parallelize, automate, and embed human-in-the-loop only where it matters.
- Stand up an agentic AI mesh. Govern agents across teams to prevent sprawl, ensure security and scale responsibly.
This isn’t a toggle in IT. It’s a CEO-level pivot.
From Insight to Action
On that Google Meet, the question wasn’t: “Do we need strategy?”
It was: “Which levers first?”
That’s why I built the AI Marketing Audit + Growth Lever Map. It’s a diagnostic that functions like a growth MRI.
Here’s what you walk away with:
- Bottleneck Diagnosis → where funnels leak, ads burn cash, or content fizzles.
- Growth Lever Mapping → Quick Wins (0–30d), Mid-Term (30–90d), Long-Term (90–365d).
- 90-Day Priority Roadmap → clarity on what to fix now vs. later.
- My Strategic Note → your biggest missed opportunity, revealed.
Find your hidden growth levers. Stop guessing, start scaling.
The Stakes
Markets are moving exponentially. Most orgs are still moving linearly.
The winners won’t be the ones who piled on copilots. They’ll be the ones who rewire workflows with agents, and prove it in the P&L.
Because AI without strategy is just noise. With strategy, it becomes your exponential edge.
Norm Bond
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