AI Won’t Save Your Transformation — But This Will
AI won’t save your transformation — but alignment will.
When I listened to Jason Furman’s interview with Ross Douthat — warning about an AI-driven economic bubble — I heard more than a market concern. I heard the same pattern I’ve seen inside enterprises for years: massive investment, thin proof, and a widening gap between motion and value. The same anxiety that grips investors now lives in every boardroom — extraordinary promise, uneven performance.
Furman’s point was blunt: productivity hasn’t caught up with the hype. Capital is flowing into capability, not yet into return. Inside companies, McKinsey’s June 2025 study found the same dynamic — nearly 80% of enterprises now use generative AI, but few report measurable earnings impact (Seizing the Agentic AI Advantage, McKinsey 2025).
I’ve seen this movie before. Every major technology wave follows the same rhythm — exuberance, disillusionment, alignment, adoption. Transformations don’t fail because of the tech — they fail when speed outruns alignment. That’s the point we’ve reached with AI: activity has replaced architecture.
Economists call it the valley of death — the period when investment rises and productivity dips. I’ve stood in that valley. Teams look busy, metrics look green, and yet value stalls. The energy is real, but it’s scattered. In one large-scale enterprise rollout, we built an engine meant to unify and simplify processes. On paper, it was a breakthrough. In practice, no one agreed on what success meant. The issue wasn’t the algorithm — it was the absence of shared definition and ownership. We hadn’t aligned on belief before we built for scale.
That’s the real productivity story — whether in markets or organizations. Technology scales what already exists. If the system is fragmented, AI amplifies the noise. If the system is aligned, it accelerates value creation. That truth has held since the first automation program I led — the best code in the world can’t overcome unclear accountability.
McKinsey calls this the “alignment dividend” — the measurable gain when operating models are redesigned for AI before deployment. Companies that realign decision rights and accountability early see productivity improvements up to 20% faster than peers. It’s not the AI itself — it’s the structural readiness that determines return.
Alignment is also the bridge between transformation and renewal. In SaaS, renewal proves belief — the customer chooses again because value is still visible. In transformation, alignment is the same test. When AI systems come up for review, boards will ask the same questions they ask at renewal: What’s the measurable value? Who owns it? Is it compounding or decaying? Be ready to answer before the question is asked.
When I see teams sprinting ahead of alignment, these are the four things I check first:
- Outcomes mapped to owners who already report them monthly.
- Two “first-value” workflows that prove impact within one business cycle.
- Weekly decision loops where AI insights replace slide decks — not add to them.
- Governance wired into operations, not layered above it.
It’s simple but ruthless: if these aren’t in place, automation just multiplies uncertainty.
The latest McKinsey playbooks point to the same conclusion — the advantage isn’t in the model; it’s in the alignment. The winners I’ve seen are the ones who build accountability first — and intelligence second.
Get alignment right first, adoption next, acceleration last — because technology only amplifies what’s already true.
Next insight: The optimism trap — how tone, pressure, and narrative drift erode credibility long before results do.