Discover how to evaluate AI initiatives to reduce churn by focusing on amplification, acceleration, and automation for measurable business impact.
Three Levers to Stop Churn -
Most chemicals and materials executives I talk to already have AI initiatives running. Pilots, working groups, use-case inventories. Something is in motion. What I rarely see is clarity on where that motion is headed — and in the current market, that distinction matters more than it ever has.
The trough is grinding. Although, temporarily improved, overcapacity will persist. Demand has not snapped back the way people expected. Capital allocation decisions are getting harder, not easier. In that environment, exploratory AI is a luxury. Not because AI doesn't work — it does, and the evidence is mounting — but because unfocused investment in a down cycle is exactly what gets cut when the budget conversation gets uncomfortable.
The executives who will come out of this period ahead are not the ones who waited. They're the ones who got focused.
A Simple Filter Most Organizations Aren't Using
There's a straightforward way to evaluate any AI initiative: does it pull one of three levers?
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Amplification — AI enriches what a human brings to their work, producing a qualitatively better output. A sales rep preparing for a discovery call uses AI to surface the customer's application shifts in their end markets, and competitive moves the customer hasn't mentioned directly — the deck they walk in with starts from a place most reps never reach. A procurement team using AI to prepare negotiation scenarios they wouldn't have had time to build manually.
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Acceleration — AI compresses the time between input and output on workflows that already exist. A customer quality complaint that previously routed through three teams over two weeks now has a root-cause analysis ready in hours. A repricing request that would have required days of assembling margin data, competitive benchmarks, and account history now surfaces in an afternoon.
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Automation — AI executes tasks with minimal human involvement. Marketing copy that once spent weeks cycling through legal and brand voice reviews is produced, compliant and on-brand, in hours. Maintenance work orders generated and scheduled from sensor data without a technician triaging the alert.
If an initiative doesn't pull at least one of these levers with a clear, quantifiable impact — it's not an investment. It's a budget line that won't survive scrutiny.
This isn't a judgment on ambition. It's a discipline for protecting the initiatives that are actually working from being lumped in with the ones that aren't.
Actioning the Insight
The exercise is straightforward. Take your current AI portfolio — every pilot, every working group, every initiative someone calls "strategic" — and put each one through the filter.
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Which lever does it pull?
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What is the measurable impact?
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How quickly does that impact show up on the P&L?
What you'll likely find: a few initiatives that pass cleanly, several that are promising but not yet tied to a value case, and some that can't answer the question at all.
The ones that pass — double down. The ones that are promising — sharpen the value case or stop. The ones that can't answer the question — stop now.
The trough is not a reason to pull back on AI. The trough is a reason to stop confusing activity with progress. The organizations that come out of this ahead will be the ones that used the constraint to get focused — not the ones that waited for the constraint to lift.
Clarity is a competitive advantage. In this environment, it might be the only one you can actually control.
Until next week,
Kendall -
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