Two conversations that sounded identical
Two client conversations recently were almost word-for-word the same.
Both businesses are data-rich and expert-heavy. Both have spent real money on AI-related pilots over the past couple of years. Some machine-learning models, some GenAI proof-of-concepts, even early agentic workflows. And both said essentially:
“We’re not short on ideas or budget. We’re short on coherence. Nothing has reached the point where a business leader would change a resource-allocation decision because of it. How do we turn this into something deliberate, where each investment builds on the last and actually compounds?”
We’ve been part of these conversations for years, but the tone has shifted. Two years ago the question was “Should we do AI?”
Today it’s “We are doing AI, how do we stop wasting time and make it accretive?”
After those two calls I wrote down the pattern that keeps repeating in the (still small) number of companies that have actually moved from pilots to something executives trust and use every week. I’m sharing it here because I suspect many of you are having the exact same internal debate right now.
The pattern has five stages
| Stage | What it feels like day-to-day | What actually changes for the business |
|---|---|---|
| 1. Scattered experiments | Multiple teams running pilots, excitement mixed with healthy skepticism, no shared foundation | Occasional interesting finding, but nothing repeatable or defensible |
| 2. First trusted answer | One question is answered at a quality level a leader would defend to their most skeptical colleague | Political air-cover appears; budget, attention, and talent follow |
| 3. Connected capability | 3–5 high-value use cases share the same data backbone and governance model | Time-to-insight collapses; debates about “what the number really is” mostly end |
| 4. Always-on decision layer | Leaders and their teams query the system in natural language several times a day | Operating reviews, forecast calls, and business review prep prep become dramatically shorter and higher-conviction |
| 5. Proprietary advantage | Models continuously retrain on your unique historical data | Competitors using generic tools simply can’t match depth or speed |
Almost every company we speak with today is between Stage 1 and Stage 2.
The leap that unlocks everything else is delivering one single answer that is trusted enough to act on. Not ten answers, not a platform, not a roadmap. One.
How that leap actually happens
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- A private equity partner asks: “Which of our portfolio companies are quietly drifting off plan and why?” We pick the three companies that worry him most, connect four existing data sources (CRM, ERP extracts, board decks, monthly operating reports), and in nine weeks deliver a ranked list plus full explainability. The next resource-allocation discussion uses that list without a single caveat. Stage 2 achieved.
- A professional services firm asks: “Of the several thousand open opportunities in our CRM right now, which ones are actually likely to convert to paid projects in the next six months, and what drives the difference?” We use their CRM, project management system, calendars, and historical billing data. Eight weeks later the firm has a ranked list they immediately use to re-assign resources. Stage 2 achieved.
- A telecom operator asks: “Where is our highest-propensity new-logo growth actually hiding?” Same pattern: one question, narrow scope, decision-grade rigor, reusable foundation. They see 5.5× better conversion on the top segment within a single quarter.
In all three cases the technical stack is boring: mostly existing cloud data warehouse, a semantic layer, and well-understood algorithms. Maybe our Overwatch solution for faster, more trusted speed to market but doesn’t have to be. The difference is sequence and discipline.
The practical playbook we now use with every client who asks this question
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Start with the single question you would pay almost any amount to have answered with complete confidence in the next 60–90 days. Write it down. Not five questions. One.
Recent examples we’ve seen:
- “Which open opportunities should we prioritize for the next 90 days?”
- “What actually moved win rate/margin last quarter: mix, pricing, duration, or something else?”
- “Where is our highest-leverage growth hiding in the next 12–18 months?”
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Force the first project to become the seed for everything that follows. The data pipeline, entity definitions, governance rules, and semantic layer built for Question #1 are reused 100 % for Questions #2 through #10. Nothing gets rebuilt from scratch.
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Insist on decision-grade rigor from day one.
- Full audit trail
- Explicit assumptions
- Explainability that survives the harshest skeptic in the room If it doesn’t meet that bar, you haven’t moved the needle.
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Ship in weeks, not months. Narrow scope is the superpower. Completeness comes later.
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Once Stage 2 is achieved, Stage 3 is almost mechanical: add the next two or three questions on the exact same foundation. Suddenly the CFO, the head of sales, the business unit leaders, and the BD team are all looking at the same decomposition of performance. Conversations stop being about the data and start being about what to do next.
A quiet observation from the companies now in Stage 4
When leaders have an always-on decision layer they trust, something subtle but profound happens:
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- Business review prep that used to take weeks now takes hours
- Resource-allocation meetings that used to be political now feel obvious
- Experts spend more time on high-value work because the system tells them where to focus
I don’t know any investor, operating executive, or business leader who wouldn’t want a 90% reduction in time spent arguing about numbers. It doesn’t just give them time back, it allows them to focus on what matters.
If you’re having this conversation internally right now
The most useful thing you can do this week is pick the one question that matters most and ask:
“What would have to be true for the answer to be defensible in front of our leadership or our most skeptical partner?”
Everything else, tools, team, budget, flows from there.
We’re having more of these discussions every month. If you’re in the same spot, feel free to reach out. Happy to compare notes on the question you care about most.
No deck, no demo, just a short conversation about the one thing that would actually move the needle for you in 2026.
How Can We Help?
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