Stop Counting AI Projects. Start Ranking Them.
The Deliberate AI Leader — A Series for Executives Who Want to Get This Right – Part 14
Summary:
We recently made the case that most companies don’t have an AI strategy — they have an AI portfolio, made up of every department’s individual initiatives, all competing for the same capital, talent, and attention. Once that portfolio is inventoried, there’s a second step most organizations skip entirely: ranking it.
Not by excitement. Not by executive sponsorship. Not by who built the flashiest demo. By economic return.
The Executive Question
If you had $250K available for transformation next year, would you rather fund 15 disconnected copilots, or 4 enterprise initiatives producing a 40%+ projected IRR?
Framed that way, the answer feels obvious. But it’s not the question most leadership teams are actually asking. Instead, budget tends to flow toward whichever department made the most persuasive case in the room that quarter — which has almost nothing to do with which initiative would generate the greatest return.
Why Ranking Is Harder Than It Sounds
Ranking requires comparing initiatives that don’t naturally sit next to each other — a customer-facing chatbot against a supply chain optimization model against an HR automation tool. Without a common framework, that comparison happens on gut feel, political capital, or whoever asks first. With one, it happens on the same criteria every time, regardless of who’s proposing the project.
The Stakeholder Problem Nobody Talks About
Ranking AI initiatives isn’t just an analytical exercise — it’s a political one. The moment you rank projects against each other, someone’s initiative moves down the list, and that someone usually has a seat in the room. This is where objective criteria earn their keep: a leadership team working from the five-dimension framework and a documented IRR estimate for every project can defend a ranking decision on the merits, rather than relitigating it as a personality conflict every budget cycle.
This is also why the ranking exercise works best as a standing process, not a one-time event. Portfolios shift. A project that ranked low six months ago might have matured past its riskiest assumptions. One that ranked high might be stalling on adoption. Revisiting the ranking quarterly keeps the portfolio honest.
What Changes Once You Rank Instead of Count
The moment leadership starts ranking AI initiatives by projected return rather than counting how many are underway, the conversation shifts. Projects that were coasting on sponsorship alone get real scrutiny. Strong initiatives that were underfunded because they came from a quieter team get the resources they deserve. And the organization starts building a genuine competency in capital allocation for AI — the same competency it already has for every other kind of investment.
It also changes how new project proposals get written. Once a team knows their initiative will be ranked against everything else in the portfolio using the same five dimensions and a documented IRR estimate, the business cases that show up get sharper, more honest, and less reliant on enthusiasm to carry the day.
Where This Series Goes Next
Ranking is easier with a visual model. In the next article, we walk through a simple 2×2 matrix — projected IRR against enterprise complexity — that lets a leadership team place every initiative in the portfolio at a glance and immediately see where the quick wins, the strategic bets, and the distractions actually sit.
Ready to rank your organization’s current AI initiatives? Book a Strategy Call and we’ll build the ranking with you.
About WHIM Innovation
WHIM Innovation helps organizations harness the practical power of AI, automation, and custom software to work smarter and scale faster. We combine deep technical expertise with real-world business insight to build tools that simplify operations, enhance decision-making, and unlock new capacity across teams. From AI strategy and workflow design to custom monday.com apps and fully integrated solutions, we partner closely with clients to create systems that are efficient, intuitive, and built for long-term success.