What an Idea Scorecard run actually returns

This is a complete sample run for someone whose deliverables are being absorbed by AI. The person below is fabricated for illustration and the output is not a customer result.

The job of this output is not to argue that a decision is needed, because anyone in this position already knows that. The job is to put two credible directions next to each other and make the rejection of one of them defensible in writing.

The situation

Senior instructional designer inside an enterprise software company

Nineteen years building onboarding curricula, certification tracks, and enablement content for a global sales organization. Over the last eighteen months the storyboarding and first draft work has moved to internal AI tooling, and headcount in the team has gone from eleven to six.

The two directions compared

Option A: AI enablement consulting for L and D teams

Recommended

Sell a fixed scope engagement that helps internal learning teams decide what to automate, what to keep human, and how to prove the difference to their executive sponsor. The work sits directly on top of nineteen years of building the exact deliverables now being absorbed, which means the credibility is already there before the first call.

The buyer is a director who is being told to cut cost without losing quality and has no internal person who has done both sides of that trade. That is a budget line that already exists, so the sale does not depend on creating a new category.

Option B: Self paced course teaching instructional design with AI

Rejected

This is the option almost everyone in this position reaches for first, because it looks like leverage and it uses skills already in hand. It is rejected here for a specific reason rather than a general one, and that reason is written down so it does not get quietly relitigated in three months.

The buyer for a course is the same displaced practitioner, not the company holding the budget. That audience is shrinking, price sensitive, and buying it would be buying a slower version of the problem they are already living in.

Why the obvious option was rejected

This is the hardest part of the output and the part most people skip when they think it through alone. A rejected option that is not written down comes back every time the recommended path gets difficult.

The buyer is the wrong side of the displacement

A course sells to the person losing the role, while the consulting engagement sells to the organization causing the change. Only one of those two has a budget that grows as AI adoption accelerates.

Time to first revenue is roughly five times longer

The consulting path can be sold from a conversation and a one page scope, while the course needs a finished curriculum, a platform, and an audience before the first dollar arrives. Nine months of unpaid build is the actual cost of the obvious option.

The proof does not transfer

Enterprise experience is the strongest asset here and it is worth the most when sold into enterprise. Packaged as a course it becomes a credential line rather than the product itself, which discards most of its value.

The first three moves

Write the engagement as a single page with a fixed scope, a fixed price, and a named outcome, then send it to four former colleagues who now sit on the buying side.
Run eight conversations with L and D directors about what they are being asked to cut this year, and record the exact phrases they use rather than paraphrasing them.
Publish two short teardowns of real training assets that AI handles badly, since the fastest credibility signal here is showing where the automation actually breaks.

None of these require leaving the current role. The sequence is built so the evidence arrives before the income decision does.

Your own run uses your role, your track record, and the specific way your work is being absorbed. The comparison and the rejection reasoning come back at the same level of detail shown above.

Score your own idea

See also the Offer Architect sample output.