Use-case portfolio

Recommend a program the organization can execute: which capabilities to deploy, which ideas to investigate, where to develop employee practice, and what to defer. Start with the business ambition and the resources available for the next commitment.

Shape the investments

Develop each serious opportunity enough to understand the changed work. Identify who gains a capability, what the AI does, how the work reaches an outcome, and why that outcome matters. Combine extraction, search, drafting, and routing when they are parts of one service. Preserve separate opportunities when they serve different decisions or customers.

Look beyond the submitted use-case list. Employee-created tools, work currently rationed by experts, recurring investigations, and new customer services may be better investments than speeding up an existing document. Use opportunity-design when the choices need more invention.

Compare investments at a similar level of development. Establish enough of each experience, architecture, and economic mechanism to judge its potential and the commitment required.

Assemble a coherent program

Consider how the investments reinforce one another:

• An integrated workflow delivers an outcome across the systems and teams that own the work.
• A reusable capability can make several workflows cheaper or better: identity resolution, task context, an action interface, evaluation cases, or a domain procedure.
• Employee practice can expand what teams do themselves and supply the next generation of workflow ideas. Fund time to use, adapt, and share useful approaches alongside access to tools.

Include what serves the ambition. Fund shared capability against named first consumers and the variation they need. Discover common behavior through those deployments; avoid paying for speculative universality. Count shared costs and overlapping benefits once.

Look for sequencing effects. One deployment may release the specialist capacity another needs. An employee tool may establish demand before a product build. Two services may compete for the same expert even when their engineering work is independent. Make these relationships part of the recommendation.

Choose the next commitments

Use the constraints that can change the choice: available budget, engineering time, source-system access, operating capacity, customer timing, and ability to absorb changed work. Distinguish a hard prerequisite from work that can proceed with a temporary interface or representative records.

Compare the benefits and uncertainties that distinguish the options. Use ranges and thresholds where useful; keep an unknown separate from a poor result. Explain what the proposed bundle gains and what the organization gives up by deferring the alternative.

Fund an experiment for the decision it can resolve. Fund a deployment for the useful capability it will operate. An ambitious uncertain idea can deserve the next experiment while another receives the production commitment. A broad enablement investment can earn its place through recurring useful work and the opportunities it produces, without assigning invented savings to every employee.

Read the allocation example for a program that combines a deployment, shared capability, employee practice, and a probe under finite capacity.

Make the sequence executable

Specify what starts, the dependency it consumes, the result that releases the next commitment, and who will run it. Preserve the central value mechanism in the first scope. Reserve capacity for integration findings, adoption, and operation.

Show the deferred alternative and the evidence that would move it forward. Revisit the portfolio when a probe, customer response, native product feature, or operating result changes the economics or sequence.

Deliver the investment comparison and sequence in the user's working format. A decision-maker should be able to see the proposed commitments, their combined resource demand, the useful capability each creates, and the choices still open.