To prioritize artificial intelligence use cases, score each initiative across five dimensions: business impact, speed to return, technical feasibility, risk and compliance, and strategic differentiation. Classify the result as A, B or C. Fund category A initiatives, validate category B through controlled pilots, and incubate, redesign or stop category C. The score is a decision aid, not an automatic answer: weights and estimates must reflect data maturity, execution capacity, financial priorities and risk tolerance.
The method answers two different questions at once: which initiatives can generate value quickly, and which can create a capability that is difficult to copy. The useful output is not a permanent ranking. It is a portfolio with explicit investment choices, testable assumptions and criteria for advancing, scaling or stopping each initiative.
Score five dimensions and record confidence
- Business impact: expected effect on revenue, margin, cost, productivity, risk or customer experience.
- Speed to return: time until observable economic or operational value, not time until a prototype.
- Technical feasibility: data, integrations, architecture, security and available skills.
- Risk and compliance: regulatory, reputational, operational, contractual and security exposure.
- Strategic differentiation: contribution to proprietary data, products, capabilities or experiences that competitors cannot easily reproduce.
Give every dimension a score from zero to ten, a short rationale and a confidence level. Equal scores can hide very different realities: one initiative may be supported by operational evidence while another depends on assumptions that have not been tested. A simple weighted formula can convert the dimensions into a score from zero to 100, but the committee should keep the assumptions, likely range and confidence visible. A score of 82 based on fragile assumptions is not necessarily stronger than 76 supported by reliable data.
Turn scores into A, B and C decisions
- Category A — fund and prepare implementation: high relative value, sufficient feasibility and manageable risk.
- Category B — run a guarded pilot: relevant potential, but technical, economic, adoption or regulatory uncertainty remains.
- Category C — incubate, redesign or stop: low relative value, excessive dependencies or risk that does not fit the current moment.
A starting threshold is A at 75 or above, B from 50 to 74 and C below 50. These cutoffs are not universal benchmarks. Recalibrate them when the score distribution, budget or risk tolerance produces an unrealistic portfolio. Category A still requires validation and a named owner. Category C may be a good idea whose required data, integration or operational capability does not yet exist.
Estimate return and effort without false precision
When historical data is limited, use ranges, proxies and short tests rather than waiting for certainty or inventing a precise ROI. Decompose value into observable units such as transaction volume, time per task, rework, conversion, avoided loss or released capacity. Separate gross benefit from capturable value because saved hours do not automatically become lower cost or higher revenue. Estimate total effort across integration, cloud, licenses, evaluation, security, support, training, maintenance and governance rather than looking only at model complexity.
- Define conservative, likely and favorable benefit ranges.
- Record total cost and the critical dependencies that can delay value.
- Assign confidence to impact, timing, cost and risk estimates.
- Convert the largest uncertainty into a testable pilot hypothesis.
- Set the value KPI, risk limit and go or no-go rule before the pilot begins.
Balance quick wins and strategic advantage
Classify expected value capture into three horizons: up to six months for a quick win, six to 18 months for medium-term initiatives and more than 18 months for strategic bets. Quick wins commonly appear in repetitive processes with accessible data, human review and few critical integrations. Strategic initiatives take longer when they involve intelligent products, proprietary data, core-process redesign or cumulative learning effects. Sequence the portfolio so short-term work improves data, reusable components or team capability needed by the strategic bets.
Choose between internal automation and intelligent customer products
This is not a binary choice. Internal automation can offer a shorter path to efficiency when the process is stable and measurable. Intelligent products can improve revenue, retention or differentiation, but face greater adoption uncertainty and reputational exposure. Favor automation that creates reusable capacity, data or skills, while reserving space for customer-facing initiatives that can build defensible assets through proprietary data, deep workflow integration, network effects or hard-to-copy operational knowledge.
Use governance and stage gates to protect the portfolio
- Give every initiative a business owner and a technical owner.
- Use a primary KPI that represents realized value, not only model accuracy or usage.
- Define go or no-go criteria before the pilot.
- Set human review, risk limits and an incident response plan.
- Monitor production systems for quality, cost, traceability and rollback.
- Release funding in four-to-eight-week stages to limit sunk cost.
An executive AI committee can review the portfolio monthly with business, technology, data, product, security, legal or compliance and operations. Its job is to allocate resources, remove dependencies and stop initiatives that fail to confirm their assumptions. Warning signals include unusable data, integration cost that exceeds likely benefit, low adoption, unmanageable risk or no credible path to capture the efficiency created.
Move from ranking to a 12-month roadmap
- Consolidate up to 12 initiatives in a standard inventory.
- Run a cross-functional workshop with business, technology, data, product and risk.
- Score initiatives and document assumptions, confidence and dependencies.
- Select the critical uncertainties for diagnostics or controlled pilots.
- Build a 12-month roadmap with owners, stage gates and funding decisions.
- Review the portfolio quarterly and update scores with realized value.
The MAKINAI framework turns prioritization into an operating discipline. A short portfolio assessment can combine the workshop, scoring, dependency diagnosis and roadmap, then develop initial business cases for the highest-priority initiatives. The first conversation should confirm scope, access to evidence and decision criteria before implementation begins.