FORMWEFTMany scenarios but unclear priorities
Place business impact, feasibility, and risk in a single evaluation framework.
AI STRATEGY
AI Strategy Consulting: Find the right scenario first, then select the model.
Through business interviews, process and data inventory, and value and risk assessment, identify priority enterprise AI scenarios.
Three situations suitable for AI scenario assessment first
Before investing in models and system development, validate business value, data conditions, and governance boundaries.
Existing pilots but hard to prove value
Establish observable success metrics and distinguish demo effects from production value.
Sensitive data boundaries unclear
First confirm permissions, audit trails, human review, and acceptable risk.
AI Strategy Consulting deliverables
Output scenario priorities, value and risk assessments, a first-phase roadmap, success metrics, and governance boundaries.
Business goal and process interviews
Data and system condition inventory
Scenario value and risk assessment
First-phase roadmap and success metrics
An assessment is not just a checklist; it forms actionable decisions
Prepare key processes, business owners, representative inputs and outputs, and existing metrics when starting. Use evidence to select the first investment.
Implementation work
Interview key roles, sample business processes, and record task frequency, duration, errors, and dependencies. Rank scenarios by value, data availability, technical feasibility, and risk.
Acceptance evidence
Deliver problem definitions, current-state baselines, required data and interfaces, owners, pilot scope, and success and stop conditions for each priority scenario, so the client can decide on the next phase.
Clear boundaries
The diagnostic phase does not by default include production development, full data governance cleanup, or fixed revenue commitments. If data or permissions are insufficient, list them as prerequisites rather than filling gaps with assumptions.
Common AI diagnostic questions
Do I need to choose a model first?
No. Start by defining the business task and acceptance criteria, then compare models, tools, or whether AI is needed at all.
What if the data isn't organized yet?
First, evaluate available sources and responsible parties. Data preparation can be part of the first-phase scope, but it should be separated from the work and acceptance of AI application development.
Must development continue after the assessment?
Not necessarily. The assessment should support decisions to continue, adjust, or stop, and can also be used by the client's internal team or other implementation parties within an agreed scope.
Submit project background
Describe the goals, current state, and expected timeline, and we will organize the next steps accordingly.