AI Opportunity Assessment — Discovery, then Build
WiscAI engages in two phases. A three-week, fixed-scope AI Opportunity Discovery produces a scored, two-lane opportunity map. A scoped Build engagement implements the highest-ROI opportunity. No open-ended retainers, no vague deliverables, no commitment past the phase you are in.
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Two lanes. One opportunity map.
Every AI opportunity falls into one of two lanes. Scoping both up front means leadership sees the full landscape — not just the lane they already know.
Internal and Operational
Workflows where staff spend time drafting, retrieving, summarizing, reconciling, or analyzing. The risk surface is internal. Human-in-the-loop is the default. These opportunities tend to move fastest because the stakes of a wrong answer are recoverable.
- Drafting memos, reports, and first-pass analysis
- Retrieving information from internal documents and systems
- Reconciling data across tools, files, and sources
- Staff training, onboarding, and knowledge transfer
- Internal dashboards, briefings, and reporting loops
Customer-Facing or Regulated
Workflows that touch members, customers, patients, athletes, or regulated records. Compliance posture must be explicit. Evaluation criteria match the regulator's expectation, not just the developer's. These opportunities require deliberate guardrails and a clear escalation path.
- Member, customer, or patient communication
- Underwriting, claims, fraud, and compliance review
- Regulated retrieval — BSA, AML, NCAA, ERISA, HIPAA contexts
- Voice and chat systems with explicit disclosure
- Any workflow where a wrong answer creates regulatory risk
Two phases. Fixed scope at each gate.
Discovery is a standalone deliverable. Build is scoped against the atlas Discovery produces. Most clients continue from one to the other, but neither phase assumes the next.
AI Opportunity Discovery
A focused, three-week engagement that produces a scored, two-lane opportunity atlas for your organization. Deliverables include the opportunity map, cost and impact projections for the top candidates, a first-phase build proposal, and a clear recommendation on where not to start. No commitment past Discovery itself.
AI Build Engagement
Targeted implementation of the highest-ROI opportunity identified in Discovery. The team that scoped the opportunity also ships it — no handoff, no re-briefing, no lost context. Build engagements are themselves fixed-scope and fixed-fee, sized to the specific workflow being automated.
What happens across the three weeks
Each week has a specific outcome. Leadership sees progress continuously, not just at the end.
Surface
Interviews with department leads. Review of existing systems and data access. First-pass workflow mapping across both lanes — internal/operational and customer-facing/regulated. No scoring yet; just a complete picture of candidate workflows.
Score and Prioritize
Every candidate workflow scored against six criteria. Two-lane classification applied. Short list assembled per lane. Preliminary cost and impact projections for the leading candidates. Check-in with leadership on trade-offs.
Atlas and Build Plan
Deliverables finalized. Two-lane opportunity atlas, scored. First-phase build proposal with fixed-scope pricing for the top opportunity. Recommendations on sequencing, where not to start, and what to leave for later.
Six criteria. Applied to every candidate.
The scoring framework is explicit. Leadership sees the reasoning, not just the recommendation.
Staff-Time Impact
How many hours per week does the current workflow consume? Which roles? Higher impact moves the candidate up the list — but only when paired with feasibility and measurability.
Data Readiness
Do the inputs the AI needs actually exist, and are they accessible? Missing or locked data does not disqualify a candidate, but it does change the sequencing.
Technical Feasibility
Can current AI models reliably do the work? What does the evaluation harness need to look like? Where does the system need to hand off to a human?
Risk and Compliance
What happens when the AI is wrong? Who is affected? What regulatory surface does the workflow touch? Lane 2 candidates carry this weight explicitly.
Change-Management Load
How disruptive is the rollout for the team? Which roles are affected? What training or process change is required? Low change load accelerates time-to-value.
Measurability
Can outcomes be tracked in a way the organization will actually use? A candidate that creates value but cannot be measured will be hard to defend at the next budget cycle.
Four recurring shapes of Build engagement
Most engagements fall into one of four patterns. Discovery identifies which shape fits; Build ships the system.
Document Extraction and Workflow Automation
Structured and unstructured documents processed at volume. Extraction, classification, routing, approval flows. Common in finance and accounting, operations, and back-office administrative work.
Domain-Knowledge Coaching and SME Augmentation
Expert knowledge captured as retrievable, promptable systems. Onboarding and training acceleration. Reduces dependency on a few senior staff and preserves institutional knowledge.
Member, Customer, or Athlete-Facing AI
Voice, chat, and guided flows that interact directly with the people your organization serves. Compliance posture scoped up front. Escalation to human staff built in, not bolted on.
Compliance-Aware Deployment
Regulated environments — credit union, insurance, ERISA advisory, NCAA, clinical. Evaluation harnesses that match the regulator's lens. Audit trail, disclosure, and escalation designed in from the first week.
Pillars that apply the two-lane frame
Each industry and function page uses the same two-lane scoping. Pick the closest match to your situation to see real use cases and engagement shapes.
Start with a 30-minute conversation.
We will tell you honestly whether Discovery is the right starting point — or whether your situation calls for something different.
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