Paid diagnostic
What the consulting engagement produces.
The first engagement is deliberately narrow. It is built to answer: where is AI already costing money, which use cases deserve action, and what should be shipped first?
AI current-state review
Inventory active AI tools, teams, workflows, vendors, model access points, and known pain points. The output is a plain-language map of what exists today and who owns it.
Spend and accountability analysis
Identify fragmented subscriptions, duplicated tools, untracked model usage, and teams without budget visibility. The goal is a CFO-readable control view.
Use-case prioritization
Rank AI opportunities by value, owner, feasibility, data readiness, implementation effort, and risk of becoming another demo with no operational owner.
Operating model recommendations
Define the approval flow, ownership model, vendor posture, internal roles, and governance rhythm needed to make AI adoption repeatable.
Executive decision memo
Deliver a board-ready memo summarizing findings, recommended first pilot, budget range, expected value, dependencies, and the decision needed from leadership.
Pilot candidate shortlist
Leave with one primary pilot and two backup options, each with scope, acceptance criteria, rough cost, stakeholders, and a path to measurable value.
Listen and map
Leadership interviews, tool and spend review, workflow walkthroughs, and identification of the highest-friction AI adoption points.
Prioritize and decide
Opportunity scoring, operating model recommendations, pilot framing, budget logic, and executive readout.
Move to architecture
If the case is strong, NEXTGEN turns the diagnostic into an architecture and pilot SOW. If not, the memo explains what to stop.
Best fit
Leadership teams with real AI activity but weak control.
This is for organizations already spending time or money on AI and needing clarity before the next budget cycle, vendor decision, or executive review.