Map how work actually gets done in a business area and locate the friction AI could realistically relieve.

Screen candidate AI ideas on value, feasibility, data, and risk, and rule out the ones that will stall.

Rank competing ideas by value against effort in a way you can defend to the people affected.

Assemble a ranked shortlist into a balanced set of AI projects, showing who gains and who absorbs the extra work.

Map how work actually gets done in a business area and locate the friction AI could realistically relieve.

Screen candidate AI ideas on value, feasibility, data, and risk, and rule out the ones that will stall.

Rank competing ideas by value against effort in a way you can defend to the people affected.

Assemble a ranked shortlist into a balanced set of AI projects, showing who gains and who absorbs the extra work.

Build a phased AI roadmap with milestones, dependencies, and clear conditions for moving to the next stage.

Sequence AI spending across the near, middle, and longer term so early wins pay for riskier bets.

Identify where AI assistants and agents change how work is done, and who is allowed to build them.

Critique a draft roadmap for feasibility and value, and improve it, including by cutting what will not survive.

Structure an AI business case that separates hard return, soft return, and strategic option value by the evidence behind each.

Build an advisory-depth ROI model that prices hidden costs such as downstream rework, quality decline, and vendor risk.

Define baselines, value metrics, and two-year targets, pairing each efficiency gain with a quality check that could expose it.

Assemble a decision-ready business case that can honestly recommend approval, delay, or stopping.

Apply AI governance frameworks, such as NIST AI RMF, ISO/IEC 42001, and the EU AI Act, so responsibility is designed in from the start.

Identify and mitigate model, data, regulatory, third-party, and agentic AI risks in a governance and risk plan.

Test whether a human-review control can be performed at the volume a reviewer faces, then redesign or reject it.

Communicate AI strategy to executives, including how to deliver an unwelcome finding early, plainly, and actionably.

Apply the program's frameworks to complete an opportunity assessment, prioritized portfolio, and readiness summary for a realistic manufacturer.

Build a roadmap, ROI business case, and governance plan that recommend against ideas the evidence does not support.

Integrate separate advisory components into one consistent package and an executive presentation built around a single recommendation.

Document your reasoning so the package stands alone as a portfolio piece, hardest finding included.