Most AI strategies in regulated industries fail for the same reason: they are use-case lists, not decisions. A Virtova AI strategy engagement is built to produce decisions. Which three to five use cases to fund. Which to retire. Which to defer. What the governance program has to look like for any of them to make it to production.
Engagements are led personally by Sultan Meghji, whose tenure as inaugural Chief Innovation Officer of the U.S. FDIC covered AI across the U.S. banking system. The work is calibrated to the sector’s actual rulebook rather than generic “AI best practice”: interagency model-risk guidance and fair-lending expectations for banks, HIPAA and FDA considerations for healthcare and life sciences, FedRAMP and sector-specific controls for federal contractors.
What this engagement looks like
A Virtova AI strategy engagement typically runs six to ten weeks and produces four artifacts.
A triaged use-case portfolio. Each candidate use case is scored on value, feasibility, and regulatory fit. The output is a short prioritized list (in our experience, five or fewer use cases worth real investment for the coming twelve months) plus an equally explicit list of use cases to retire or defer and why.
An AI operating model. Who decides, who builds, who audits, and who turns a model off. Most clients do not have this written down in a way that would survive examiner scrutiny; the engagement fixes that.
A governance plan mapped to the actual rulebook. For U.S. firms, that means NIST AI RMF alignment, interagency model-risk-management expectations, and the relevant sectoral guidance. For firms with European exposure, it means a written EU AI Act readiness posture. For both, it means a documented risk appetite statement with specific sentences (not “we will use AI responsibly”) and a running governance cadence.
A phased implementation plan. Twelve to eighteen months of sequenced work, with decision gates, delivery milestones, and the named owner for each item. No thirty-page waterfalls; a single page a CEO can absorb and a board can track against.
Sectors the practice covers
- U.S. banking: global, regional, and mid-size institutions.
- Insurance: claims, underwriting, fraud, customer operations.
- Healthcare and life sciences: clinical decision support, operations, and life-sciences R&D at the boundary with FDA expectations.
- Private-equity portfolio companies across financial services, healthcare, and industrial technology.
- Federal agencies and federally regulated firms, where FedRAMP, agency-specific guidance, and the evolving federal AI executive orders set the floor.
When the engagement is the wrong answer
AI strategy is the wrong engagement when the organization already has a prioritized portfolio and a functional governance program, and is stuck on execution. In that case the gap is program management or specific delivery support, not another strategy document. Virtova will say so in the discovery call rather than scope a project that is the wrong shape.
Next step
Most engagements start with a 30-minute discovery call. Bring what you have; we will tell you where the holes are and what the right next engagement looks like.