Most organizations do not have a full-time Chief AI Officer yet. Many will never need one at the scale the title implies. What they need, often for twelve to eighteen months, is a senior executive who can stand up an AI program, run it through its first audit, and hand it off to a permanent successor. That is what a fractional Chief AI Officer does.
At Virtova, fractional CAIO engagements are led personally by Sultan Meghji, the former inaugural Chief Innovation Officer of the U.S. FDIC, where he built the agency’s first innovation division from scratch and stood up policy work covering AI, quantum, digital assets, digital identity, and cybersecurity for the U.S. banking system. Sultan is also the Co-Founder and CEO of Frontier Foundry, a secured-AI platform company serving financial services, life sciences, and federal law enforcement. Both sides of that career show up inside the engagement: the regulator’s posture on one hand, and the operator’s experience turning models off in production on the other.
What this engagement looks like
A Virtova fractional CAIO engagement is structured around five threads that run in parallel from day one.
Operating model. The first three weeks are usually spent making concrete who decides, who builds, who audits, and who turns a model off. In most firms this is ambiguous on day one. It needs to stop being ambiguous before anything else.
Governance. Charter, cadence, risk appetite, tier classification, model inventory, typically aligned to the NIST AI Risk Management Framework for U.S. firms or the EU AI Act for firms with European exposure. For banks, the interagency model-risk-management guidance is the anchor: SR 26-2 (April 17, 2026) for in-scope traditional and non-generative AI models, plus the parallel governance discipline the agencies tell firms to stand up for the generative and agentic systems SR 26-2 explicitly leaves out of scope. What we leave behind is an operating program, not a binder.
Portfolio. Almost every engagement begins with too many pilots and not enough production. A good first pass typically retires roughly a third of the portfolio inside the first two months and focuses the rest toward measurable outcomes.
Board and examiner work. Carrying water to the board and, in banking, to examiners is a standing part of the job. The CAIO translates model behavior into risk language, sits with non-technical directors through what they are signing off on, and drafts the AI section of the board risk report. In examination-driven industries, this also means writing the AI narrative that supervisors see.
Succession. If the engagement does not end in a named permanent hire, it did not work. Months nine through twelve are typically the recruiting window, and Virtova runs the hiring process alongside the client.
Who this is for
The engagement fits four kinds of organizations especially well:
- U.S. regional and mid-size banks preparing for interagency examinations that increasingly ask how AI is governed.
- Insurers and health systems putting generative AI into claims, underwriting, or clinical workflows for the first time, with no governance baseline.
- Private-equity portfolio companies where the sponsor has identified AI value creation but the portco has no AI leadership.
- Federal agencies and federally regulated firms adapting to the accelerating pace of U.S. AI and digital-asset regulation.
When the role is the wrong answer
Fractional CAIO is a leadership role, not a delivery role. If the real problem is “we already have governance and a roadmap, but three pilots are stuck in procurement,” the gap is program management, not another executive. We will say so on the discovery call.
It is also not a permanent arrangement. Twelve to eighteen months with a documented handoff is the shape. Anything past that, in our experience, usually means the hiring process has stalled, which is its own problem and its own conversation.
Why a generalist regulated-industry operator, not an AI specialist
A wave of boutiques now markets “fractional CAIO as a service” led by AI specialists from AI-native firms. That profile is real, and for an AI-native company it is often the right pick. Inside a bank, an insurer, a hospital, or a federal agency, the hard part of AI is rarely the model itself. It is the forty years of consent orders, audit findings, and institutional decisions the model has to respect, the regulator on the line, and the board that needs one page they can defend. A generalist regulated-industry operator who has already run those rooms, in our experience, outperforms a pure AI specialist for that mandate.
A note on regulatory context
The federal AI governance picture for U.S. financial services has moved meaningfully in the last twelve months. The interagency model-risk-management guidance has been superseded for the first time since 2011: SR 26-2 (April 17, 2026) replaces SR 11-7 and SR 21-8, preserves the framework, and — importantly — explicitly excludes generative and agentic AI from formal scope while still telling banks to use the principles to govern those systems. The GENIUS Act and CLARITY Act have reshaped the digital-asset stack. The SEC’s consolidated audit trail has become a live AI-risk surface in the April 2026 Bloomberg coverage of the Mythos vulnerability Sultan was quoted on. A Virtova fractional CAIO engagement is calibrated to the rulebook that is actually landing, not the one that looked stable in 2024.
Next step
Most engagements start with a 30-minute discovery call. Bring what you know; we will tell you honestly whether fractional CAIO is the right shape of help, or whether it is something else.