Chief Risk Officer — Applied-AI Portfolio

The mandate

A deliberate change of pace is required to deal with a reset of enterprise risk ownership and board assurance within a multinational-owned enterprise artificial-intelligence products company. The immediate arena is the applied-AI portfolio during a commercialisation inflection. For mandate 170, the successful executive inherits decisions that have been deferred, competing stakeholder expectations and a need to establish facts before committing further capital.

The Chief Risk Officer operating perimeter covers approximately ₹1,050 crore in AI product and services revenue, with activity spanning several applied-AI portfolio customer, product and delivery clusters rather than a single asset. The Chief Risk Officer Artificial Intelligence remit carries direct influence over roughly 240 colleagues and third-party capacity.

The chair, executive committee and principal capital sponsors want a Chief Risk Officer who can convert ambiguity into a short list of explicit choices for the applied-AI portfolio. The Chief Risk Officer Artificial Intelligence seat must resolve a commercialisation inflection, while preserving the underlying strengths of the applied-AI portfolio. For mandate 170, value will come through sharper allocation, stronger leaders and an operating cadence that exposes variance early.

The Chief Risk Officer’s first year on the applied-AI portfolio is expected to end with early-warning quality, control effectiveness and regulator-ready evidence. In mandate 170, authority covers resources and leadership appointments; material trade-offs go directly to the board sponsor.

Why this seat is open

This is an urgent replacement for the Chief Risk Officer — Applied-AI Portfolio seat following an accelerated leadership transition. Interim accountability is in place for the applied-ai portfolio, but the board wants a permanent appointment within 6–8 weeks because a commercialisation inflection cannot remain under split ownership. The predecessor’s outcome is being handled neutrally and professionally. The external search remains confidential until the preferred candidate and transition plan are agreed.

What you will own

• Set the Chief Risk Officer value-creation thesis for the applied-AI portfolio, translate it into no more than five enterprise priorities and stop work that does not support them.
• Carry stewardship of approximately ₹1,050 crore in AI product and services revenue, including allocation, risk acceptance and board forecasts.
• Lead the Chief Risk Officer Artificial Intelligence organisation of about 240 employees and partners, appointing a team with clear decision rights and credible succession for every critical seat.
• Resolve the applied-AI portfolio economics and execution constraints created by a commercialisation inflection, with Chief Risk Officer-approved owners, dated milestones and transparent escalation thresholds.
• Establish one Chief Risk Officer operating review across commercial, customer, financial, people, technology and risk outcomes for the applied-AI portfolio; remove reconciliations that obscure accountability.
• Have held independent challenge authority and closed material issues with evidence accepted by board or supervisory review in mandate 170.
• Build the Chief Risk Officer’s three-year succession and capability plan for the applied-AI portfolio, reducing dependence on individual executives and improving mobility across the wider Artificial Intelligence organisation.

The first 12 months

• Days 1–90: Validate the applied-AI portfolio baseline, meet the 30 stakeholders most consequential to a reset of enterprise risk ownership and board assurance, assess the leadership team, stabilise immediate delivery risks and agree a board-owned scorecard with explicit decision gates.
• Months 4–9: Make the principal Chief Risk Officer portfolio and organisation choices for the applied-AI portfolio, install the new operating cadence, fill critical leadership gaps and deliver the first measurable release of cash, capacity or customer value.
• Months 10–12: Demonstrate a repeatable applied-AI portfolio trend against early-warning quality, control effectiveness and regulator-ready evidence, lock the following year’s capital and talent plan, evidence control sustainability and present a credible three-year value case with downside actions.

What the board will measure

• Delivery of the Chief Risk Officer’s agreed first-year applied-AI portfolio value case within a 10% tolerance, with variance explained before rather than after the relevant quarter closes.
• A Chief Risk Officer forecast that remains decision-useful across three consecutive quarters and reconciles the applied-AI portfolio’s operating, cash, customer and people assumptions.
• Closure of the Chief Risk Officer mandate’s highest-priority applied-AI portfolio risk and execution issues by their board-approved dates, with independent evidence that fixes are sustained.
• Retention of at least 90% of critical applied-AI portfolio talent and ready-now successors for at least 70% of the Chief Risk Officer’s direct reports.
• A quantified Chief Risk Officer-owned improvement in the applied-AI portfolio operating constraint behind a commercialisation inflection, supported by a clean baseline and named data owner.
• Clear stakeholder confidence in mandate 170: no unresolved high-severity escalation older than 30 days and no material surprise withheld from its agreed governance forum.

The person

You are currently a CRO, Deputy CRO or Chief Compliance and Risk Officer in a multinational-owned Artificial Intelligence or adjacent enterprise. In relation to the applied-AI portfolio, your Chief Risk Officer track record includes a transition where the original plan was no longer sufficient; you can explain your choices, evidence and numerical impact. Candidates from AI, enterprise software, data infrastructure, cloud, analytics or applied research will be considered where the operating model, customer stakes and governance intensity match this Chief Risk Officer brief.

As a Chief Risk Officer candidate, you bring 22–28 years of progressive Artificial Intelligence or adjacent-sector experience, consistent with the 22-28 experience band. At minimum, you have carried a P&L, book, budget or accountable portfolio of ₹850 crore and led an organisation of at least 240 people.

For mandate 170, the board wants two transitions: a difficult applied-AI portfolio portfolio choice and a leadership-system change during a commercialisation inflection. As the prospective Chief Risk Officer for this applied-AI portfolio, you must challenge optimistic cases and still create followership. References for mandate 170 must distinguish your contribution from the institution around you.

The Chief Risk Officer role in Artificial Intelligence is based in Mumbai; relocation is expected, although a structured weekly commute may be considered during the first quarter.

Non-negotiables

• Current or recent accountability at the level of CRO, Deputy CRO or Chief Compliance and Risk Officer, with direct exposure to a board, investment committee or equivalent Artificial Intelligence governance forum.
• Proven Chief Risk Officer ownership of at least ₹850 crore and leadership of no fewer than 240 employees in a comparable applied-AI portfolio context.
• One completed Artificial Intelligence or adjacent-sector example of a reset of enterprise risk ownership and board assurance with outcomes sustained for at least two reporting periods after the initial intervention.
• Sector credibility from AI, enterprise software, data infrastructure, cloud, analytics or applied research; experience that is purely functional and lacks Chief Risk Officer-level applied-AI portfolio consequences will not meet the bar.
• Willingness to meet the Mumbai location expectation, complete conflicts and background diligence, and protect the confidentiality of mandate 170.

Compensation and terms

The anticipated Chief Risk Officer package is ₹2.2–3.0 crore fixed + performance variable, calibrated to the final applied-AI portfolio scope and the candidate’s current mix. Any long-term participation for mandate 170 follows standard vesting and performance conditions. The Chief Risk Officer appointment in Mumbai, centred on the applied-AI portfolio, offers regular exposure to the chair, executive committee and principal capital sponsors. A notice period of up to 6 months can be accommodated for the selected executive in mandate 170.

Confidentiality

To protect the board, incumbent team and candidate, the organisation remains unnamed until a confidential conversation confirms mutual relevance for mandate 170. The operating facts have been rounded and blended expressly to remove identifying signals for mandate 170.