Director, Artificial Intelligence, Finance

Your role

Set the strategy and build alignment:

• Define and communicate a value-first AI strategy and roadmap for Global Finance, aligned with Finance priorities, enterprise AI strategy, technology standards and the Financial Systems roadmap.
• Determine where AI can materially improve outcomes, where conventional automation or process redesign is preferable, and where an opportunity should not proceed.
• Build a shared agenda across FP&A, Controllership, Project Finance and other Finance teams; engage regional and business leaders to identify needs that can scale.
• Advise Finance leadership on investment choices, dependencies and risks; secure sponsorship and rally teams that do not report to the Director.

Own a disciplined portfolio of use cases:

• Establish transparent intake and prioritization connected to enterprise channels and governance; assess business value, process and data readiness, feasibility, adoption, total cost and risk.
• Maintain a sequenced portfolio with named sponsors, accountable process owners, delivery partners, milestones and clear decisions to proceed, change direction or stop.
• Prioritize a few opportunities with a credible path to impact over a large collection of pilots. Candidate areas include reporting commentary, Finance knowledge access, exception handling, forecasting support, collections and project-margin early warning; each requires its own assessment and business case.

Make the business case and prove the return:

• Require proportionate business cases before material investment, with baselines, expected benefits, implementation and ongoing costs, risks, dependencies, adoption assumptions and alternatives.
• Distinguish time saved from capacity genuinely redeployed and from cost removed; do not treat these as interchangeable financial benefits.
• Agree measurement methods and benefit owners before delivery; track investment and realized value at use-case and portfolio levels, with independent validation where appropriate.
• Report candidly on adoption, net value, cost and control effectiveness; recommend whether to improve, scale or discontinue initiatives that underperform.

Build, test and demonstrate solutions personally:

• Personally design, build and refine selected Finance agents and AI-enabled workflows, especially early prototypes and focused solutions that accelerate learning.
• Use Microsoft Copilot and Copilot Studio hands-on to configure agents, test them with users, assess reliability and improve outputs based on feedback.
• Use AI tools regularly in professional work to improve analysis, research, drafting and workflow execution, applying appropriate review and data-handling requirements.
• Turn Finance problems into working demonstrations; assess limitations and costs, and decide whether a solution should stop, improve or enter the approved production route.
• Stay close enough to delivery to challenge designs, troubleshoot barriers and coach builders, without being the sole developer of enterprise-scale products; partner with Digital and IT on supported deployment.

Establish practical, responsible governance:

• Translate enterprise AI policy and standards into a Finance operating model covering ownership, intake, risk assessment, testing, approvals, human oversight, monitoring and lifecycle management.
• Partner with Digital, IT, the Chief Digital Officer's'organization, Cybersecurity, Privacy, Legal, Risk and Internal Audit to clarify decision rights and navigate the path from idea to approved production use.
• Protect sensitive Finance and client information through appropriate access, validation, traceability and human review before AI outputs inform reporting or decisions.
• Work with data and process owners on source quality, definitions and controls; reuse approved enterprise platforms and challenge unnecessary complexity without bypassing security or technology accountabilities.

Deliver through partnership and adoption:

• Partner with the Financial Systems CoE so initiatives fit ERP, EPM and reporting architecture without creating competing technology roadmaps.
• Agree delivery responsibilities with Digital and IT while retaining Finance accountability for business outcomes; redesign workflows with process owners around human decisions, exceptions and controls.
• Lead communications, training and feedback to build user confidence; create reusable approaches that can scale across regions while respecting genuine process and risk differences.

Lead a lean, high-impact team:

• Build and coach a small team with commercial judgment, hands-on capability and delivery discipline; mobilize a federated network of Finance champions, process owners and enterprise specialists.
• Create a culture of curiosity, constructive challenge, accountability and collaboration, including the confidence to recommend "not AI" when appropriate.
• Represent Finance in enterprise AI forums and lead by example as both sponsor and practitioner: demonstrate tools, share what works and acknowledge limitations.