Business Director, AI Strategy & Transformation - Enterprise Risk Management

Business Director, AI Strategy & Transformation – Enterprise Risk Management The Director of AI Strategy & Transformation for Enterprise Risk Management is a strategic leadership role focused on modernizing enterprise risk management through technology and data‑driven insights. This leader will set the long‑term vision and strategy for integrating Artificial Intelligence, Machine Learning, advanced language models, and transformational data analytics into ERM processes. This role will lead two complementary teams: an AI Strategy team and a specialized Data & Analytics Transformation team. Distinct from our established ERM Data, Analytics, and Reporting function, this specialized Data & Analytics team will be solely dedicated to transforming how we conduct risk management. The Director will guide this team to test hypotheses, identify opportunities to adjust our methodologies, and build data‑driven business cases for our destination state. Acting as a bridge between risk professionals, product, and technology teams, this role will synergize these efforts—using D&A to uncover opportunities and build the case for change, and using the AI team to automate those modernized processes to increase the efficiency and effectiveness of the risk function. The ideal candidate will balance a multi‑year vision with the delivery of immediate, practical quick wins. Role Responsibilities Data & Analytics for Risk Transformation Lead and develop a specialized Data & Analytics team focused exclusively on transformational initiatives, operating distinctly from the existing Business As Usual (BAU) data team. Direct hypothesis‑driven data exploration to identify where and how risk management programs, processes, and methodologies should evolve to drive value, time savings, and enhanced risk oversight. Foster a complementary ecosystem between D&A and AI: leverage the D&A team to identify bottlenecks and build the business case for process changes, while deploying the AI team to automate and optimize those modernized processes via machine learning. Use data to continuously measure the impact of transformational changes, define the "destination state" of our risk capabilities, and guide the strategic roadmap. Strategy Development & Execution Formulate a multi‑year AI vision and strategy for ERM that sets a clear long‑term direction for modernizing enterprise risk management while remaining aligned with the overall enterprise strategy. Design a balanced implementation roadmap that delivers immediate quick wins, such as automating highly manual tasks and processes to prove value early while simultaneously building toward long‑term, foundational AI capabilities. Establish a clear prioritization framework to evaluate potential AI use cases based on their complexity, speed to implementation, and long‑term impact on effectiveness and efficiency. Secure executive alignment through clear business cases that balance improving operational efficiency with the strategic value of long‑term risk reduction. Define the data, technology, and change‑management plans required to sustainably support AI tools over time, ensuring the team transitions smoothly from legacy processes to AI‑assisted workflows. AI Implementation & Internal Tool Development Identify and prioritize high‑impact opportunities to use AI, Machine Learning, and Large Language Models to improve the speed, accuracy, and efficiency of enterprise risk management processes. Partner directly with Product, Tech, and Data teams to build, test, and deploy custom internal AI tools specifically tailored for risk managers and compliance officers. Review successful AI projects and tools used in other parts of the company (such as first line risk offices) and adapt those proven technologies for use within the ERM framework. Enhancing Efficiency with Advanced Models Use advanced models like Gemini and Claude in day‑to‑day risk management workflows to automate highly manual tasks in execution of enterprise risk processes. Build automated workflows that use AI to parse and analyze large volumes of unstructured data. Layer AI capabilities on top of existing risk management systems to extract better insights, flag operational anomalies, and reduce manual data entry for the team. Team Adoption & Value Tracking Lead the practical training and upskilling of the ERM team, ensuring risk professionals know how to effectively use, prompt, and validate the outputs of new AI tools. Define and track clear metrics to measure the success of AI adoption, focusing on time saved, reduced manual errors, and earlier detection of risks. Requirements Experience & Technical Familiarity Practical experience identifying, scoping, and launching AI projects, with a solid understanding of how to use models like Gemini or Claude safely within a secure corporate environment. Strong understanding of modern data setups, including how AI models search internal documents, connect to existing databases, and automate workflows. Leadership & Collaboration Proven ability to work across departments, serving as the bridge between product, technology, data and risk and compliance professionals. A practical, results‑oriented mindset with the ability to take an idea from a simple test case all the way to a functioning tool used by the team. Strong communication skills, with the ability to clearly explain the benefits and limitations of AI technologies to senior leaders. Basic Qualifications Bachelor’s Degree At least 4 years of experience performing quantitative analysis At least 4 years of experience performing qualitative analysis At least 2 years of experience performing people management At least 2 years of experience performing project management Preferred Qualifications Master’s Degree 2+ years of experience in financial services 1+ year of experience in consulting 3+ years of experience in Enterprise Risk Management, Operational Risk, or Technology Management, with a track record of successfully delivering technology modernization projects Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. McLean, VA: $230,400 - $263,000 for Business Director. Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(s) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well‑being. Learn more at Capital One Careers website. Eligibility varies based on full or part‑time status, exempt or non‑exempt status, and management level. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non‑discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug‑free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23‑A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901‑4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. For technical support or questions about Capital One's recruiting process, please send an email to View email address on click.appcast.io. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. 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