AI Product Manager

Norton Blake Limited; Greater London; On-site; GBP 90,000 - 140,000; Full time

Job summary

Norton Blake Limited is seeking an AI Product Manager to lead the definition, measurement and delivery of AI value across a major banking organisation. You will work with senior stakeholders to translate AI investment into measurable outcomes and support forecasting and investment decisions.

You will develop AI value frameworks, define leading and lagging metrics, and establish centralised quantification methodologies to enable bankwide planning and governance.

Qualifications

• Proven experience in product management, strategy, transformation, consulting or value/benefits realisation within AI, data, technology or digital portfolios.
• Strong understanding of AI and GenAI value drivers, including traditional automation, citizen AI, consumption-based models and agentic AI workflows.
• Experience developing business cases, ROI models, benefits frameworks, KPI hierarchies or financial value assessments for technology-led initiatives.
• Ability to translate complex AI investment and delivery activity into clear commercial, operational and risk-related outcomes.
• Strong stakeholder management and influencing skills, with experience engaging senior leaders, budget holders, product owners and operational teams.

Responsibilities

• Own the workstream responsible for defining and quantifying the value delivered through AI initiatives across the organisation.
• Develop and enhance AI value frameworks and approaches, drawing on industry-leading research and case studies.
• Define a clear hierarchy of metrics to demonstrate AI value beyond productivity gains.
• Establish a robust, centralised methodology for AI value quantification for bankwide forecasting.
• Assess how emerging AI models could transform the future banking operating model and identify required investments.
• Partner with product owners, COOs and senior stakeholders to align on AI value measurement and ROI assumptions.
• Influence stakeholders to build confidence in the proposed AI value approach and ROI tracking.
• Lead the development of spend per outcome metric as a measurable L2 deliverable by October.
• Establish reporting and governance for AI value to enable transparent decision making.
• Produce quantitative AI ROI case studies demonstrating measurable outcomes and scalable lessons.

Tools

AI platforms

Job description

We are seeking an AI Product Manager to lead the definition, measurement and delivery of AI value across a major banking organisation.

This is a highly visible role focused on establishing a credible, centralised approach to AI value quantification. You will work with senior stakeholders across business divisions to define how AI investment translates into measurable commercial and operational outcomes, supporting bankwide forecasting, prioritisation and investment decisions.

Key Responsibilities

• Own the workstream responsible for defining and quantifying the value delivered through AI initiatives across the organisation.
• Develop and enhance AI value frameworks and approaches, drawing on industry-leading research, best-practice case studies and different AI consumption models, including Citizen AI, metered consumption and reusable agentic workflows.
• Define a clear hierarchy of leading and lagging metrics to demonstrate AI value beyond productivity gains, including risk reduction, revenue generation, cost avoidance and cost reduction.
• Establish a robust, centralised and adaptable methodology for AI value quantification, suitable for use in bankwide forecast modelling and investment planning.
• Assess how emerging AI models, including agentic workspaces and agentic commerce, could transform the future banking operating model, and identify the capabilities, change and investment required to realise this value.
• Partner with product owners, divisional budget holders, COOs and senior business stakeholders to align on AI value measurement, ROI assumptions and prioritisation decisions.
• Influence and challenge stakeholders where required, building confidence in the proposed approach to AI value, benefits tracking and return on investment.
• Lead the development of the first “spend per outcome” metric, targeted as an L2 deliverable by the end of October. This will involve stakeholder outreach, interviews, business-unit engagement and a detailed understanding of divisional priorities and operating models.
• Establish clear reporting and governance for AI value, enabling consistent measurement, transparent performance tracking and evidence-based decision making.
• Produce quantitative AI ROI case studies, targeted as an L2 deliverable by December, demonstrating measurable outcomes and scalable lessons for future AI investment.

Required Experience

• Proven experience in product management, strategy, transformation, consulting or value/benefits realisation within AI, data, technology or digital portfolios.
• Strong understanding of AI and GenAI value drivers, including traditional automation, citizen AI, consumption-based models and agentic AI workflows.
• Demonstrable experience developing business cases, ROI models, benefits frameworks, KPI hierarchies or financial value assessments for technology-led initiatives.
• Ability to translate complex AI investment and delivery activity into clear commercial, operational and risk-related outcomes.
• Strong stakeholder management and influencing skills, with experience engaging senior leaders, budget holders, product owners and operational teams.
• Experience working within a large, complex or regulated organisation. Banking, financial services or another highly regulated sector would be advantageous.
• Excellent analytical, structured problem-solving and communication skills, with the ability to present a compelling case to both technical and non-technical audiences.
• Experience of AI strategy, AI operating models, AI governance or enterprise AI transformation.
• Knowledge of agentic AI, autonomous workflows, AI platforms, AI consumption models or AI-enabled customer journeys.
• Experience defining metrics and reporting for investment portfolios, transformation programmes or enterprise technology initiatives.
• Awareness of the banking operating model, including divisional P&Ls, risk management and regulatory considerations.