EY
Senior Manager - AI Business Transformation - TC - FS
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Senior Manager - AI Business Transformation - Financial Services
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Position Overview
This is a senior delivery role focused on leading AI-enabled transformation programmes for financial services clients. The Senior Manager will take opportunities that have been shaped and sold, and turn them into practical client outcomes.
Most engagements begin with a design phase, in which the team defines:
- The future vision
- Priority use cases
- Value case
- Operating model
- Delivery roadmap
- Implementation approach
Engagements then transition into a build phase, where solutions, processes, controls, adoption plans and new ways of working are developed and implemented.
The role demands:
- A strong consultant with deep financial services experience
- Robust delivery discipline
- The ability to connect business design, AI, data, technology, risk and change
Role Objective
Lead the successful design and delivery of AI-enabled business transformation programmes, helping financial services clients transition from AI ambition to practical implementation and measurable value creation.
Your Client Impact
- Lead design-phase engagements, defining how AI can transform:
- Business processes
- Customer journeys
- Operating models
- Colleague experience
- Translate client ambition into:
- Prioritised AI use cases
- Target-state designs
- Value cases
- Implementation roadmaps
- Delivery plans
- Work with clients to uncover:
- Pain points
- Operational inefficiencies
- Customer challenges
- Risk issues
- Revenue opportunities
- Design future ways of working, combining:
- Human expertise
- AI capabilities
- Automation
- Data-driven decisioning
- Strengthened controls
- Lead build-phase delivery workstreams, ensuring AI-enabled solutions are usable, scalable, controlled, and aligned to business outcomes.
- Manage multidisciplinary teams across:
- Business analysis
- Process design
- AI
- Data
- Technology
- Architecture
- Risk
- Change
- Testing
- Facilate workshops with client teams, including:
- Current-state process mapping
- Opportunity identification
- Future-state design co-creation
- Delivery priority agreement
- Ensure transformation plans address:
- Adoption
- Governance
- Training
- Skills
- Controls
- Data readiness
- Operational integration
- Support clients in measuring benefits across:
- Revenue growth
- Cost reduction
- Customer satisfaction
- Operational efficiency
- Risk reduction
- Maintain delivery quality, managing:
- Engagement risks
- Clear, practical, and senior-decision-ready outputs
Key Responsibilities
Design-Phase Delivery
- Lead discovery and design activities:
- Stakeholder interviews
- Workshops
- Process reviews
- Data analysis
- Opportunity assessment
- Develop:
- Clear problem statements
- Design principles
- Future-state journeys
- Process models
- Role impacts
- Operating model changes
- Identify and prioritise AI use cases based on:
- Value
- Feasibility
- Risk
- Implementation complexity
- Organisational readiness
- Create business cases and benefits models quantifying expected impact across:
- Financial, customer, operational, and risk outcomes
- Define:
- Transformation roadmaps
- MVP scope
- Sequencing
- Delivery plans
- Adoption approaches
- Collaborate with AI, data, and technology specialists to ensure recommendations are:
- Technically feasible
- Aligned to:
- Enterprise architecture
- Data strategy
- Control requirements
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Build-Phase Delivery
- Lead workstreams moving AI-enabled designs into:
- Implementation
- Pilot
- Scale
- Coordinate business, technology, data, risk, and change activities to maintain alignment with agreed transformation vision.
- Support development of:
- AI-enabled workflows
- Prototypes
- Proofs of concept
- Pilots
- Scaled enterprise solutions
- Ensure clarity in:
- Business requirements
- User stories
- Acceptance criteria
- Controls
- Testing approaches
- Adoption plans
- Manage:
- Delivery risks
- Dependencies
- Issues
- Scope changes
- Stakeholder expectations
- Track benefits realisation, focusing delivery teams on measurable business outcomes.
Financial Services Transformation Expertise
- Apply knowledge across:
- Retail banking
- Commercial banking
- Insurance
- Wealth management
- Asset management
- Capital markets
- Risk
- Compliance
- Operations
- Customer service
- Understand:
- Regulatory environment in financial services
- Ensure AI-driven transformation considers:
- Conduct
- Customer outcomes
- Operational resilience
- Data privacy
- Model risk
- Financial crime
- Regulatory compliance
- Responsible AI
- Guide clients in balancing:
- Innovation
- Risk management
- Governance
- Operational practicality
Client and Team Leadership
- Serve as a trusted day-to-day delivery lead for senior client stakeholders.
- Prepare and present materials for:
- Steering committees
- Design authorities
- Programme boards
- Executive decision forums
- Lead multidisciplinary teams of:
- Consultants
- Business analysts
- Designers
- Technologists
- Subject matter specialists
- Coach junior team members, fostering high-performance delivery.
- Manage:
- Engagement economics
- Delivery quality
- Scope
- Risks
- Timelines
- Contribute to proposals and follow-on opportunity development.
Essential Experience
- Strong consulting experience, ideally from:
- Big 4 firms
- Financial services consultancies
- Technology consultancies
- Transformation advisory firms
- Deep understanding of:
- AI
- Generative AI
- Automation
- Data-led transformation
- Business implications
- Experience:
- Engaging senior client stakeholders
- Managing delivery expectations in complex environments
- Knowledge of regulatory financial services environments and practical change-delivery constraints.
- Familiarity with AI use cases, including:
- Intelligent document processing
- Customer service AI
- Advisor enablement
- Underwriting support
- Claims automation
- Lending decision support
- Financial crime analytics
- Risk and compliance automation
- Knowledge management
- Operational workflow redesign
- Experience with delivery methodologies:
- Agile
- Product-based approaches
- Hybrid environments
- Practice within:
- MVP development
- Pilots
- Proofs of concept
- Scaled enterprise solutions
- Knowledge of:
- Responsible AI
- Model risk management
- Data governance
- GDPR
- AI governance
- Regulatory expectations
- Exposure to:
- Cloud computing
- Data platforms
- Workflow tools
- CRM platforms
- Case management solutions
- Enterprise AI platforms
- Proven track record in leading:
- Design phases for complex programmes (current-state assessment, future-state design, benefit modelling, roadmapping)
- Build phases (delivery planning, agile delivery, testing, adoption, benefit tracking)
- Experience managing and coordinating teams across:
- Business
- Technology
- Data
- Risk
- Change functions
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Essential Skills
- Transformation delivery leadership
- Business design and operating model design
- Workshop facilitation & stakeholder management
- Structured problem-solving and analytical thinking
- Ability to translate business needs into AI-enabled solutions
- Financial services domain expertise
- Project and workstream management
- Excellent written and verbal communication
- Benefits-led delivery and value tracking
- Risk, issue, dependency, and scope management
- Team leadership, coaching, and quality review
Candidate Profile
The ideal candidate is a hands-on transformation leader, comfortable navigating:
- Strategy
- Design
- Delivery
- And, crucially, navigating ambiguity within complex client environments.
Key strengths include the ability to:
- Lead workshops and manage complex stakeholder groups
- Craft practical future-state designs
- Drive implementation while ensuring:
- Clear business ownership
- Strong governance
- Employee adoption
- Reliable controls
- Measurable value
Understand that AI transformation requires more than technology alone.
What It Takes to Succeed
EY offers a competitive total rewards package, including:
- Performance-based compensation
- Support for flexible working
- Career development
FlexEY allows customisation, encompassing:
- Holidays
- Health & well-being
- Insurance
- Savings
- Discounts and offers
Additional Benefits
- Mentorship, coaching, and development from engaging colleagues
- Opportunities to grow new skills and advance your career
- The flexibility to shape your work life according to your needs
If you align with the criteria above, apply today and make an impact shaping the future of AI transformation in financial services. Join us in building a better working world.
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