EY
Senior Manager - Microsoft - AI Business Transformation - TC - FS
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Senior Manager - Microsoft - AI Business Transformation
Position overview
This is a senior role for a hands-on transformation leader who helps financial services clients move from AI ambition to practical delivery. The role leads design, pilot and build work across business process, operating model, colleague experience, data, technology, risk and change.
The Senior Manager will work with client sponsors such as product owners, CIO, CDO, CAIO and COO teams, risk and compliance functions and delivery teams to shape AI patterns and use cases, build practical roadmaps and deliver controlled solutions that create measurable value.
Microsoft platform literacy and Co-sell experience are important. The role requires high-level architecture skills, but more importantly must be able to connect business needs to Microsoft technologies and bring this to life for a client.
Role objective
- Lead the design and delivery of AI-enabled transformation programmes for financial services clients, helping them move from strategy and use case shaping into implementation, adoption and measurable value.
- Connect business needs, AI opportunities, Microsoft platform capabilities, risk controls and change delivery.
- Build strong working relationships with Microsoft teams to support joint propositions, co-sell activity, co-build opportunities and follow-on pipeline growth.
Your client impact
- Turn client ambition into clear AI use cases, target-state designs, value cases, roadmaps and delivery plans.
- Redesign business processes, customer journeys, colleague journeys and operating models using AI, automation and data.
- Lead build, pilot and scale workstreams so AI-enabled solutions are usable, secure, controlled and aligned to business outcomes.
- Help clients prioritise AI opportunities based on value, feasibility, risk, complexity and readiness to adopt.
- Embed responsible AI, data governance, security, controls, testing, adoption and benefits tracking into delivery plans.
- Connect business stakeholders, technology teams, data teams, risk, compliance and change teams around a shared delivery plan.
- Work with Microsoft account, specialist and engineering teams where their platform insight can improve solution design or delivery confidence.
- Produce clear materials for senior decision forums, including steering committees, design authorities, programme boards and executive reviews.
Key responsibilities
AI transformation design
- Lead discovery, stakeholder interviews, workshops, process reviews, data reviews and opportunity assessments.
- Define problem statements, design principles, future-state journeys, process changes, role impacts and operating model implications.
- Identify and prioritise AI patterns and use cases using a balanced view of business value, technical feasibility, risk, cost, data readiness and adoption effort.
- Create practical business cases, benefits models, MVP scopes, transformation roadmaps and delivery plans.
- Work with AI, data, architecture and technology specialists to ensure recommendations are feasible and aligned to enterprise architecture and control requirements.
Build, pilot and scale delivery
- Lead workstreams that move AI-enabled designs into prototypes, proofs of concept, pilots and scaled solutions.
- Translate business designs into requirements, user stories, acceptance criteria, test plans and adoption plans.
- Coordinate business, technology, data, risk and change activity so delivery remains aligned to the agreed transformation vision.
- Manage delivery risks, dependencies, issues, scope changes and stakeholder expectations.
- Track benefits and run costs so delivery teams stay focused on measurable value, not only solution build.
- Support handover into business as usual, including ownership, support model, controls, monitoring and continuous improvement.
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Responsible AI, risk and governance
- Embed responsible AI controls into design, build, test, release and run activities.
- Help define human review, escalation and approval points for higher-risk AI workflows.
- Support AI evaluation approaches covering accuracy, groundedness, bias, toxicity, security, privacy, explainability and business fitness.
- Consider AI-specific risks such as hallucination, prompt injection, unsafe tool use, data leakage and poor knowledge grounding.
- Align delivery with financial services expectations for model risk, operational resilience, data governance, GDPR, auditability and secure-by-design change.
Microsoft ecosystem and alliance working
- Assess where Microsoft capabilities can accelerate delivery, including Microsoft 365 Copilot, Copilot Studio, Azure AI Foundry, Azure OpenAI Service, Microsoft Fabric, Power Platform, Microsoft Purview, Entra ID, Defender and Sentinel.
- Explain Microsoft platform choices in clear business language for senior stakeholders.
- Work with Microsoft account, specialist sales and engineering teams to validate platform fit, align to priority workloads and de-risk delivery.
- Support co-sell and co-build activity by contributing to joint propositions, solution narratives, client briefings and follow-on opportunities.
Client and team leadership
- Act as the trusted day-to-day delivery lead for senior client stakeholders.
- Lead multidisciplinary teams across business analysis, process design, AI, data, technology, architecture, risk, compliance, change and testing.
- Coach junior team members and create a high-performance delivery environment.
- Manage engagement economics, delivery quality, scope, risks and timelines.
- Contribute to proposals, client pitches and follow-on opportunity development where relevant.
Success in this role
- Clients have a clear AI transformation roadmap linked to measurable business value.
- AI use cases move from design into controlled pilots and scalable implementation.
- Solutions are adopted by users and embedded into real business processes.
- AI risks, data issues, security requirements and governance controls are addressed early.
- Microsoft platform choices are linked to business outcomes, architecture fit and delivery feasibility.
- Engagements create follow-on opportunities through strong client delivery and Microsoft ecosystem collaboration.
Essential experience
- Strong consulting experience, ideally in Big 4, financial services consultancy, technology consultancy or transformation advisory.
- Experience leading AI, automation, data or digital transformation work from design into delivery.
- Strong understanding of regulated financial services environments and the constraints of delivering change within them.
- Experience engaging senior stakeholders and managing delivery expectations in complex organisations.
- Experience working in agile, product-based or hybrid delivery environments.
- Experience developing business cases, roadmaps, MVPs, pilots, proofs of concept or scaled enterprise solutions.
- Practical knowledge of responsible AI, data governance, AI governance, model risk, and regulatory expectations.
- Experience managing multidisciplinary teams across business, technology, data, risk, compliance and change.
- Experience working with Microsoft teams or partner ecosystem motions, including co-sell, co-build, joint propositions or technical validation.
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Essential skills
- Transformation delivery leadership.
- Experience of working with Microsoft in a Co-sell or Co-build motion.
- Business design and operating model design.
- Workshop facilitation and stakeholder management.
- Structured problem solving and analytical thinking.
- Ability to translate business needs into practical AI-enabled solutions.
- Financial services domain knowledge.
- Programme and workstream management.
- Benefits-led delivery and value tracking.
- Risk, issue, dependency and scope management.
- Team leadership, coaching and quality review.
Microsoft platform and AI knowledge
The candidate should be able to understand, explain and work with specialists across the following areas:
- Microsoft 365 Copilot as a user experience layer for knowledge work and AI-enabled productivity.
- Copilot Studio for custom agents, agent flows, connectors, tools, triggers and human review steps.
- Azure AI Foundry and Azure OpenAI Service for enterprise AI applications, agents, model access, evaluation and monitoring.
- High-level understanding of Microsoft Fabric for data products, analytics, OneLake, AI grounding and governed data workflows.
- Power Platform for workflow automation, low-code apps and business process enablement.
- Microsoft Purview, Entra ID, Defender, Sentinel, sensitivity labelling, data loss prevention, auditability and secure-by-design delivery.
- AI design patterns such as enterprise knowledge assistants, custom copilots, agentic workflows, intelligent document processing, customer service augmentation, compliance automation and colleague productivity transformation.
Desirable experience
- Microsoft AI, Azure, Fabric, Power Platform, security or data certifications.
- Experience integrating AI into enterprise systems of record such as CRM, ERP, HR, finance, risk, policy, document management, workflow and service management platforms.
- Experience in banking, insurance, wealth management, asset management, capital markets, payments, risk, compliance, finance or operations transformation.
Candidate profile
The ideal candidate is a hands-on transformation leader who can move confidently between strategy, design and delivery. They will be comfortable leading client workshops, managing complex stakeholder groups, creating practical future-state designs and driving implementation through ambiguity.
They will understand that successful AI transformation is not only about technology. It also requires clear business ownership, strong governance, adoption by colleagues, trusted controls and a delivery approach that creates measurable value.
They will be credible with business, CIO, data, risk and compliance stakeholders, and able to work effectively with Microsoft teams to create mutual commercial value and improve delivery confidence.
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