AI Transformation Manager

Job Description & Summary

The opportunity

Convert business priorities into high-value AI products and agentic workflows, owning discovery, process redesign, product direction, agile backlog and benefits realization.

What you will be doing

· Lead value-discovery and process-design workshops with business and technology stakeholders.

· Map current workflows, decisions, hand-offs, pain points, controls and performance baselines.

· Prioritize agentic use cases based on value, feasibility, risk and time to impact.

· Act as product owner or product-management lead for client delivery, maintaining outcomes, roadmap and backlog.

· Define business cases, KPIs, benefit owners and measurement approaches.

· Coordinate user adoption, operating-model changes and transition to business ownership.

What we need from you

· 7+ years in management consulting, digital transformation, product management or process improvement.

· Strong experience in business cases, process redesign, agile delivery and executive facilitation.

· Ability to translate business needs into clear product outcomes and acceptance criteria.

· Working understanding of AI, agents, data dependencies, human oversight and automation.

Relevant AI technologies and tooling

· Working knowledge of agentic solution concepts, including tool calling, workflow orchestration, memory, retrieval-augmented generation, human-in-the-loop controls, evaluation and observability.

· Ability to convert a business process into agent roles, tools, decision points, structured inputs and outputs, exception paths, acceptance criteria and measurable value hypotheses.

· Familiarity with platforms and frameworks used by delivery teams, such as LangChain and LangGraph, Microsoft Agent Framework or Semantic Kernel, OpenAI Agents SDK, Microsoft Copilot Studio and workflow automation platforms.

· Experience using Agile product-management tooling such as Azure DevOps or Jira to manage epics, user stories, acceptance criteria, dependencies, releases and benefits measures.

Measures of success

· Value of prioritized use cases

· Backlog quality and stakeholder alignment

· Speed from discovery to usable release

· Benefits measured after deployment

· Client adoption and satisfaction

Key interfaces

· Other members of the AI Transformation & Agentic Systems Practice

· PwC sector, functional, cloud, cyber, risk, Responsible AI and change specialists

· Client business owners, product owners, technology teams and operational users

· Technology alliance and implementation partners where relevant

Contribution to the practice

· Support proposals, client workshops and market development appropriate to seniority.

· Contribute reusable methods, patterns, code, assets and lessons learned.

· Coach colleagues and participate in the capability’s continuous learning agenda.

· Uphold PwC quality, independence, confidentiality and risk-management requirements.

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