Associate Director, AI Strategy, EY-Parthenon

Location: London

Other locations: Primary Location Only

Date: 16 Sept 2026

Requisition ID: 1743860

At EY, we’re all in to shape your future with confidence. We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world.

Key responsibilities

• Lead sizeable workstreams and selected end-to-end AI strategy engagements, acting as the primary day-to-day client lead and ensuring delivery of commercially impactful outcomes, with oversight and support from Directors and Partners.
• Convert broad client questions into clear hypotheses, issue trees, workplans, analytical requirements, stakeholder plans and decision points.
• Own the day-to-day management of engagements, including team deployment, timelines, dependencies, deliverable quality, client governance, scope management and engagement economics.
• Assess an organisation’s AI maturity, strategic ambition, business priorities, technology landscape, data readiness, talent base and governance capabilities and translate findings into clear strategic recommendations, investment priorities and executive decision points.
• Identify, quantify and prioritise AI value creation opportunities across growth, productivity, cost, risk and customer outcomes, linking opportunities to measurable business impact.
• Develop and prioritise portfolios of AI use cases using commercial value, strategic relevance, feasibility, risk, data readiness and time-to-impact criteria.
• Define target AI operating models, including decision rights, governance, funding, delivery structures, talent requirements and collaboration between business, technology, data and risk teams.
• Evaluate build, buy and partner choices, including the implications of foundation models, cloud providers, specialist AI vendors and existing enterprise platforms.
• Develop practical AI roadmaps, investment requirements, business cases, capability-building plans and implementation priorities based on the guidance from Directors, Partners and EY Experts, balancing value, feasibility, organisational readiness and implementation risk.
• Deliver AI-focused transaction work.
• Lead or support buy-side AI due diligence for private equity and corporate investors, assessing the risks from AI to the business model / credibility and commercial relevance of a target’s AI capabilities and strategy.
• Assess whether claimed AI capabilities are proprietary, defensible and material to the investment thesis, rather than superficial product features or repackaged third-party functionality.
• Quantify potential AI value creation opportunities, associated execution requirements and implications for value creation thesis.
• Identify material risks, capability gaps, technical debt, cost exposures and dependencies that may affect valuation, deal terms or integration planning.
• For vendor due diligence, develop an evidence-backed AI equity story that clearly articulates current capabilities, competitive differentiation, value delivered to date and the future value creation opportunity.
• Prepare management teams to respond credibly to investor scrutiny of the company’s AI capabilities, roadmap, economics and defensibility.
• Present concise, decision-oriented findings to investment committees, deal teams, management teams and other senior stakeholders.
• Support the assessment of post-deal AI value creation opportunities, integration considerations and technology-enabled synergy potential.
• Manage senior stakeholders.
• Build trusted working relationships with C-suite executives, business-unit leaders, AI / Data leaders, functional leaders, private equity investment professionals and portfolio management teams.
• Plan and facilitate executive interviews, workshops, working sessions and steering committees.
• Communicate complex AI and technology topics in clear commercial language tailored to the audience.
• Serve as a trusted advisor to senior stakeholders on AI strategy, investment priorities and transformation decisions.
• Build long-term executive relationships and identify opportunities to expand EY-Parthenon's impact with clients.
• Lead and develop teams.
• Lead multidisciplinary teams of consultants and specialists, typically combining strategy, commercial, data, technology, operating model, sector and transaction expertise.
• Coach junior colleagues in structured problem-solving, analytics, story lining, client communication and professional judgement.
• Provide apprenticeship-style coaching, helping team members develop consulting judgement, executive communication and commercial thinking.
• Create an inclusive, collaborative and high-performance team environment, including during periods of significant delivery pressure.
• Provide meaningful feedback and contribute to the formal and informal development of team members.
• Support business and proposition development.
• Play a leading role in proposals, pitches and commercial discussions, owning sections of pursuits and contributing to conversion efforts.
• Help shape AI strategy, AI transformation and AI transaction propositions based on recurring client needs and market developments.
• Identify potential follow-on opportunities arising from existing engagements and support their conversion.
• Contribute to selected thought leadership, market perspectives and client events.
• Build internal and external market relationships that support future business development opportunities.
• Build the practice.
• Contribute to the development of EY-Parthenon's AI Strategy methodology, propositions, tools and intellectual property.
• Support recruitment, capability building and knowledge sharing across the AI Strategy team.
• Develop points of view on emerging AI trends, business implications and sector-specific opportunities.
• Help strengthen EY-Parthenon's market position through thought leadership and external engagement.

Skills and attributes for success

• Structured strategy consulting capability.
• Strong hypothesis-led problem-solving skills and the ability to structure complex or ambiguous questions.
• Excellent analytical judgement, including the ability to distinguish material issues from interesting but non-critical detail.
• Experience combining primary research, secondary research, quantitative analysis and expert input into an integrated answer.
• Strong storylining and synthesis skills, with the ability to develop concise, executive-level recommendations.
• Ability to shape executive decision-making by converting analysis into clear strategic choices and recommendations.
• Confidence operating at pace, with incomplete information and under demanding client deadlines.
• A high degree of personal ownership, attention to detail and commitment to quality.
• Techno-commercial AI fluency.
• A sound understanding of the principal components of the enterprise AI landscape, including generative AI, predictive machine learning, foundation models, data platforms, cloud infrastructure, model deployment and AI-enabled enterprise applications.
• The ability to understand and discuss AI architecture, data requirements, integration considerations, model lifecycle management, MLOps or LLMOps, security, privacy and responsible AI and the judgement to bring in specialist experts when deeper technical, legal, cyber or regulatory expertise is required.
• The judgement to assess where technical depth is required and when to involve specialist architects, engineers, data scientists, cyber professionals, lawyers or risk experts.
• The ability to engage credibly with architects, engineers and data scientists while maintaining focus on commercial and strategic outcomes.
• The ability to translate technical choices into implications for value, cost, scalability, speed, risk, differentiation and strategic control.
• Familiarity with the commercial dynamics of the AI ecosystem, including hyperscalers, foundation-model providers, enterprise software vendors, specialist AI companies and open-source technologies.
• A practical rather than purely theoretical perspective on what is required to deploy and scale AI in a large organisation.
• Commercial and quantitative capability.
• Strong commercial acumen and the ability to connect AI opportunities to business strategy, competitive advantage and financial performance.
• Experience developing business cases, value-driver trees, market assessments, cost models, investment requirements and implementation roadmaps.
• Experience linking AI investment decisions to enterprise value creation, shareholder value and competitive advantage.
• The ability to assess total cost of ownership, unit economics, operating expenditure, capital expenditure, implementation costs and potential value realisation.
• Strong Excel and PowerPoint capability, together with confidence interpreting financial, operational and technical solutions / artefacts.
• The ability to evaluate claims critically and distinguish demonstrated value from untested assumptions.
• Leadership and communication.
• Strong project and team leadership, including the ability to manage multiple workstreams and disciplines.
• Credibility with senior executives and the confidence to lead challenging conversations.
• Excellent written and verbal communication, with the ability to explain complex topics clearly and precisely.
• The ability to influence without relying on formal authority.
• A proactive, low-ego and collaborative working style.
• Intellectual curiosity and a sustained interest in AI, technology, innovation and their commercial implications.

Candidates must have:

• At least Six years of management consulting experience, with substantial experience gained within a recognised strategy or management consulting firm, strategy boutique, or strategy-led transactions practice.