AI Strategy and Adoption Consultant

Job Description Roles & Responsibilities : This role helps SDS and its clients to move from AI experimentation to enterprise-scale impact — assessing maturity, shaping the use-case portfolio, defining transformation roadmaps and operating models, and driving adoption. Based in the AI CoE, the consultant multiplexes to Data & AI Service Line engagements, combining diagnostic rigor, transformation planning, and executive stakeholder engagement. AI Maturity assessment - Design and maintain AI maturity assessment frameworks spanning strategy, data, technology, governance, operating model, adoption, risk, and value. - Conduct maturity assessments across business units, functions, and regions; benchmark current state and identify gaps against target-state capabilities. - Identify, shape, and prioritise AI use cases — including GenAI and agentic solutions — based on value, feasibility, data readiness, risk, and scalability. Transformation strategy and Roadmap development - Develop AI transformation roadmaps with short to long-term initiatives, tailored to business priorities, maturity, and org readiness. - Recommend AI operating models with governance interfaces. - Build business cases and ROI models; establish tracking of value realization across the portfolio. - Guide the maturity journey from PoC to production-scale AI use case adoption Consult for client engagements - Support leadership decision-making through structured recommendations, business cases, and executive briefings. Act as a trusted advisor to stakeholders in client organisations. - Facilitate discovery workshops, interviews, and executive alignment sessions; derive actionable recommendations and transformation programs with defined success metrics. - Support pre-sales for Service Line AI transformation engagements. Change Management and capability building - Define adoption playbooks and change management interventions. - Advise on capability-building pathways, collaborating with talent and delivery teams to address skill gaps. - Development of consulting assets, accelerators, and AI service offerings. Experience - 10–12 years in AI/digital strategy, management consulting, enterprise transformation, or business architecture Expected Skills - Strong grasp of the AI/ML and GenAI landscape, adoption challenges, Scaling PoCs to production - Experience with maturity/capability frameworks and assessments, operating model design, and transformation roadmap development - Proven ability to build business cases, value models, and ROI narratives that secure investment - Exposure to MLOps, Responsible AI and AI Governance - Experience working alongside engineering and architecture teams in a services or product organization Stakeholder skills - Excellent executive communication; ability to influence without authority