AI Strategy and Adoption Consultant

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

Function: Information Technology
Experience Level: Mid-Senior Level