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
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