Principal, AI Strategy & Analytics

Be the one building AI-powered experiences where they matter most.

At Genesys, we help organizations create better customer experiences through AI-powered experience orchestration. Our platform connects people, systems, data and AI to help organizations deliver more personalized service, improve operational efficiency and build stronger customer relationships.

Help build, support and operate technology used by more than 8,000 organizations in over 100 countries – moving AI from possibility to production in real-world enterprise environments every day.

The Principal, AI Strategy & Analytics is a senior strategic advisory role responsible for helping customers and internal teams identify where AI can create measurable business value, how that value should be quantified, and how outcomes should be validated over time.

This role combines executive-level consulting, customer experience strategy, quantitative analysis, value realization, and AI transformation expertise. The Principal will help shape outcome-led AI engagements by translating business goals into measurable opportunity areas, KPI frameworks, value models, and prioritized recommendations.

This individual will work across business, operational, analytical, and technical domains while partnering closely with Professional Services, Customer Experience Advisory, Technical Account Managers, Customer Success leadership, and other internal teams. The role is focused on strategy, measurement, and decision support — not product management, sales ownership, or implementation delivery.

The ideal candidate is a strong executive communicator and analytical problem solver who can bring structure to ambiguous customer situations, use data to clarify opportunity areas, and help teams define what success should look like before, during, and after AI adoption.

Key Responsibilities:

Strategic AI Advisory and Outcome Alignment

• Engage with executive stakeholders and internal teams to align AI initiatives with measurable business objectives.
• Lead strategic advisory engagements focused on AI adoption, value realization, customer experience transformation, operational improvement, and outcome definition.
• Facilitate executive workshops, AI strategy sessions, value realization discussions, and outcome-focused planning activities.
• Translate customer business goals, operational constraints, and experience challenges into practical AI opportunity roadmaps.
• Help customers and internal teams prioritize AI use cases based on value potential, feasibility, readiness, data availability, and measurable impact.
• Develop clear narratives that connect AI capabilities to business outcomes, operational performance, customer experience improvement, and long-term value realization.

Outcome Intelligence and Analytics

• Develop KPI frameworks, value realization models, measurement strategies, benchmarking approaches, and business impact models.
• Analyze customer operational, journey, interaction, digital, routing, bot, and experience data to identify friction, constraints, and improvement opportunities.
• Establish baseline measurement approaches that help customers understand current-state performance before AI initiatives are scaled or optimized.
• Create executive-ready reporting, scorecards, business cases, and analytical summaries that quantify AI impact and identify opportunities for improvement.
• Apply statistical, analytical, and modeling techniques to evaluate trends, performance drivers, adoption gaps, and optimization opportunities.
• Support before-and-after measurement strategies that help determine whether AI initiatives are producing meaningful business change.

AI Strategy and Value Realization

• Evaluate customer readiness for AI adoption, including operational maturity, data availability, reporting capability, KPI clarity, governance, and organizational readiness.
• Develop phased AI transformation strategies that help customers move from experimentation to measurable impact.
• Identify opportunities to improve customer experience, operational efficiency, self-service effectiveness, routing performance, agent productivity, and adoption of AI-enabled capabilities.
• Help customers validate whether existing AI investments are producing expected value and identify where tuning, redesign, enablement, or operating model changes may be needed.
• Provide thought leadership on outcome-led AI, value realization, AI readiness, customer experience optimization, and measurable transformation.

Methodology and Practice Development

• Contribute to the continued development of the AI Outcomes methodology, including outc