Principal, AI Strategy & Analytics

Genesys•Raleigh, NC

6d•$161,500 - $283,900•Hybrid

About The Position

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.

Requirements

Bachelor’s degree in Business, Economics, Mathematics, Statistics, Data Science, Computer Science, Engineering, Operations Research, or a related field.
10+ years of experience in consulting, analytics, AI strategy, customer experience transformation, digital transformation, value realization, management consulting, or a related field.
Demonstrated experience leading executive-level strategic engagements or advisory conversations.
Strong quantitative and analytical background with experience applying data to business decision-making.
Experience developing KPI frameworks, ROI models, value realization strategies, business cases, performance measurement programs, or benchmarking methodologies.
Strong understanding of AI, automation, customer experience, analytics, digital engagement, and transformation concepts.
Ability to analyze imperfect or incomplete data and turn it into practical, defensible recommendations.
Exceptional executive communication, facilitation, storytelling, and presentation skills.
Ability to translate complex technical, analytical, and operational concepts into business-focused recommendations.
Proven ability to influence senior stakeholders and drive alignment across multiple teams or functions.

Nice To Haves

Advanced degree such as MBA, MS Analytics, Data Science, Economics, Engineering, Statistics, Operations Research, or related field.
Experience with consulting, advisory, strategy, or transformation organizations.
Experience in customer experience, contact center, CCaaS, SaaS, digital transformation, AI, analytics, or automation industries.
Familiarity with Genesys Cloud, conversational AI, predictive routing, workforce engagement, customer journey analytics, agent assist, knowledge, bots, or AI-enabled customer experience platforms.
Experience applying statistical analysis, experimentation, optimization techniques, operational research, or causal measurement approaches to business problems.
Experience with contact center metrics such as containment, AHT, FCR, transfer rate, escalation rate, abandon rate, service level, agent utilization, customer effort, CSAT, NPS, and adoption metrics.

Responsibilities

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.
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.
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.
Contribute to the continued development of the AI Outcomes methodology, including outcome intelligence, applied AI, and outcome engineering frameworks.
Create repeatable tools, accelerators, playbooks, KPI libraries, value models, assessment methods, and analytical templates that improve consistency and scalability.
Develop practical guidance that helps internal teams frame customer conversations around measurable outcomes rather than standalone capabilities.
Mentor consultants, strategists, delivery leaders, and customer-facing teams on outcome-driven AI strategy, KPI mapping, and value realization approaches.
Help establish common language, reusable frameworks, and repeatable methods for defining, measuring, and optimizing AI outcomes.
Partner with Professional Services, Customer Experience Advisory, Technical Account Managers, Customer Success leaders, and other internal teams to support complex customer scenarios.
Support high-priority customer situations, including strategic opportunities, executive escalations, renewal support, adoption challenges, and complex transformation initiatives.
Provide strategic and analytical support to help execution teams move forward with clearer goals, stronger measurement plans, and better prioritization.
Represent the NACS AI Strategy Team as a subject matter expert in customer meetings, internal enablement, leadership discussions, and thought leadership activities.