Global Sales & Services Operations (GSSO) is the team that helps shape Gartner's mission-critical sales and services priorities and works with sales and services leaders to drive tactical and analytical insights. As an associate on the GSSO team, you'll be at the forefront of the ongoing transformation of Gartner's sales and services teams, which drive approximately $5.3B in Contract Value (CV). You will partner with business leaders across Gartner to support global sales and services teams comprised of nearly 9,000 associates who sell to and service every major function across the enterprise
About this roleWe are seeking a business-facing AI Product Leader to lead the design and delivery of AI-enabled products that transform enterprise sales processes. This role will provide dedicated product ownership for Sales Assistant, Enterprise Assistant, and related AI-enabled sales workflows.
The role partners closely with Sales, Sales Operations, Data Science, UX, Architecture, Salesforce, Engineering, Legal, Information Security, and Change Management to translate business needs into scalable, secure, and measurable products. The successful candidate will combine enterprise sales-process expertise, product management discipline, technical fluency, and a practical understanding of AI and agentic workflows.
This is an opportunity to shape how AI supports the future of enterprise selling. You will assess existing sales processes, identify opportunities for simplification and transformation, and determine where work should be agent-led, automated, guided, or supported through native platform capabilities. You will own products from discovery and solution design through development, pilot, launch, adoption, and continuous improvement.
What You'll Do- Reimagine enterprise sales processes for an agent-driven future by assessing current workflows and identifying opportunities to simplify, redesign, automate, or enhance them with AI.
- Lead product discovery with business leaders, frontline sellers, operations teams, and other users to understand processes, pain points, client needs, controls, and desired outcomes.
- Translate business needs into future-state workflows, product requirements, experience designs, roadmaps, success measures, and prioritized backlogs.
- Determine the right solution approach for each use case, distinguishing between agent-led, automated, guided, and native-platform capabilities.
- Lead products through the full product lifecycle, including discovery, solutioning, requirements definition, build, testing, pilots, launch, feedback, iteration, and scaled rollout.
- Partner with Data Science, Engineering, UX, Architecture, Salesforce, and data teams to deliver secure, scalable, and intuitive AI-enabled experiences.
- Apply practical knowledge of AI applications, prompts, data grounding, orchestration, evaluations, guardrails, context management, and human-in-the-loop workflows.
- Facilitate demonstrations, pilots, user feedback sessions, design reviews, and leadership readouts.
- Orchestrate delivery across Sales, Operations, Product, Data Science, Engineering, Architecture, Legal, Information Security, and Change Management.
- Communicate product direction, decisions, dependencies, risks, trade-offs, delivery progress, and business impact to senior stakeholders.
- Influence and align teams across the organization without relying on direct authority.
- Establish and track measures of product quality, adoption, user experience, seller efficiency, and impact on sales execution.
- Balance user value, technical feasibility, enterprise risk, scalability, governance, and speed of delivery.
- Ensure products operate effectively within a governed enterprise environment, including privacy, security, access, and regulatory requirements
What You'll Need- Bachelor's Degree or Equivalent
- 10+ years relevant experience
- Enterprise sales-process expertise: Demonstrated understanding of enterprise selling, including account planning, opportunity management, QBRs, seller workflows, Salesforce, and sales enablement.
- AI product fluency: Practical experience applying AI to business processes, including agentic workflows, prompts, data grounding, orchestration, evaluations, guardrails, context management, and human-in-the-loop design.
- Process-transformation skills: Ability to analyze an existing business process, identify opportunities for simplification or redesign, and determine whether the right solution is agent-led, automated, guided, or platform-based.
- Product discovery and requirements skills: Ability to facilitate discovery with business leaders and end users, identify underlying needs, define future-state workflows, and translate findings into clear product requirements.
- End-to-end product delivery experience: Demonstrated ability to take a digital, data, or AI product from an ambiguous problem through solution design, backlog development, build, testing, pilot, launch, adoption, and iteration.
- Technical product judgment: Sufficient technical fluency to collaborate effectively with Engineering, Data Science, Architecture, Salesforce, and data teams; assess solution options; understand dependencies; and make informed trade-offs.
- Prioritization and roadmap management: Ability to prioritize work based on user value, business impact, technical feasibility, risk, scalability, and delivery speed.
- User-centered problem solving: Ability to understand user needs through interviews, observation, feedback sessions, demonstrations, and pilots rather than relying solely on stated requirements.
- Outcome measurement: Experience defining and tracking success measures such as product quality, adoption, user experience, seller efficiency, process effectiveness, and business impact.
- Stakeholder influence: Demonstrated ability to align and influence cross-functional teams-including Sales, Operations, Product, Technology, Data Science, Legal, Information Security, and Change Management-without direct authority.
- Executive communication: Ability to communicate product direction, recommendations, risks, dependencies, trade-offs, decisions, delivery progress, and business impact clearly to senior stakeholders.
- Enterprise governance awareness: Experience incorporating privacy, security, access, legal, regulatory, and responsible AI considerations into product decisions and delivery.
