AI Enablement Lead$144,000 - $180,000 + bonus. This role also requires a minimum of 2 days a week onsite in the IANS Boston office.
About the RoleIANS is seeking a highly collaborative and execution-oriented
AI Enablement Lead, to drive enterprise-wide AI adoption as part of the AI Enablement function. This role is responsible for translating proven AI workflows and agentic outputs into repeatable, scalable practices across IANS-ensuring that the best ideas developed in the Agentic Capabilities & Output Studio reach the teams and clients who need them.
This is an execution and change management role that also requires direct, hands-on technical implementation - building working tools, not only coordinating others' work. The AI Enablement Lead operates with significant autonomy inside a centrally governed function, working directly with functional leaders across Research, Sales, Client Services, and Product to prioritize, build, deploy, and embed AI-enabled workflows into day-to-day operations.
The AI Enablement function exists to answer a single question: How do we scale what works; quickly, responsibly, and in ways that deliver measurable value to clients and the organization?
Key ResponsibilitiesPrioritization & Pipeline Management- Partner with the Chief Product Officer and functional leaders to maintain a ranked pipeline of AI use cases tied to client and business impact.
- Apply clear criteria to identify which initiatives to accelerate, pause, or stop-actively preventing duplication and low-value experimentation.
- Serve as the primary coordination point between the Agentic Capabilities & Output Studio and the broader organization.
Workflow Rollout & Adoption- Build, deploy, and own AI workflows, dashboards, and tools across functions, from first working prototype through enterprise-wide rollout.
- Develop adoption playbooks, training materials, and onboarding resources that make new workflows accessible and repeatable for non-technical users.
- Design and build the measurement layer itself - usage instrumentation, health-scoring models, live dashboards, and scheduled reporting - and use it to track adoption, surface at-risk accounts, and continuously improve deployed workflows.
- Continuously observe how deployed systems, pipelines, and agents behave in production, and inject enhancements and automation wherever they add leverage - treating live systems as something to watch, tune, and improve, not just to launch.
Change Management & Enablement- Lead change management efforts to build AI fluency and confidence across the organization, moving teams beyond experimentation toward consistent, productive use.
- Serve as a trusted internal resource on what AI tools can and cannot do in practice-grounded in evidence, not hype.
- Champion a culture of urgency, focus, and accountability around AI adoption without sacrificing quality or governance.
Cross-Functional Collaboration- Work closely with the Agentic Lead, Product, Technology, and Research teams to ensure workflows handed off for scaling are well-documented, tested, and fit for purpose.
- Collaborate with functional leaders to embed AI-enabled outputs into recurring client workflows, increasing the depth and stickiness of IANS's value proposition.
- Contribute observations and adoption learnings that inform broader AI strategy, governance, and roadmap decisions.
Qualifications- Demonstrated experience driving adoption of new tools, workflows, or practices across a cross-functional organization.
- Strong project management and prioritization skills, with the ability to manage multiple workstreams and stakeholders simultaneously.
- Excellent communication and facilitation skills, with the ability to translate technical capabilities into practical, accessible guidance for non-technical audiences.
- Comfortably operating in fast-moving, ambiguous environments with a bias toward action and measurable outcomes.
- Strong judgment around what is scalable and impactful versus merely interesting-and the confidence to advocate for focus.
Preferred Qualifications- Experience working in or alongside product, research, or content-driven organizations.
- Hands-on fluency with AI tools and LLMs, plus enough technical range to build working solutions independently - writing SQL against a data warehouse, assembling dashboards, authoring agent and automation skills, and reasoning about connectors, identity, and data pipelines.
- Background in learning & development, internal consulting, or operational transformation roles.
- Exposure to change management frameworks or adoption measurement approaches.
