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The AI Adoption Manager leads end-to-end AI education and adoption programs for enterprise clients, ensuring teams achieve self-sufficiency and measurable business impact. This role acts as the primary client interface, managing relationships, tracking adoption metrics, and aligning all activities with data governance and compliance guardrails.
Lead AI adoption across the client teams — from first assessment, through workshops and hands-on enablement, to self-sufficient daily AI use, with adoption reported as measured business impact.
Neurons Lab delivers AI education and adoption programs for enterprise clients, mainly in financial services (banking, insurance, and capital markets). This role leads those programs inside the customer's own teams — taking each new client from first assessment, through workshops and hands-on enablement, to confident daily AI use.
The AI Adoption Manager is the face of the program with the client. Embedded in the customer's business teams, the role runs the full education and adoption cycle and carries the customer success side of the engagement: building the relationship, keeping adoption healthy, reporting outcomes to client stakeholders, and surfacing where the account can grow. Because most clients operate in regulated financial-services environments, every program runs inside the client's data-governance, compliance, and responsible-AI guardrails.
Post-workshop AI adoption per team (primary KPI)
Measured business impact per team — time saved, cycle-time, or effort reduced against a baseline captured before enablement
Number of active champions identified, developed, and made visible to client leadership
Cadence adherence — recurring sessions held on rhythm, response times measured in hours, not days
Teams released as self-sufficient; qualified opportunities passed to the technical tracks
Engagement growth — follow-up workshops, recurring enablement, new scopes originating from business team engagement
Assess and prioritize — map each team's workflows and current AI usage, turn their real pain points into a prioritized enablement plan, and rule out use cases where the payoff isn't real
Deliver enablement end to end — design and run workshops (personally and with external trainers) that target each team's own use cases and produce walk-away skills, prompts, and tools they use the next day
Build reusable assets — maintain a shared library of approved prompts, skills, and templates teams can reuse without you in the room
Grow champions and adoption — develop champions inside each team, surface and remove adoption blockers, and hold a steady cadence with the business teams
Keep it inside the guardrails — align every plan with the client's data-governance, acceptable-use, and responsible-AI policies, working with IT, security, and legal
Measure and report value — baseline each team, track adoption against targets, and report progress, risks, and ROI to client sponsors
Drive to self-sufficiency and expansion — hand teams over once they sustain AI use on their own, pass engineering-grade work to the technical track, and surface new scopes for the account
Workshop and training design and delivery, with strong live facilitation
Change management and adoption, grounded in instructional design and adult learning
Practical, daily AI fluency (Claude, ChatGPT, agentic workflows, prompt engineering) and the ability to rebuild an expert's workflow as an AI-assisted one for non-technical users
Customer success — trusted client relationships, healthy adoption, and usage turned into demonstrated value
Strategic program design and clear executive, cross-functional communication, with comfort in ambiguity
Modern AI tools, agentic workflows, and prompt engineering, applied practically and daily
Change management and adoption psychology — what makes change stick from within
AI governance and responsible-use frameworks — data classification, acceptable-use, and responsible-AI policy, enough to keep enablement inside client guardrails
Enablement/training business or consulting background
5+ years in change management, enablement, digital-transformation consulting, or enterprise software rollout, including at least one full-cycle deployment
Top-tier management-consulting experience (e.g. McKinsey, BCG, Bain) is a strong plus
Customer success experience strongly desired — owning client relationships, adoption health, and value realization
Hands-on experience driving technology or process adoption inside organizations
Track record designing and delivering workshops/training sessions personally
Experience running assessments, feedback sessions, and executive updates
Fluent English required
Competitive compensation — a monthly base plus expansion revenue upside
Fully remote — outcomes over attendance
Unlimited PTO
Full-time contractor engagement with a fast-growing AI consultancy at the forefront of enterprise transformation
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