AI Adoption Lead

AHEAD - Remote, United States

Non-technical Verified Jul 4, 2026 Source: thinkahead.com

This role is part of the Internal AI Job Board, a curated list of jobs for teams building or operating internal AI systems. Follow the original role page for the employer description, requirements, and application flow.

Compensation: $130,000 - $150,000 a year The compensation range indicated in this posting reflects the On-Target Earnings (“OTE”) for this role, which includes a base salary and any applicable target bonus amount

Responsibilities

Partner with the OCM team to design and execute a BU-level AI change strategy, moving employees from AI experimenters to AI accelerators
Develop and run stakeholder engagement plans, including resistance mapping and influence strategies
Build a network of champions and superusers within the BU to sustain adoption momentum
Monitor adoption signals and adjust interventions based on real-time uptake data
Address employee anxiety and build psychological safety around AI-augmented work
Conduct systematic task deconstruction across BU roles to identify what AI automates, augments, or creates
Redesign job descriptions and role profiles to reflect new human–AI responsibilities
Work with BU leaders to define new AI-augmented job families and career pathways
Identify roles at risk of displacement and proactively design transition pathways
Partner with job architects and compensation teams to update role-leveling frameworks
Assess BU-level AI fluency and identify skill gaps across functions, levels, and workforce segments
Commission or co-design targeted learning programs — technical, workflow, and mindset
Integrate AI capability-building into daily workflows, not just stand-alone training events
Develop manager enablement specifically for leading AI-augmented teams
Track and report on capability uplift against BU transformation milestones
Build a dynamic skills supply/demand picture for the BU accounting for humans and AI agents
Identify future workforce requirements based on AI-driven process changes (12–36 month horizon)
Inform build/buy/borrow/automate decisions for critical capability gaps
Support BU leaders in scenario planning for headcount and structure as AI scales
Feed BU insights into enterprise-wide strategic workforce planning processes