Quick Summary
AHEAD builds platforms for digital business. By weaving together advances in cloud infrastructure, automation and analytics, and software delivery,
The AI Adoption Lead is AHEAD's embedded human answer to the gap between AI deployment and realized value. This is a people-first, business-embedded transformation role, part change manager, part org designer, part coach, and part workforce strategist, dedicated to a specific business unit (BU). Reporting to the VP, Talent and Workforce Transformation, the AI Adoption Lead ensures that the business unit’s employees are genuinely ready to work alongside AI: with the right skills, redesigned roles, reimagined workflows, and the confidence to operate in a continuously evolving environment.
- 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
- Assess whether the BU's current structure enables or inhibits AI-augmented ways of working
- Advise on structural changes — spans, layers, team composition, and human–agent workflow design
- Support BU leadership in redefining management accountabilities as AI takes on operational tasks
- Identify and pilot new operating models, such as human-in-the-loop decision flows
- Document and share org design patterns for replication across the enterprise
- Build a culture of active participation in AI transformation, not passive compliance
- Surface and address fear, mistrust, and equity concerns across BU employee groups
- Embed responsible AI practices, transparency, human validation, governance, into team norms
- Partner with the Talent Development team to equip managers to lead AI-augmented teams, orchestrating humans and AI agents together, not just using AI tools themselves
- Run dedicated BU manager learning programs focused on judgment, coaching, and human–AI workflow oversight
- Own the BU's AI adoption measurement framework, design and instrument metrics, not just report on them
- Partner with eTech to ensure adoption data (usage, frequency, depth) is accessible and actionable
- Surface informal and shadow AI use within the BU and channel it into governed, productive adoption
- Track adoption health across workforce segments including tenure, function, generation, and role level
- Feed BU intelligence upward into the Hive Transformation Office to inform org-wide strategy
Nice to Have
~2 min readLocation & Eligibility
Listing Details
- Posted
- June 23, 2026
- First seen
- June 23, 2026
- Last seen
- June 23, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 87%
- Scored at
- June 23, 2026
Signal breakdown
Please let Thinkahead know you found this job on Jobera.
3 other jobs at Thinkahead
View all →Explore open roles at Thinkahead.
Similar Lead jobs
View all →Browse Similar Jobs
Stay ahead of the market
Get the latest job openings, salary trends, and hiring insights delivered to your inbox every week.
No spam. Unsubscribe at any time.