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.
Duties/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
- 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
AI Change Strategy & Adoption
Role & Job Redesign
Capability & Skill Building
Strategic Workforce Planning
Organizational Design
Culture & Responsible AI
Manager Enablement
Adoption Measurement & Intelligence
Education and Experience
- 8+ years in change management, HR transformation, org effectiveness, or related people and OD roles
- Demonstrated experience leading large-scale technology or digital transformation from the people side
- Strong grasp of change frameworks and ability to adapt them to AI contexts
- Experience in workforce planning, role design, or job architecture
- Ability to build trust and credibility with business unit leaders and frontline employees
- Data literacy with comfort using adoption metrics and workforce analytics to drive decisions
- Personal proficiency with AI tools and genuine enthusiasm for AI-augmented work
- Experience embedded in a business unit (not just HR or CoE roles)
- Exposure to agentic AI, automation workflow design, or human-in-the-loop process redesign
- Background in learning & development or capability-building at scale
- Knowledge of org design principles and structural assessment methodologies
- Experience with skills-based talent models and dynamic workforce planning tools
- Industry knowledge aligned to the target business unit
- Certification or coursework in AI transformation leadership
Preferred:
Skills Required
- 8+ years in change management, HR transformation, org effectiveness, or related people and OD roles
- Demonstrated experience leading large-scale technology or digital transformation from the people side
- Strong grasp of change frameworks and ability to adapt them to AI contexts
- Experience in workforce planning, role design, or job architecture
- Ability to build trust and credibility with business unit leaders and frontline employees
- Data literacy with comfort using adoption metrics and workforce analytics to drive decisions
- Personal proficiency with AI tools and genuine enthusiasm for AI-augmented work
- Experience embedded in a business unit (not just HR or CoE roles)
- Exposure to agentic AI, automation workflow design, or human-in-the-loop process redesign
- Background in learning & development or capability-building at scale
- Knowledge of org design principles and structural assessment methodologies
- Experience with skills-based talent models and dynamic workforce planning tools
- Industry knowledge aligned to the target business unit
- Certification or coursework in AI transformation leadership
AHEAD Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about AHEAD and has not been reviewed or approved by AHEAD.
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Retirement Support — 401(k) contributions are matched dollar-for-dollar on the first $5,000 each year, with matching made each pay period and immediate 100% vesting. This structure signals above-standard employer support for retirement savings.
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Affordable Benefits — Medical options include low employee premiums for PPO and HDHP plans, and the HDHP adds employer HSA funding plus a dollar-for-dollar HSA match up to stated amounts. Dental and vision plans list very low per-paycheck costs, helping keep overall healthcare spend manageable.
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Wellbeing & Lifestyle Benefits — No-cost telemedicine (including virtual mental health when enrolled), free Calm access for the employee and dependents, and an EAP with counseling are included. Company-paid life and disability plus voluntary protections (legal/ID, pet insurance) and other extras round out a comprehensive set of supports.
AHEAD Insights
What We Do
AHEAD builds platforms for digital business. By weaving together cloud infrastructure, intelligent operations, and modern applications, we help enterprises deliver on the promise of digital transformation.


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