AI Adoption Lead

AHEAD

1d•$130,000 - $150,000•Hybrid

About The Position

AHEAD builds platforms for digital business. By weaving together advances in cloud infrastructure, automation and analytics, and software delivery, we help enterprises deliver on the promise of digital transformation. At AHEAD, we prioritize creating a culture of belonging, where all perspectives and voices are represented, valued, respected, and heard. We create spaces to empower everyone to speak up, make change, and drive the culture at AHEAD. We are an equal opportunity employer, and do not discriminate based on an individual's race, national origin, color, gender, gender identity, gender expression, sexual orientation, religion, age, disability, marital status, or any other protected characteristic under applicable law, whether actual or perceived. We embrace all candidates that will contribute to the diversification and enrichment of ideas and perspectives at AHEAD. 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.

Requirements

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

Nice To Haves

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

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