AI Adoption Lead

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. Duties/Responsibilities AI Change Strategy & Adoption 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 Role & Job Redesign 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 Capability & Skill Building 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 Strategic Workforce Planning 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 Organizational Design 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 Culture & Responsible AI 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 Manager Enablement 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 Adoption Measurement & Intelligence Own the BU's AI adoption measurement framework, design and instrument metrics, not just report on them Partner with the Tech 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 Education and Experience Minimum 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 Preferred 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 Compensation $130,000 - $150,000 a year Benefits Medical, Dental, and Vision Insurance 401(k) Paid company holidays Paid time off Paid parental and caregiver leave Plus more! 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