Transformation change strategy & execution: Develop and execute structured change management strategies for enterprise transformation initiatives, including digital, data, process, and AI-enabled programs; define change approach, roadmap, adoption plan, and success measures.
AI change management & responsible adoption: Lead change activities that help employees understand, trust, and effectively adopt AI capabilities, including role-based impacts, responsible use expectations, human-in-the-loop practices, model limitations, privacy, security, and governance requirements.
Stakeholder engagement & alignment: Identify and manage stakeholder groups across operations, customer, corporate functions, OT, IT, HR, legal/compliance, and leadership; facilitate engagement sessions, readiness discussions, and feedback loops to secure alignment and reduce adoption risk. Develop and manage business change champion and AI ambassador networks to accelerate adoption, gather feedback, identify resistance, and promote best-practice sharing across the enterprise.
Change impact assessment & readiness: Assess current-state processes, operating model impacts, role changes, skills gaps, adoption barriers, and resistance points; translate findings into readiness plans, mitigation actions, and targeted interventions. Integrate change management activities into agile delivery, product development, release management, and business deployment processes to ensure adoption planning begins early in the initiative’s lifecycle.
Communications & training enablement: Partner with Communications, P & O, business leaders, and program teams to develop clear messaging, leadership talking points, training materials, user guides, office hours, and adoption campaigns that support successful transition.
Business process redesign & adoption support: Support process redesign and operating model changes needed to embed transformation outcomes into day-to-day work; coordinate with business teams to align procedures, controls, accountabilities, and adoption milestones.
Metrics, value realization & adoption monitoring: Define and track change adoption KPIs, including stakeholder readiness, training completion, usage, proficiency, satisfaction, behavior change, operational impact, and value realization; prepare executive-ready reporting and insights. Analyze user adoption patterns using platform telemetry, survey feedback, training participation, and business KPIs to identify adoption gaps and recommend targeted interventions.
Risk, governance & compliance partnership: Embed change management into governance checkpoints and project lifecycles; coordinate with AI governance, legal/compliance, cybersecurity, privacy, and risk teams to ensure adoption plans reflect applicable policies and controls.
Sustainment & continuous improvement: Support pilot-to-production transitions, adoption reinforcement, lessons learned, continuous improvement cycles, and post-implementation sustainment plans to ensure transformation benefits are realized and maintained.
AI literacy and workforce capability development: Partner with business leaders, HR/P&O, and learning teams to develop AI literacy programs, role-based learning pathways, AI champion networks, and workforce upskilling initiatives that improve organizational readiness and AI fluency.