Berlin, Germany
AI Adoption Lead
Purpose of the Job
The AI Adoption Lead is responsible for building the AI capabilities, confidence, and responsible-use behaviors required for employees, managers, and leaders to integrate AI into everyday work. The role translates the company’s AI strategy into practical learning journeys, hands-on enablement experiences, and workflow-based adoption support that help people move from awareness to sustained usage and measurable business value.
This role owns the human capability-building layer of AI adoption: AI literacy, role-based learning, practical tool enablement, responsible-use education, prompt and workflow guidance, manager enablement, adoption clinics, community learning, and measurement of skill uplift, usage, confidence, and productivity impact. The role works closely with Digital, IT, HR, Communications, Legal, Risk, Compliance, Cybersecurity, Data Governance, and business leaders to ensure AI training is practical, scalable, safe, and aligned with business priorities.
Tasks & Responsibilities
Strategy, roadmap and governance
- Develop and own the enterprise AI learning and people enablement roadmap, aligned with digital strategy, tool rollout plans, workforce priorities, and responsible AI expectations.
- Translate AI strategy, policies, and governance requirements into practical capability-building priorities for different employee groups.
- Define learning personas and proficiency levels, from AI awareness and responsible use to advanced workflow integration and champion-level expertise.
- Partner with Digital, IT, HR, Legal, Risk, Compliance, Privacy, Cybersecurity, Data Governance, Communications, and business teams to ensure all training content is accurate, compliant, scalable, and easy to apply.
Learning design and content development
- Design role-based AI learning journeys for executives, people managers, knowledge holders, project teams, functional experts, and selected frontline or operational teams.
- Create practical learning assets including quick-start guides, prompt examples, workflow playbooks, tool comparison guides, FAQs, responsible-use checklists, onboarding materials, manager toolkits, and use-case libraries.
- Build learning modules that cover AI fundamentals, approved tools, responsible use, data protection, prompt writing, quality checking, bias and risk awareness, workflow redesign, and productivity use cases with the support of external providers
- Curate external and internal AI learning resources into simple pathways that help employees find the right content at the right moment.
Training delivery and adoption support
- Facilitate engaging training sessions, webinars, team workshops, use cases demos that help employees apply AI tools to real work scenarios.
- Support teams in identifying high-value use cases and embedding AI into recurring workflows, rituals, templates, operating procedures, and collaboration habits.
- Enable managers to coach their teams on responsible AI use, create space for experimentation, and reinforce adoption through team routines.
- Support pilots and scaled rollouts of approved enterprise AI tools such as Microsoft Copilot, ChatGPT Enterprise, Gemini, internal AI assistants, or other approved AI solutions.
Measurement, feedback and continuous improvement
- Define track learning and enablement metrics, including participation, completion, confidence uplift, active usage, repeat usage, workflows changed, time saved, quality improvement, and adoption barriers.
- Use surveys, feedback, office-hour insights, adoption data, and manager input to continuously improve training content and enablement interventions.
- Prepare concise updates, dashboards, and leadership summaries showing progress, risks, capability gaps, and recommended next actions.
Work Experience
- 5+ years of experience in learning and development, digital capability building, enterprise training, technology adoption, change enablement, workforce upskilling, or organizational transformation.
- Proven experience designing and scaling role-based learning journeys, capability academies, workshops, enablement assets, and adoption programs in a complex organization.
- Strong understanding of practical workplace AI applications, responsible-use principles, data protection considerations, and adoption challenges for nontechnical audiences.
- Hands-on experience with enterprise AI or digital productivity tools, ideally Microsoft Copilot or similar AI-enabled workplace platforms.
- Experience translating complex digital, technical, legal, or policy topics into simple, practical, behavior-changing learning content.
Competence
- Excellent facilitation, instructional design, stakeholder management, storytelling, and practical problem-solving skills.
- Ability to make AI accessible, relevant, and safe for employees with different levels of digital confidence.
- Strong empathy for learner needs, adoption barriers, and the behavioral change required to make AI stick in daily work.
- Ability to work credibly with senior leaders, Digital, IT, HR, Communications, Legal, Risk, Compliance, Data Governance, and business teams.
- Experience building learning communities, champion networks, office hours, peer-learning routines, or Centers of Excellence.
- Strong ability to influence without direct authority and align stakeholders around adoption priorities, learning standards, and measurable outcomes.
- Strong program management discipline for learning delivery, enablement planning, adoption support, governance, metrics, and executive reporting.
- Knowledge of learning design, adult learning principles, digital adoption methods, change management, and practical measurement of behavior change.
- Ability to connect AI training to business value, including workflow efficiency, quality improvement, employee experience, and responsible use.