Adoption Specialist

• Change Management StrategyAnalyzing psychological barriers to AI-native transformation and designing organizational initiatives to overcome them
• Internal CommunicationPlanning and executing communication strategies that convey the vision, significance, and progress of transformation across the organization
• Training Program DesignPlanning and running workshops, e-learning, and training programs to elevate AI literacy
• CoachingGuiding mindset shifts at every level, from frontline teams to executives, with tailored support
• Adoption Measurement & ImprovementQuantitative monitoring of adoption rates, usage depth, and psychological resistance, with continuous improvement cycles
• Stakeholder EngagementBuilding trust with key stakeholders and forming internal alliances to drive transformation

Required Experience & Skills

Problem Framing
The ability to transform a client request like “we want to adopt AI” into an organizational question: “In which department, in which process, and whose psychological barriers are blocking transformation?” Digging beneath the surface-level symptom of “not being used” to uncover the structures of fear, anxiety, vested interests, and habits, and defining where to intervene first

Problem Solving
Forming hypotheses about organizational resistance and anxiety, validating them through small-scale pilots and dialogue sessions, and adjusting the approach incrementally. Not “changing everyone at once” but “sparking change in a few influential people and spreading success stories” — strategic execution. Resilience to push transformation forward persistently, adapting flexibly to unexpected pushback

Communication
Empathizing with frontline workers’ anxieties while conveying the significance of transformation, presenting progress and outcomes with data to executives, and sharing technical constraints and possibilities with IT departments — understanding each person’s position, emotions, and interests and adapting language and delivery accordingly. Building consensus through dialogue rather than silencing dissent

Change Management
Structurally analyzing psychological resistance to change and developing strategies informed by the organization’s culture, power structures, and incentive design. Viewing “why they can’t change” as a systemic organizational issue rather than an individual problem, and driving transformation end-to-end from roadmap design through stakeholder engagement

Internal Communication
Translating the transformation vision beyond abstract slogans into language that each department and level can receive as personally relevant, and designing internal adoption. Building consensus through dialogue rather than eliminating dissent, and strategically scaling success stories to maintain transformation momentum

Training Design
Experience planning and designing training programs and e-learning for AI literacy improvement. Facilitating workshops that let participants discover and try for themselves rather than one-way knowledge transfer. Customizing curricula based on participants’ levels and departments

Coaching
Coaching experience spanning executives to frontline teams, both individual and group. Facilitation that drives behavioral change through “drawing out insights” rather than “teaching.” Building psychological safety within teams that tolerates failure and encourages experimentation

Nice to Have

Business Process Understanding
Experience in process improvement and operational efficiency projects. Ability to visualize and analyze workflows, identifying where AI should and should not intervene. Judging the impact and feasibility of transformation based on understanding of frontline operations

Data Literacy
Experience quantitatively measuring AI adoption rates, workflow efficiency, and behavioral changes, and connecting them to ROI analysis. Objectively demonstrating transformation progress through data visualization and reporting, and proposing next actions

ML/AI Fundamentals
Basic understanding of how machine learning and AI models work — what training data means, why models sometimes give wrong answers, and the difference between deterministic and probabilistic outputs. Essential for setting realistic expectations during adoption and helping users understand AI behavior without technical jargon

AI Tool Awareness
Understanding the characteristics, limitations, and appropriate use cases of major AI tools such as ChatGPT, Claude, GitHub Copilot, and Gemini. Knowledge sufficient to provide specific guidance tailored to users’ business contexts and honestly communicate what AI can and cannot do

Project Management
Experience tracking overall transformation program progress and managing multiple workstreams simultaneously. Regular stakeholder reporting, early risk detection, and proposing countermeasures