AI ADOPTION WORKSHOPS & LEARNING
Build the capability and reinforcement required for organisational AI adoption
Forward Transformation designs connected learning for leaders, managers and priority roles.
Through tailored workshops, application labs and learning pathways, participants develop the understanding, judgement and practical capability to apply AI responsibly in their work. Organisations strengthen the expectations, manager support and reinforcement needed for learning to continue beyond the session.
Every engagement is led by Selina Thompson, a senior change and digital adoption consultant with more than 15 years of enterprise experience.
Enterprise experience in role-based AI enablement
30 role-based AI sessions
Designed for senior leaders, people managers and subject-matter experts in a complex EMEA organisation.
60% average improvement
Average improvement in assessed AI proficiency following role-based learning and application.
15+ years
Experience leading digital adoption, workforce readiness and behaviour change across global organisations.
When AI learning alone is not changing how work gets done
General AI awareness and tool training can build important knowledge. Organisational adoption requires people to connect that foundation to their roles, responsibilities and real workflows.
Learning becomes more useful when it addresses why AI matters to the work, the concerns that may limit responsible use, where it is genuinely valuable, how human judgement should be applied and what support is needed after the session.
What participants develop
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role-relevant understanding;
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confidence through practice;
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responsible-use judgement;
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clearer use cases and boundaries; and
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practical next steps for their work.
What the organisation can strengthen
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clearer leadership expectations;
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better-equipped managers;
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more consistent role-based practices;
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reinforcement beyond the learning event; and
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evidence of what participants can understand and apply.
Connected learning for the people responsible for AI adoption
Leaders, managers and employees play different roles in organisational AI adoption. Learning is tailored to the decisions, conversations and work each audience needs to handle.
Leadership learning
Help leaders understand their role in AI adoption, align expectations and make better decisions about workforce application.
AI Adoption learning helps leaders:
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connect AI priorities to meaningful changes in work;
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clarify what they expect managers and teams to do differently;
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recognise concerns, dependencies and support needs;
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agree where human accountability remains essential; and
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identify useful signals of progress.
Manager enablement
Help managers guide responsible experimentation, hold practical team conversations and reinforce appropriate AI use.
AI Adoption enablement helps managers:
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discuss appropriate AI use with their teams;
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guide responsible experimentation;
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address uncertainty and surface adoption barriers;
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maintain quality standards and human judgement;
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coach application in relevant work; and
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reinforce useful practices after the session.
Role-based AI application
Help priority roles explore relevant AI use cases, practise relevant applications, and define the role of human judgement.
AI Adoption application helps participants:
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identify valuable use cases within their responsibilities;
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examine what changes in the workflow and what remains human;
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practise with relevant scenarios or approved tools;
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review quality, risk and decision boundaries; and
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turn promising experimentation into practical next steps.
Designed around your organisation and the work
The format of organisational AI adoption learning follows your requirements. Selina works with the client team to connect each adoption intervention to the audience, organisational context and work participants need to understand or apply.
Prepare the learning
Understand the audience, approved tools or use cases, relevant workflows, existing capability, boundaries and intended outcomes.
Set the context
Connect the learning to why AI matters, where it fits in the work, what responsible application requires and what is expected of the audience.
Facilitate and coach application
Use discussion, practical scenarios and guided practice to help participants apply ideas, exercise judgement and learn from one another.
Evaluate and reinforce
Assess learning and application, identify remaining support needs and recommend appropriate follow-up or reinforcement.
Delivery may include leadership sessions, manager workshops, role-based application labs, facilitated practice, adoption clinics and reinforcement sessions.
Choose how learning can support organisational AI adoption
The right approach depends on what needs to change.
You may need to address one immediate adoption challenge, build confidence and capability across a priority audience, or connect learning to a wider AI programme.
Focused AI adoption workshop
Best when you need to address one defined adoption challenge with a specific audience.
This workshop aligns leaders around their role in adoption, preparing managers to support responsible AI use or helping a priority role connect AI to real work.
The session is designed to create shared understanding, practical decisions and clear next steps.
Where useful, follow-up can be added to reinforce the learning and support application in the workplace.
Role-based AI adoption learning pathway
Best when a priority audience needs to build confidence and capability over time.
Connected sessions help participants move from understanding where AI can support their work to applying it in real tasks, exercising judgement and building more consistent ways of working.
The pathway can include manager involvement, guided application between sessions and reinforcement based on what participants experience in practice.
Learning within an enterprise AI adoption programme
Best when learning needs to support a broader AI initiative rather than sit alongside it.
Learning is designed around the programme’s priority roles, workflows, approved use cases, governance expectations and measures of progress.
This can include leadership learning, manager enablement and role-based application, helping capability-building support the organisational changes the programme is trying to achieve.
Forward Transformation can design and facilitate the learning workstream independently or alongside internal L&D, change, AI, technology and business teams.
When learning is only part of the problem
If the challenge also involves understanding why adoption is stalling, clarifying ownership or coordinating the wider organisational adoption effort, learning alone may not be enough.
Forward Transformation helps organisations diagnose AI adoption barriers and coordinate the next stages to build people capability and business transformation.
Explore AI Adoption Consultancy
Frequently asked questions about AI adoption workshops and learning pathways
1 / Can the learning be tailored to our approved AI tools and use cases?
Yes. Selina can design learning around the AI tools, approved use cases, workflows and organisational guidance already in place.
The focus is on helping people apply AI responsibly within their roles and day-to-day work, rather than providing generic product instruction.
2 / Who are AI adoption workshops designed for?
AI adoption workshops can be designed for senior leaders, people managers, champions, specialist functions or priority role groups.
Different audiences can take part in separate sessions or in a connected learning pathway, depending on what each group needs to understand, practise or reinforce.
3 / Should we choose a single AI adoption workshop or a longer learning pathway?
A single workshop works best when there is one clearly defined adoption need. A learning pathway is more appropriate when confidence, capability and behaviour need to develop through practice and reinforcement over time.
The right format depends on the audience, the adoption challenge and what needs to change in real work.
4 / Can AI adoption learning complement our existing internal or vendor training?
Yes. Forward Transformation can build on existing AI literacy, policy, governance or vendor-led tool training.
Selina focuses on the next layer: connecting that knowledge to specific roles, workflows, manager support and responsible application in everyday work.
5 / How is AI adoption learning evaluated?
Evaluation is shaped around the purpose of the engagement and the changes the organisation wants to see.
It may include participant feedback, confidence or proficiency measures, evidence of practical application, manager feedback and agreed follow-up measures linked to the role or workflow.
Where learning forms part of a wider AI adoption programme, evaluation can also connect to broader adoption and business measures.
Discuss your organisational AI Adoption workshop or learning requirement
Tell Selina who the learning is for, what is already in place and what you need people to understand, practise or apply differently in their work.
You don't need a finished brief at this stage. Selina can help identify whether the best fit is a focused workshop, a connected learning pathway or learning delivered within a wider AI adoption programme.
