AI for L&D Professionals
capability building,
designed for your organisation.
A custom-built corporate programme for L&D managers, learning designers, training facilitators, instructional designers, learning experience designers, talent development specialists, and corporate university leaders. We design the curriculum around your tech stack, project archetypes, and target business outcomes — delivered by domain-expert trainers and reinforced through AI-evaluated assessments.
A modular syllabus, built to be tailored.
Below is our reference curriculum. Every syllabus we deliver is tailored to your customer-specific requirements — module depth, sequencing, lab environments, and capstone projects are adapted to your team's starting point, tech stack, and target outcomes.
- AI categories in L&D: content authoring, delivery, personalisation, tutoring, analytics
- Tool landscape: ChatGPT, Claude, Gemini, Copilot + L&D-native tools (Synthesia, Articulate AI, Cornerstone, Docebo AI, EdApp)
- What's mature: content authoring, summarisation, translation. What's emerging: AI tutors, adaptive paths
- Strategic implications for L&D operating model
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Demonstrable skills your team will apply on live projects.
Design AI-augmented learning programmes end-to-end
Needs analysis → learning objectives → content → delivery → assessment → measurement — AI applied across the full ADDIE/SAM cycle.
Produce AI-generated learning content at scale
Courseware, slides, video scripts, microlearning — produced with brand-consistent quality and instructional integrity.
Implement AI tutoring and adaptive learning
Conversational tutors, learner-specific paths, AI-driven feedback — aligned to adult-learning principles.
Pass GSDC AI for L&D certification
Two attempts; cohort first-attempt pass rate 92%.
Compress content production by 60-80%
Documented pre/post on real learning programmes; quality maintained or improved per learner feedback.
Lead AI strategy for the L&D function
Equipped to advise on tool stack, build operating model, govern learner-facing AI use.
Where your team is now vs where they'll be after the programme.
Where most teams start
- ·Aware AI is reshaping L&D but unsure which capabilities to adopt and in what order
- ·Limited fluency with AI tools for learning design beyond casual ChatGPT use
- ·Cannot rapidly produce AI-augmented learning content while preserving instructional quality
- ·No framework for AI-augmented learning measurement and Kirkpatrick at scale
- ·Limited fluency with personalisation, adaptive learning, and AI tutor patterns
- ·Concerned about AI's implications for learners but unsure how to design for ethical use
Where they'll arrive
- ✓AI-augmented learning design — needs analysis, learning objectives, content design, assessment design — all 3-5× faster
- ✓Content production at scale — courseware, slides, video scripts, microlearning, knowledge checks — produced with quality and consistency
- ✓Personalisation and adaptive learning — applies AI tutoring patterns, learner-specific paths, AI-driven feedback
- ✓Measurement & analytics — Kirkpatrick at scale, AI-augmented behaviour-change measurement, business-impact tracking
- ✓Ethics & governance — designs L&D for ethical AI use by learners; navigates academic integrity in corporate contexts
- ✓GSDC AI for L&D certification — credential for senior L&D roles
Built for L&D outcomes, not seat counts.
Prompt discipline, not prompt luck
Learners move from trial-and-error prompting to named patterns such as role prompting, few-shot, prompt chaining, and self-critique.
Reusable team assets
The programme produces Custom GPTs, reusable workflow templates, and a shared prompt library that teams can govern and scale.
Daily productivity workflows
Labs focus on email, reports, slides, meetings, spreadsheets, research synthesis, and role-based business assignments.
Measured time savings
Capstone workflows document recurring task compression, review-cycle reduction, and before/after productivity improvements.
Responsible enterprise use
Learners practise confidentiality, IP, bias detection, verification checklists, and safe-use protocols before adoption at scale.
Sustainment built in
30-day, 60-day, and 90-day check-ins help learners keep pace as ChatGPT features and frontier models evolve.
A four-milestone path from skill gap to client-ready.
Foundation & baseline
Establish a working mental model of ChatGPT, frontier models, tokens, context windows, hallucination risks, and model-selection trade-offs.
Prompt engineering labs
Learners practise CRISPE, SPEAR, role prompting, constraint-led prompting, few-shot prompting, self-critique, and prompt iteration on real work scenarios.
Custom GPTs & workflow automation
Each learner builds reusable GPTs and connects ChatGPT to productivity tools for email, documents, spreadsheets, meetings, and research workflows.
Capstone & sustainment
Learners demonstrate a personal AI productivity system and continue with prompt-of-the-week, model-of-the-month, and 30/60/90-day check-ins.
Want this curriculum aligned to your tech stack and project archetypes?
Why enterprise teams choose the B2B engagement model.
Domain-expert trainers, not professional presenters.
"My job isn't to teach ChatGPT as a tool — it's to help professionals build repeatable AI workflows, verify the output, and reclaim hours from routine work."
Taught by people who've actually shipped the work.
Built for L&D leaders and their learners.
Who this is for
- ·Knowledge workers who want to apply ChatGPT productively in their daily workflows
- ·Business analysts, consultants, marketing professionals, project managers, and individual contributors
- ·Teams that use ChatGPT for occasional drafting but need reliable, business-grade outputs
- ·Managers looking to establish team-wide prompt standards and safe-use protocols
- ·Organisations that want to automate repetitive work across email, spreadsheets, calendars, and documents
Pre-requisites
- ·No coding prerequisite for business and productivity tracks
- ·Basic familiarity with workplace tools such as email, documents, spreadsheets, slides, and meetings
- ·Willingness to bring real recurring tasks into labs for workflow redesign
- ·Enterprise cohorts should align data-handling expectations before learners use company or client information
Trusted by L&D leaders across the world.
"The programme moved our team from random prompting to a repeatable method. The prompt library and Custom GPTs became assets we could actually reuse."
"The most useful part was workflow automation. Learners took their weekly reports, meeting recaps, and research tasks and reduced hours of repetitive effort."
"Responsible use was handled practically. The team finally understood what can be pasted, what must be masked, and how to verify output before sending it."
Questions L&D teams ask before signing.
No. AI will not fully replace instructional designers, but it will change how instructional design work is done. AI can help create outlines, storyboards, quizzes, scenarios, learning objectives, summaries, assessments, and draft course content faster. However, human instructional designers are still needed for learning strategy, learner analysis, instructional flow, pedagogy, content validation, engagement design, accessibility, evaluation, and business alignment.