AI for learning design: a hands-on course for in-house L&D teams

Why attend this course?

Design better, not just faster

Move beyond AI as a content generator. Use it to improve the quality of your learning design decisions from the start.

Build repeatable workflows

Leave with a team-ready AI workflow covering every stage of the development lifecycle, not isolated prompts.

Stay in control

Learn the Human-in-the-Loop architecture that keeps professional judgement at the centre of AI-assisted design.

Work with real tools

Hands-on practice with general-purpose LLMs and specialist learning production tools.

Stay tool-agnostic

Principles that work regardless of which LLM or authoring platform your organisation uses, now or in future.

A resource pack you can use

Delegates will get a resource pack that includes:

• An eval prompt template
• A reusable prompt structure you can adapt to any content type
• A rubric starter kit
  • Pre-built rubric criteria for the three most common L&D content types
• A one-page eval plan

Built for your team

Private sessions for your organisation only, with content and examples tailored to your sector and context.

Topics covered

Note: this outline is subject to change based on participant needs and context.

AI foundations for L&D practitioners

Reframing AI in the context of corporate learning – what it can and cannot do, how to evaluate tools critically, and how to build the internal case for adoption.

• How LLMs work – what L&D practitioners actually need to know
• The landscape of AI tools relevant to corporate L&D
• Common failure modes: where AI produces plausible but poor learning design
• Introduction to Human-in-the-Loop architecture
• Having the AI conversation with stakeholders and senior leaders

Needs analysis and learning design with AI

Using AI to interrogate briefs, identify performance gaps, write learning objectives, and build course architecture – before a single piece of content is produced.

• Turning a vague stakeholder brief into a structured needs analysis
• AI-assisted discovery question generation and SME interview preparation
• Writing and stress-testing learning objectives with AI
• Generating and refining course structures and module outlines
• Building a design rationale document for stakeholder sign-off

Content development: advanced workflow automation

The hands-on production core. Building AI-assisted workflows for the full range of corporate learning content – and knowing where human expertise must lead.

• Scripting and storyboarding with AI: prompting, editing, and quality control
• Scenario and case study development with AI assistance
• Facilitator guides, job aids, and performance support materials
• Automating repetitive development tasks: versioning, formatting, translation preparation
• Prompt engineering for L&D: a practical framework with ready-to-use templates

Specialist multimedia tooling

Using specialist AI tools for audio, video, image, and interactive content within a coherent production workflow.

• AI narration and voice: tools, use cases, and quality standards
• AI video and presenter tools for corporate learning contexts
• Image and graphic generation for learning materials
• Integration with common authoring tools
• Building a multimedia workflow that combines LLMs and specialist tools

Assessment and evaluation design with AI

Using AI to design assessments that actually measure learning – and evaluation frameworks that demonstrate impact to the business.

• Scenario-based and knowledge-check assessment design with AI
• Avoiding common AI assessment pitfalls (surface recall, lack of transfer)
• AI-assisted evaluation planning at Kirkpatrick levels 1–3
• Generating learner feedback surveys and post-training reinforcement content

Governance, quality control, and ethics

The frameworks and habits that keep AI-assisted learning design trustworthy, compliant, and instructionally sound.

• Reviewing AI-generated content: a practical QA checklist for L&D
• Data privacy, IP, and confidentiality in AI-assisted L&D workflows
• Bias, accuracy, and hallucination: what to watch for and how to catch it
• Building internal AI usage guidelines your team will actually follow
• Communicating AI use transparently to learners and stakeholders
• Using AI evals for courseware Quality Assurance

Building your team’s AI workflow

Pulling the course together into a repeatable, team-wide approach – and managing the change that comes with it.

• Designing an end-to-end AI-assisted development process for your team
• Roles, responsibilities, and Human-in-the-Loop decision points
• Change management: bringing sceptical colleagues and risk-averse stakeholders along
• Measuring time and quality impact – making the case internally
• Keeping up as the tools change: a system for staying current

Pricing

Corporate / in-house sessions

This course is available exclusively as a private session for in-house teams. Pricing is based on group size and any customisation required.

Private sessions include:

• A dedicated session for your organisation only
• Content and exercises tailored to your industry, tools, and learning context
• Use of your own internal scenarios and examples where appropriate
• Flexible scheduling to suit your team across time zones
• A participant workbook and prompt library to take away
• Optional follow-up consultation session

Contact us to discuss your requirements and receive a proposal.