AI Foundations

Summary

AI Foundations is a practical, instructor-led programme that closes the gap between using AI tools and understanding what they are actually doing. Across six modules, participants learn how generative AI works, how to prompt and verify it properly, how to apply it to everyday drafting, document and data work, how to handle the risk and governance questions it raises, what lies beyond simple chat tools, and how to lead adoption across a team or organisation. Modules 1, 2 and 4 form the core curriculum for every participant; Modules 3, 5 and 6 are selected to match the audience in the room.

Who Should Attend

This programme is for teams and individuals who are already using AI tools often inconsistently, without a shared standard for what is safe to enter or how to check what comes back. It suits:

• Staff who draft, summarise, report on, or handle documents and data as part of their day-to-day work
• Teams that need a common approach to prompting, verification and data handling before AI use becomes uneven or risky
• Managers and senior staff responsible for deciding what AI use cases to pursue, running a pilot, and building the case for wider adoption
• Organisations in regulated or public-sector settings, where classification of information and accountability for AI-assisted decisions carry particular weight

No prior technical background is required. The programme works well for mixed-role groups: operational staff and senior leaders each get material aimed at their part of the adoption question.

Course Description

AI Foundations is built around a simple diagnosis: most teams have adopted AI tools faster than they have understood them, and that gap is where the familiar failures come from confidential material pasted into a public tool, a confident wrong answer taken at face value, and a pilot that quietly goes nowhere. The programme addresses each in turn.

The day moves from concept to practice. Module 1 builds an accurate mental model of what generative AI is and why it fails the way it does. Module 2 turns that understanding into a repeatable method for prompting, iterating and verifying output. Module 3 applies the method to the real work participants do drafting, long documents, meetings, spreadsheets and reporting. Module 4 addresses the governance question that, for many organisations, determines whether any of this is approved for use at all: what may go into these tools, what may not, and who is accountable. Module 5 gives an accurate map of what sits beyond a chat window retrieval, tool use and agents so participants can evaluate vendor claims rather than take them on faith. Module 6 is aimed at leading adoption: choosing the right use cases, running a proper pilot, and building a 90-day roadmap.

Throughout, the exercises use participants’ own real work and documents (redacted where necessary) rather than generic examples, so what is learned is directly usable the following Monday.

Duration and Format

• Length: One full day (approximately 8 hours across six modules, including exercises and breaks)
• Format: Instructor-led, delivered to a group. Modules 1, 4, 5 and 6 are conceptual and discussion-based; Modules 2 and 3 are hands-on and require a laptop with access to an approved AI tool
• Core vs. tailored content: Modules 1, 2 and 4 apply to every participant. Modules 3, 5 and 6 are selected to match the audience’s role for example, Module 6 is aimed primarily at senior participants responsible for adoption decisions
• Group exercises: A mix of individual work, paired discussion and small-group exercises, with a short plenary debrief after each

Pre-Requisite

There is no formal prerequisite. Participants should:

• Have used, or be about to start using, an AI chat tool in their work no technical or programming background is needed
• Bring a laptop for Modules 2 and 3, with access to an approved AI tool for hands-on exercises
• Bring examples of their own real work documents, notes, or tasks redacted of any confidential material, to use in the exercises

Course Outline

     01: AI Foundations  (~90 minutes)
     02: Working with AI: Prompting and Verification  (~90 minutes, hands-on)
     03: AI at Work: Practical Applications  (~90 minutes, hands-on)
     04: Risk, Governance and Data Handling  (~75 minutes)
     05: Beyond Chat: Agents, Tools and Automation  (~60 minutes)
     06: Leading AI Adoption  (~75 minutes)

What You Will Be Able to Do

By the end of the programme, participants will be able to:

• Explain in plain language what generative AI is, how it was trained, and why it produces confident but sometimes wrong answers
• Judge whether a given task plays to the strengths or weaknesses of an AI tool before delegating it
• Structure a prompt deliberately, using context, task, format and constraints, rather than typing a bare question
• Diagnose why an output missed the mark and correct it in the next turn instead of starting over
• Verify AI-generated output systematically numbers, names, citations, and anything quietly dropped
• Apply the method to real work: drafting and editing, summarising long documents, processing meeting recordings, using AI safely around spreadsheets, and turning figures into a narrative report
• Classify information by sensitivity and know what may and may not go into a given tool
• Apply the core governance principles: where accountability sits, how bias shows up, and what an acceptable use policy needs to state
• Distinguish retrieval, tool use and agents from ordinary chat, and evaluate vendor claims about them accurately
• Choose the right first use case, structure a 90-day pilot with a proper baseline, and build the case for the next step from evidence

You Leave With

• A personal sort of your own recent tasks against the capability line, identifying where AI genuinely helps your work
• A tested, four-part prompt structure, applied end to end to one of your own real tasks prompted, corrected and verified
• A completed piece of your own work a draft, a summary or a report produced using the method on real material
• A first draft of an acceptable use policy page for your own team
• Five durable takeaways: it is strongest when you supply the material and weakest when it must supply the facts; fluency is not accuracy; most disappointing results are a missing-context problem, not a capability problem; name the classification tier before you paste; and accountability always stays with the person, not the tool
• A personal commitment for Monday one thing to do differently, and one process to baseline for a future pilot
• Awareness of Envigs’ related follow-on programmes: Beyond Generative AI (for teams ready for agentic systems), AI for MIS and Executive Dashboards (for reporting functions), and Leading AI Adoption and Change Management (for senior groups)