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AI and processes

AI for Process Analysis

Generative AI as support for process analysis, documentation, reporting and organisational improvement, with clear rules of control.

Reference duration
16 hours
Structure
4 sections · 16 one-hour chapters
Approach
Applied, organisational, operational
Bring this course to your team

What people learn

  1. 01

    Understand what generative AI can and cannot do in a company.

  2. 02

    Use AI to describe, analyse and improve processes.

  3. 03

    Write working prompts for business functions.

  4. 04

    Support reporting, documentation and variance analysis.

  5. 05

    Set minimum rules for AI governance and control.

How it runs

  1. 01 · 4 hGenerative AI in the company
  2. 02 · 4 hProcess analysis and mapping
  3. 03 · 4 hAI for control, reporting and documents
  4. 04 · 4 hWorking prompts, governance and final case

Programme

4 sections, 16 hours.

Durations and programmes are the reference structure: content, level, examples and format are agreed with each company.

  1. 014 h

    Generative AI in the company

    1. What generative AI is and can doPrinciples, use cases and the difference between automation, assistance and decision.
    2. Opportunities for SMEsAdministration, control, sales, operations, HR, management and advisory work.
    3. Limits, errors and risksHallucinations, sensitive data, privacy, security, human validation.
    4. A working method with AITask, context, constraints, inputs, output format and review.

  2. 024 h

    Process analysis and mapping

    1. Describing a process with AIInputs, outputs, activities, actors, systems, documents and controls.
    2. Bottlenecks and inefficienciesRedundancy, idle time, recurring errors and manual steps.
    3. Operating procedures and checklistsProcedures, checklists, instructions and document standards.
    4. Lab: mapping a processA simulated administrative or operational process with structured output.

  3. 034 h

    AI for control, reporting and documents

    1. Commenting on management dataAssisted commentary on margins, variances, trends, anomalies and KPIs.
    2. Budget-versus-actual analysisReading variances and forming hypotheses about causes.
    3. Document summaries and classificationDocuments, minutes, procedures, contracts and reports.
    4. Communications and management outputsEmails, summary notes, reports, memos and presentations.

  4. 044 h

    Working prompts, governance and final case

    1. Prompts for business functionsAdministration, control, operations, sales, HR and management.
    2. A company prompt libraryReusable templates for recurring work, checks and analysis.
    3. AI governance in the companyPolicy, usable data, roles, controls, validation and traceability.
    4. Project work: a process with AIMap, find issues, propose improvements and summarise.

Let’s fit the course to your team’s work.

Durations and programmes are the reference structure: content, level, examples and format are agreed with each company.

Plan the course

How training runs

  1. 01Company coursesCommon ground for people who work with data and models.
  2. 02Solution trainingBy role, on the tools and models that were adopted.
  3. 03Everyday useRepeatable processes and independent users.