Highlights
- Understanding AI Features, Workflows & Agents
- Identifying and Prioritising Automation Opportunities
- Designing Effective AI-Powered Workflows
- Measuring AI Quality with Evals and Metrics
- Governance, Tool Selection and ROI Planning
- Developing a Real-World AI Implementation Proposal
Course Details
Module 1: Landscape Overview
- AI features, AI workflows and AI agents: the differences in practice
- What is realistic today versus over-promised
- Common patterns and reference architectures
- Hands-on: classify five real-world examples as feature, workflow or agent
Module 2: Process Discovery
- Criteria for automation candidates (volume, rules, risk, data quality)
- Interviewing techniques to surface hidden processes
- A canvas for scoring opportunities
- Hands-on: score three sample processes on the canvas in small groups
Module 3: Workflow Design
- Human-in-the-loop versus fully automated
- Mixing deterministic steps and AI steps
- Fallbacks, retries and graceful failure
- Hands-on: sketch a workflow design for a shared sample process
Module 4: Evals — How to Measure Quality
- What an eval is and why every AI system needs one
- Golden datasets, quality metrics, regressions
- A/B testing AI changes responsibly
- Hands-on: define an eval (metrics + small golden set) for the sample workflow from Module 3
Module 5: Tools, Governance and ROI
- Tooling landscape in brief: low-code (n8n, Make, Zapier, Power Automate), custom (LLM APIs), agent platforms
- Governance and risk: data privacy, audit, hallucinations, AI Act
- Cost and ROI: tokens, infra, dev time, maintenance
- Hands-on: do a rough ROI estimate on the sample workflow
Half Day 1 Wrap-Up: Preview of Day 2
- Recap of canvas, design and eval templates
- Final brief on what to bring tomorrow for your own workflow
- Optional: 1-on-1 check on the workflow you intend to bring
Half Day 2: Your Own Workflow (Guided Workshop)
Each participant works on one real workflow from their own organisation. The trainer rotates between participants and runs short group check-ins at each milestone. Templates from day 1 are reused so the learning transfers directly.
Module 6: Define and Score
- Write a one-line value statement for your workflow
- Score it on the day 1 canvas: volume, rules, risk, data quality, expected value
- Decide go / no-go / reduce scope
Module 7: Design
- Map current versus desired flow Mark human-in-the-loop checkpoints and fallbacks
- Identify the AI steps and what they need (context, data, tools)
Module 8: Eval Plan
- Define success in measurable terms
- Build a small golden set (5-10 cases) from your real data
- Choose metrics and a review cadence
Module 9: Tooling and Governance Choice
- Pick a tooling category that fits (low-code, custom, agent platform)
- Identify data privacy, audit and compliance considerations specific to your context
- Estimate cost and effort
Module 10: Roll-Out Proposal
- Produce a one-page proposal: problem, design, eval, tooling, cost, risks, next step
- Short pitch to the group, peer feedback
Half Day 2 Wrap-Up: Resources and Next Step
- What concrete step will you take next week
- Resources and reading list
- Q&A
Learning Outcomes
By the end of the course participants will be able to distinguish AI features, workflows and agents, identify suitable automation candidates in their own organisation, design a workflow with appropriate evals and governance, estimate realistic costs and ROI, and produce a one-page roll-out proposal for a real workflow from their own team.
Who should attend
This course is designed for managers, team leads, product owners, transformation leads and operations managers who need to evaluate, propose or oversee AI-driven process automation in their organisation.
Prerequisites
- General understanding of business processes in your own organisation
- No technical or coding background required
- A laptop with internet access
- For day 2: one concrete workflow from your own team or organisation that you would like to improve with AI (a short written description is enough, more guidance is provided ahead of day 1)
Feedback
4.8 out of 5 average
"Our tailored course provided a well rounded introduction and also covered some intermediate level topics that we needed to know. Clive gave us some best practice ideas and tips to take away. Fast paced but the instructor never lost any of the delegates"
Brian Leek, Data Analyst, May 2022
“JBI did a great job of customizing their syllabus to suit our business needs and also bringing our team up to speed on the current best practices. Our teams varied widely in terms of experience and the Instructor handled this particularly well - very impressive”
Brian F, Team Lead, RBS, Data Analysis Course, 20 April 2022