AI · AIC-63

AI Use Case and Pilot Management

12 hours 2 days

Last updated 25 Sep 2026

AI Use Case and Pilot Management is a 12-hour training course by IT Genius Institute. Many organizations start AI projects with real enthusiasm, yet a good number get stuck in pilots that never finish, known as pilot purgatory, because the…

Training schedule

No public rounds are open right now — register your interest and we will contact you when the next round opens, or request an in-house session for your team.

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Many organizations start AI projects with real enthusiasm, yet a good number get stuck in pilots that never finish, known as pilot purgatory, because the problem was never clearly defined, the data was not there to support it, nobody owned the project, success metrics were not set up front, or there was no plan to scale after the pilot. The result is lost budget and lost executive confidence in AI at the same time. This course uses project-based learning. Learners work in groups on a problem from their own work or a case study prepared by the instructor, following the path of a

real AI project. Day one narrows a large pool of ideas down to the most valuable use case using CRISP-DM, stage-gates, the AI Use Case Canvas, a value vs feasibility matrix and a business case. Day two turns that use case into a pilot with a clear scope, KPIs, success criteria, a risk plan, Agile team roles and go / no-go / pivot decision criteria, and closes with a pitch for approval to a review panel. By the end, learners have a pilot charter and a 90-day plan ready to start. (2 days, 6 hours per day, 12 hours in total, Intermediate level.)

Objectives

Understand why AI projects fail to scale and structure the project lifecycle with CRISP-DM and stage-gates
Discover and define AI use cases that meet business needs systematically with the AI Use Case Canvas
Prioritize use cases with transparent, measurable criteria
Build a business case, estimate ROI and choose between build, buy or partner
Design a pilot with KPIs, success criteria and a 90-day execution plan
Assess data, technical, risk and governance readiness before the project starts
Run the pilot with Agile practices and make principled go / no-go / pivot decisions
Pitch the project for executive approval with a one-page summary and data storytelling

Who this course is for

AI champions and digital transformation (DX) working groups within organizations
Project leads, engineers and section heads who will own a use case
Department managers who approve or sponsor AI projects
IT teams who assess the technical feasibility of AI projects

Prerequisites

Completed AI Literacy for Everyone or understand basic AI concepts
Experience working in the processes of your own department and familiarity with frontline problems
Experience with improvement projects such as Kaizen, QCC or Six Sigma is a strong advantage
No AI technical skills or programming required

Curriculum

Course Details

A 2-day course, 6 hours per day (12 hours in total, 09:00-16:00), run as project-based learning with groups working on a problem from their own work or a case study prepared by the instructor. Intermediate level. No AI technical or programming skills are required. Learners take home a full template set from the AI Use Case Canvas, prioritization matrix and business case through to a pilot charter and a 90-day plan ready to start. For in-house delivery, an optional 1-day Demo Day can be added 4-6 weeks after the training to review pilot results against KPIs.

Day 1: Finding and Selecting the Right Use Case

Section 1: Why Many AI Projects Fail to Scale

Pilot purgatory: pilots that never finish and never scale
Main causes: unclear problems, unready data and no project owner
Often overlooked causes: no KPIs from the start and no change management
Lessons from leading organizations that have scaled AI projects successfully
The impact on budget and on executive confidence in AI

Section 2: The AI Project Lifecycle and Stage-gates

The stages of an AI project following CRISP-DM
Adapting CRISP-DM to the business context and the work of each department
Stage-gates from idea to pilot through to scale
What must be proven before passing each gate
Integrating the AI project lifecycle with the PDCA cycle and a continuous improvement culture

Section 3: Use Case Discovery Techniques

Pain Point Mapping: tracing process pain points from the user perspective
Process Walk: walking the actual process to see frontline problems
The 5 AI opportunity patterns: Predict, Detect, Generate, Optimize and Automate
Building on an AI Use Case Canvas created in an earlier course

Section 4: AI Use Case Canvas

Defining the problem and the users clearly before thinking about technology
Identifying the data required and the right AI approach
Identifying the expected value and the risks of the use case
Setting the metrics that prove the use case has succeeded

Section 5: Prioritizing with Value vs Feasibility

Placing use cases on a value vs feasibility matrix
A scoring model with transparent, measurable criteria
Criteria for business value and data readiness
Criteria for technical feasibility, risk and time to results

Section 6: Business Case, ROI and Build, Buy or Partner

Estimating costs and benefits, both financial and non-financial
Measuring the baseline before starting so results can be compared
Identifying the assumptions the pilot must prove
Criteria for choosing to build, buy or partner
Working with external service providers

Section 7: Day 1 Workshop: From Ideas to Top Use Case

A problem from your own work or a case study prepared by the instructor, worked in groups
Brainstorming at least 10 AI ideas in total
Selecting the best 3 ideas and writing each as an AI Use Case Canvas
Scoring with the prioritization matrix and selecting 1 use case per group
Workshop: prepare an initial business case for the selected use case to carry into Day 2

Day 2: Designing and Managing the Pilot

Section 8: Designing the Pilot

Setting a scope small enough to prove results within limited time
Writing hypotheses and success criteria that can be verified
Choosing KPIs linked to the baseline and the business case
Planning a 6-12 week pilot timeline and the resources required

Section 9: Data and Technical Readiness

Assessing data readiness and planning data preparation
Building an MVP to test the concept with users quickly
Designing for human review of results (human-in-the-loop)
A data and technical readiness checklist before the pilot starts

Section 10: AI Risk and Governance

An AI risk assessment checklist before the project starts
Approval steps and who must take part in the decision
Recording risks and controls in the pilot charter
Linking to the guidance in the AI Governance and Responsible AI for Organizations course

Section 11: Managing AI Projects with Agile

Working in sprints and adjusting the plan from what each round reveals
The roles of the sponsor and the product owner in an AI project
The roles of the data owner, AI champion and IT
Communicating progress to executives and stakeholders

Section 12: Measuring Results and Deciding to Scale

Go / no-go / pivot criteria at the end of the pilot
Planning the scale-up and the handover into production use
Basic MLOps concepts for maintaining AI systems in production
Managing change with users

Section 13: Pitching for Executive Approval

Structuring the pitch as a one-page summary
Data storytelling that shows executives the value and enables a decision
Using Copilot to help prepare documents and slides
Preparing answers on budget, risk and time to results

Section 14: Day 2 Workshop: Pilot Charter & Pitch

Building on the use case and business case selected on Day 1
Drafting the pilot charter: scope, hypotheses, KPIs, team and risks
Planning 90 days of execution with go / no-go / pivot decision points
Workshop: pitch to an in-class review panel for feedback and a quality review of the pilot charter

Frequently asked questions

Who is AI Use Case and Pilot Management for, and what background is needed?

Built for AI champions and digital transformation (DX) working groups within organizations · Project leads, engineers and section heads who will own a use case · Department managers who approve or sponsor AI projects Background you should have: Completed AI Literacy for Everyone or understand basic AI concepts · Experience working in the processes of your own department and familiarity with frontline problems Not sure the fit is right? Talk to our team on LINE @itgenius or call 02-570-8449.

How much does AI Use Case and Pilot Management cost and how long does it run?

THB 8,900 (currently THB 8,010 on promotion). The course runs 12 hours. The fee covers course materials, lunch and refreshments throughout. Pay by bank transfer to the company account, confirm it on our payment page, and we can issue the receipt or tax invoice in your company's name.

Do I get a certificate?

Yes. Everyone who completes the course receives a Certificate of Completion from IT Genius Institute. Each certificate carries its own number, and anyone holding that number can verify it online on our certificate page, so you can add it to your portfolio or pass it to HR as evidence of training.

Where does the training take place, and is there an online option?

You can attend onsite at IT Genius Institute or arrange to join online, and we also run it as a private in-house session for your team. Ask about dates and venues on LINE @itgenius or call 02-570-8449.

What if I fall behind or miss a session — can I retake it?

Yes. You may retake the same course free of charge in a later round, under the institute's conditions. Tell our team which course and round you attended, and we will check it and offer you the rounds that still have seats. Ask us on LINE @itgenius or call 02-570-8449.

How do I enrol, or request a quotation for my company?

Enrol online with the registration form on this page. You can register several attendees at once and enter your tax ID and billing address for the tax invoice. Or request a company quotation straight from the quote button. For anything else call 02-570-8449 or reach us on LINE @itgenius.