Work on a real priority.
Agree the problem, intended outcome and a practical action or experiment during the training. Establish what evidence will show progress.
AI Skills & Adoption / Development programme
AI Adoption Accelerator: From Use Case to Evidence
Build an internal group capable of disciplined AI experimentation while taking up to three selected use cases through controlled evaluation and sponsor decisions.
Duration12 weeks
Private cohortUp to 12 participants
Live onlineFrom £12,995
BookingDates by agreement
Training is the start.
Application is where it counts.
Every course combines live learning, a practical application tool and a one-hour follow-up to review what happened when you put it to work.
Use your course-specific tool.
Use the AI experiment and adoption evidence workbook to record your starting point, actions, results, obstacles and supporting evidence while applying the learning at work.
Bring the evidence back.
Join a 60-minute live cohort follow-up, normally 30 days after training. Review results with your facilitator, work through obstacles and agree what to change next. A 7- or 15-day review can be agreed where it better fits the application.
Your practical tool
AI experiment and adoption evidence workbook — a course application workbook supplied to participants for recording implementation and review evidence.
Preview the questions worth asking before you act. The delivery workbook is provided with the course.
How application and follow-up work
The organisation provides time, relevant permissions and an owner for the agreed action. Participants capture evidence in the tool before the review. Agilinks brings facilitated reflection and focused advisory support to help interpret results and decide the next step.
One 60-minute remote follow-up per delivered cohort is included. Where a workshop already includes a one-hour follow-up, this is the same session. For the 12-week programme, the review follows programme completion and is additional to its 36 live hours. Package support allowances of eight or 16 hours remain separate; this review does not reduce them.
The review date and evidence-sharing arrangements are agreed before booking. Share approved summaries or anonymised examples; the workbook stays within your organisation unless you choose to share it. The tool is a working template, not a hosted tracking platform. Implementation is carried out by your team; technical delivery and ongoing consultancy are separately scoped. Results are reviewed honestly, including where an approach did not work.
When this is useful.
AI tools or introductory training have been funded, but the organisation lacks evaluated applications and people able to support responsible adoption.
Who commissions this?
A business sponsor and L&D lead accountable for useful adoption and internal capability.
Who should attend?
Eight to twelve nominated employees, organised into up to three project groups, with process-owner support and a business sponsor.
Required background
Participants have strong process knowledge, basic AI familiarity, analytical judgement and manager sponsorship. Approved tools, protected time, suitable use cases and an approval route are required.
What participants will be able to do.
- Frame and evaluate a bounded workplace AI application.
- Use approved information and oversight practices, and recognise escalation points.
- Interpret experiment evidence without overstating benefits.
- Demonstrate a useful practice to colleagues and support responsible adoption.
What your organisation takes away.
- Up to three evaluated pilot evidence packs documenting the test, results, limitations and next decision.
- Documented AI-assisted workflows, evaluation scorecards and human oversight requirements.
- Reusable evaluation methods, peer-support job aids and individual capability assessments.
- Sponsor checkpoints and a final decision session recommending continue, adapt or stop for each project.
A structured application journey.
12 weeks: two 90-minute live sessions weekly (36 live hours), plus approximately one to two hours of weekly assignments. Up to 12 participants and three group projects.
Indicative sequence and timings. The final agenda is agreed around your organisational priorities.
01Week 1: Establish the baseline
Learning lab · 90 minutes
Champion responsibilities; AI capabilities and limitations; personal capability baseline.
Application clinic · 90 minutes
Frame business problems and form project groups.
Required output
Development goals and candidate problem statements.
02Week 2: Use AI responsibly
Learning lab · 90 minutes
Approved tools, information boundaries, reliability, bias, human oversight and escalation.
Application clinic · 90 minutes
Apply company rules and identify unresolved approvals.
Required output
Project boundaries and approval checklist.
03Week 3: Select the business problem
Learning lab · 90 minutes
Process mapping, beneficiaries, performance evidence and non-AI alternatives.
Application clinic · 90 minutes
Challenge shortlisted problems and select a bounded use case.
Required output
Selected use case, owner and initial rationale.
04Week 4: Design effective interactions
Learning lab · 90 minutes
Instructions, context, examples, constraints, structured outputs and iteration.
Application clinic · 90 minutes
Compare approaches using synthetic or approved examples.
Required output
Documented approach and example outputs.
05Week 5: Evaluate quality
Learning lab · 90 minutes
Criteria, test cases, reference material, error types and human review.
Application clinic · 90 minutes
Apply an evaluation rubric to sample outputs.
Required output
Evaluation rubric and initial test set.
06Week 6: Plan the experiment
Learning lab · 90 minutes
Hypothesis, baseline, measures, sample, effort, risks and stop criteria.
Application clinic · 90 minutes
Review pilot plans and approval readiness.
Required output
Sponsor-reviewed plan; approval or simulated alternative.
07Week 7: Run a controlled test
Learning lab · 90 minutes
Execution discipline, conditions, error handling and evidence trails.
Application clinic · 90 minutes
Review early results within the approved scope.
Required output
Experiment log and issue record.
08Week 8: Refine the workflow
Learning lab · 90 minutes
Compare variants, failure patterns, human checkpoints and exceptions.
Application clinic · 90 minutes
Justify revisions using evidence.
Required output
Revised workflow and comparison record.
09Week 9: Assess value and limitations
Learning lab · 90 minutes
Quality versus speed, effort shifted, review overhead and adoption constraints.
Application clinic · 90 minutes
Analyse findings and challenge benefit assumptions.
Required output
Interim findings and unresolved questions.
10Week 10: Support colleagues
Learning lab · 90 minutes
Demonstrations, peer support, resistance and escalation boundaries.
Application clinic · 90 minutes
Deliver a short peer demonstration and receive feedback.
Required output
Team job aid and assessed demonstration.
11Week 11: Prepare the adoption recommendation
Learning lab · 90 minutes
Continue/adapt/stop decisions, ownership, controls, costs and dependencies.
Application clinic · 90 minutes
Critique recommendations and draft presentations.
Required output
Draft adoption recommendation.
12Week 12: Demonstrate and review
Learning lab · 90 minutes
Present project evidence to the sponsor or nominated panel.
Application clinic · 90 minutes
Reassess capability and agree individual development actions.
Required output
Final evidence pack and capability assessment.
Connect the learning to work.
Assess problem definition, responsible use, workflow quality, experiment evidence, peer demonstration and decision rationale. Missing approval or suitable data triggers a simulated case, clearly identified in the completion record.
Pre-work and preparation
Sponsor scoping, participant capability baseline, tool-access check, candidate problems, relevant policy briefing and project-group allocation.
What we each contribute
The company provides sponsor checkpoints, process owners, approved tools and protected time. Participants maintain evidence and complete assignments. Agilinks delivers shared learning, group clinics and bounded project feedback. The scope is up to three group projects, not twelve separate pilots.
A clear agreement before booking.
Starting price covers one private cohort, 36 live hours, shared teaching, group application clinics, agreed sponsor checkpoints and bounded feedback across up to three group projects. Feedback arrangements are defined in the proposal. Integrations, production deployment, extensive individual consulting and additional projects are separately priced. No successful implementation or financial saving is guaranteed.
Separately priced. Not included in annual short-course allowances; any substitution must be agreed explicitly in your proposal.
Private live-online delivery. On-site arrangements, travel, substantial customisation and paid software licences are quoted separately. Applicable tax treatment, dates, session hours, final agenda, output scope and payment and cancellation terms are confirmed in your written proposal.
Discuss your needs → agreed proposal → purchase order where required → invoice and bank transfer. No payment is taken on this website.
Questions from L&D and business teams.
Can this align with our capability framework?
Yes. Share your business priorities, role expectations and existing framework during scoping. We agree the learning objectives, relevant exercises and evaluation approach in the proposal.
Is certification included?
This is an independent Agilinks offering. No external accreditation, examination or SAFe certification is included or implied.
Can you tailor the agenda?
We agree relevant examples and priorities before booking. Substantial redesign, additional outputs or implementation support are separately scoped.