One-day private workshop · HR, L&D and change leaders
AI Change Management for HR & L&D Leaders
Help employees move from anxiety or experimentation to safe, role-relevant use. Build the learning, communication, support and measurement plan that an AI rollout needs.
- Duration
- 1 day · 8 hours
- Audience
- HR, L&D, OD and change teams
- Focus
- Readiness, learning and adoption
- Output
- A 90-day workforce adoption plan
What is the AI Change Management course?
AI Change Management is an eight-hour private workshop for HR, L&D, organisational-development and change leaders. Participants assess workforce readiness, distinguish different sources of resistance, map role-specific capability needs, design learning and champion support, and choose adoption measures that go beyond logins or attendance. The working output is a 90-day workforce adoption plan for internal review.
Is this the right course for you or your team?
Who it is for
- HR directors and HR business partners
- Learning and development leaders
- Organisational-development and change professionals
- Transformation teams responsible for workforce adoption
Situations it fits
- Employees fear displacement or surveillance
- Training is generic rather than role-specific
- Tool access exists but safe usage is inconsistent
- Adoption reporting counts attendance without measuring capability or application
Prerequisites
- Experience in HR, L&D, OD or change work
- Basic awareness of the organisation’s AI initiative
- Participation from IT, risk or business owners improves the working sessions
When a different course fits better
This workshop focuses on people adoption. Choose AI Implementation for Teams for the broader operating model.
- AI Implementation for Teamsfor portfolio, governance, rollout and measurement across the organisation
- Generative AI Fundamentalsfor general employee or manager AI literacy
Why access and training attendance are not adoption
The workshop separates awareness, capability, behaviour and business application so each can be addressed deliberately.
“Resistance looks like one problem”
Fear, distrust, overload, role ambiguity and overconfidence need different responses.
What you practise
Segment the concern, affected role and support response instead of sending one message to everyone.
“Everyone gets the same course”
Generic literacy does not prepare people for their real tasks and risks.
What you practise
Map role-specific outcomes, approved tools, practice and manager reinforcement.
“Communication creates more anxiety”
Messages promise transformation without addressing job impact or boundaries.
What you practise
Write clear statements about purpose, expectations, prohibited use and escalation.
“Adoption equals logins”
Usage volume cannot show safe, capable or valuable application.
What you practise
Combine reach, capability, applied behaviour, quality and risk indicators.
What participants will be able to do
Practise the skills below through course exercises, then check the results and explain how you would apply them to your work.
Assess workforce readiness
Map affected roles, current capability, concerns, access and manager support.
Diagnose resistance
Distinguish fear, distrust, overload, inertia and overconfidence, then choose a relevant response.
Design role-based learning
Specify outcomes, practice, tools, checks and reinforcement for priority employee groups.
Plan communication
Create honest messages about purpose, boundaries, responsibility and where employees can get help.
Build a champion model
Define selection, enablement, office hours, escalation and recognition for local advocates.
Measure adoption responsibly
Use a balanced set of reach, capability, application, quality and risk signals.
Applied to each team’s real work
HR leadership
Role impact, policy communication, manager expectations and employee trust.
Learning & Development
Needs analysis, pathways, practice, assessment and reinforcement.
Change and OD
Stakeholder mapping, resistance response, champions and feedback loops.
Business and risk partners
Use-case boundaries, approved tools, escalation and evidence of application.
The workforce adoption system
Each capability becomes a section of the final 90-day plan.
Readiness and role impact
Core
Understand who is affected, what changes and what capability is missing.
Covers
- Stakeholders and roles
- Task and tool impact
- Capability and concern baseline
What to verify
Is the assessment based on role evidence rather than broad assumptions?
Learning and reinforcement
Core
Connect learning outcomes to approved workplace practice.
Covers
- Role pathways
- Practice and assessment
- Manager and champion reinforcement
What to verify
Can participants demonstrate the behaviour after training?
Adoption measurement
Core
Track reach, capability, application, quality and risk together.
Covers
- Baseline and target
- Leading and lagging indicators
- Feedback and review cadence
What to verify
Could a high usage number hide unsafe or low-quality behaviour?
1 day · 8 live hours
Detailed curriculum
3 modules, each pairing short instruction with guided practice. Sequence and examples can be adjusted after the training-needs discussion; the core outcomes stay the same.
Module 12.5 hours Readiness, role impact and resistance
- Stakeholder and role mapping
- Capability and concern baseline
- Resistance patterns and response choices
Practical activityAssess current barriers for priority employee groups.
Module 22.5 hours Role-based learning and support
- Outcome-based learning pathways
- Practice, assessment and manager reinforcement
- Champion selection and operating rhythm
Practical activityDesign a learning pathway for one role and a champion support model.
Module 33 hours Communication, measurement and action plan
- Trust-building communication and clear boundaries
- Adoption, capability, application and risk measures
- 90-day plan, owners and checkpoints
Practical activityPresent a workforce adoption plan for internal review.
Need the agenda built around your team’s work?
Share the roles attending and the tasks to improve. The proposal sets out the adapted agenda.
Exercises and practical outputs
The day alternates diagnosis, design and review around the organisation’s real adoption context.
How every module runs
Listen
Map roles, concerns and current behaviours.
Design
Create targeted learning, communication and support.
Measure
Choose indicators that show capability and responsible application.
Mobilise
Assign owners and a 90-day sequence.
Exercises use representative, non-sensitive examples. Outputs are produced during the workshop for practice and review; anything participants keep is their own working material.
Useful AI requires ownership, evidence and boundaries
Participants learn to treat risk and review as part of the workflow, not as a disclaimer added after a pilot is already live.
NIST AI RMF is used as a voluntary risk-management reference, not as legal advice or a substitute for the organisation’s legal, privacy, security and compliance review.
Define the use and owner
State the intended task, affected users, accountable owner and decisions the system may or may not influence.
Protect information
Use only approved data and accounts. Apply the organisation’s confidentiality, retention and access rules before experimentation.
Measure in context
Choose quality, risk and adoption measures that reflect the real task; document what is not or cannot yet be measured.
Review and improve
Monitor failures, user feedback and changed conditions, then update controls or stop the use case when necessary.
How the course is tailored and delivered
Private delivery is shaped around the organisation’s maturity, approved tools, decision rights, workforce roles and current initiatives.
From first conversation to evaluation
Clarify the decision
Agree what participants must decide, design or implement after the programme.
Map the current state
Review roles, tools, policies, data constraints and existing AI or automation activity.
Select the cases
Choose realistic examples that are useful without exposing restricted information.
Define the handover
Confirm the artefact, owner, review path and next checkpoint expected after training.
Delivery formats
Private leadership or functional cohort
Best for: One organisation aligning stakeholders around a shared plan
Delivered live online or onsite. Exercises use the organisation’s context, while sensitive details remain in approved environments.
Modular rollout
Best for: Programmes that need workshops, working sessions and follow-up checkpoints
The same curriculum can be spaced around internal reviews. Dates, facilitation, materials and support are confirmed in the proposal.
Delivery modes
Live online
Facilitated sessions with breakout work, shared artefacts and live review.
Onsite
Private corporate delivery at the client location, with the same structured exercises and review.
Discussion, practice and decisions—not a lecture marathon
Technovids training sessions in different group settings. The photographs do not attribute a particular client, course or outcome.
Photo 1 of 10: Hands-on session 
Photo 2 of 10: Group photo 
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Photo 4 of 10: Group photo 
Photo 5 of 10: Classroom session 
Photo 6 of 10: Group photo 
Photo 7 of 10: Computer-lab session 
Photo 8 of 10: Group photo 
Photo 9 of 10: Classroom session 
Photo 10 of 10: Group photo
For L&D and procurement teams
The published course parameters on one page. Final scope, dates and fees are confirmed in the written proposal.
Discuss your team’s requirements| Course | AI Change Management |
|---|---|
| Duration | One day · 8 live hours |
| Audience | HR, L&D, OD, change and transformation professionals |
| Prerequisite | No technical background required; current initiative context is useful |
| Recommended group | 10–25 participants; confirmed for each delivery |
| Output | Role pathway and 90-day workforce adoption plan for internal review |
| Delivery | Private live online or onsite |
Who may deliver this programme
Technovids assigns a trainer whose subject depth and facilitation experience fit the audience and agreed scope.
Pankaj Rana
Co-founder & Lead Instructor, Technovids Consulting
Pankaj is a co-founder and the lead instructor at Technovids Consulting. His programme work spans practical AI adoption, AI engineering, evaluation, responsible production AI, data analytics and corporate learning design, with an emphasis on hands-on exercises connected to workplace tasks.
Expertise:
- Practical AI adoption
- Prompting and evaluation
- Responsible AI
- Corporate learning design
Junaid Khateeb
AI & Machine Learning Trainer, Strategist and Consultant
Junaid is an AI and machine-learning trainer, strategist and consultant with more than 22 years of training experience. His work combines enterprise AI education, business-centred adoption, responsible AI practices and applied solution design, helping professional audiences connect AI concepts to real organisational needs.
M.E. in Computer Engineering, specialising in Artificial Intelligence · author of programming books on Python, Java and C++
Expertise:
- Enterprise AI and ML training
- AI strategy and adoption
- Responsible AI
- Applied AI solution design
Pradeep Varadarajan
Technical Trainer & Curriculum Architect
Pradeep is a technical trainer and curriculum architect with more than 20 years of experience across enterprise technology, cloud infrastructure and advanced AI systems. He designs practitioner-focused programmes, labs and assessments covering AI, LLM systems, Python and machine learning, translating complex technical subjects into structured learning experiences.
Bachelor of Engineering in Electrical Engineering · instructor-led, virtual and blended delivery
Expertise:
- AI and LLM systems
- Curriculum architecture
- Python and machine learning
- Hands-on lab design
The trainer for a specific delivery is confirmed with the schedule or written proposal.
Updated
Organisations we have trained, and participant perspectives
Permissioned feedback and published client relationships provide context on delivery. They do not guarantee a specific adoption or business result.
Organisations we have delivered training for
Practical training programmes delivered for learners, professionals and teams across AI, data, cloud, productivity and professional skills.
Participant experiences across workplace roles
What professionals found useful, practical and relevant to their day-to-day work.
- Gauraw DeshmukhData Engineer · Capgemini
Technovids AI training was very practical and well structured. The sessions helped me understand how AI concepts can be applied in real data engineering and business workflows, instead of only learning theory. The trainer explained the topics clearly with relevant examples, which made the learning experience valuable and easy to follow.
- PriyanshaSoftware Developer
The AI training from Technovids helped me gain a better understanding of Generative AI, prompt engineering, and practical AI use cases for software development. The course was clear, interactive, and focused on real-world applications. It gave me confidence to explore AI tools more effectively in my work.
- Sidda RajuData Engineer
Technovids delivered the AI training in a very practical and industry-relevant way. As a data engineer, I found the examples and hands-on discussions useful for understanding how AI can improve data workflows, automation, and decision-making. The sessions were well planned and easy to understand.
- Akshat KabraData Engineer
The AI training program by Technovids was insightful and professionally delivered. It covered important AI concepts in a simple and practical manner, with examples that connected well with data and analytics use cases. The sessions helped me build a stronger foundation in applying AI in real business scenarios.
- MangeshSoftware Engineer · Siemens
Technovids conducted the AI training in a very effective and engaging manner. The sessions were practical, easy to follow, and focused on how AI can be used in real software engineering and business workflows. It was a valuable program for understanding the current direction of AI adoption in the industry.
- ReshuSoftware Developer
Technovids AI training was a very useful learning experience. The course explained AI concepts in a practical way and showed how developers can use AI tools to improve productivity, problem-solving, and application development. The trainer's approach was simple, clear, and focused on industry use cases.
Common questions before planning this course
Answers about the published course. The written proposal records any agreed customisation, delivery details and commercials.
Can AI Change Management be customised for our organisation?
Yes. A private delivery can reflect your maturity, roles, approved tools, policy environment and priority use cases. The agreed agenda and outputs are documented in the proposal.
Can the programme be delivered onsite or live online?
Yes. Both modes are available for private cohorts. The location, dates, session pattern and participant count are confirmed in the proposal.
Are templates and completion certificates included?
The programme includes the working templates named in the agreed agenda and Technovids completion certificates for participants who meet the stated requirements. Templates are starting points and require internal review before operational use.
Is this suitable at the start of an AI initiative?
Yes. Early delivery helps establish a readiness baseline, role impacts, communication boundaries and learning plan before habits and resistance become entrenched.
Is this only for HR?
HR and L&D are the primary audience, but the working sessions improve when business, IT, security, risk or transformation partners contribute relevant context.
Does the workshop produce an AI policy?
It can identify workforce-facing policy requirements and communication needs. A legal or security policy remains subject to the organisation’s own qualified review and approval.
Turn a training requirement into a clear course proposal
Share the audience, team size, delivery preference and the work you want to improve. Technovids will scope the programme and confirm the details in a written proposal.