Our team went from using AI for basic emails to building their own workflows. The workshop was tailored to our industry and roles, not generic theory.
Build practical AI capability that lasts.
Hands-on workshops help employees use AI on real work. The Nudgeable AI Academy gives them practical workflows, clear explainers and weekly updates as the tools change.

Keep building AI capability.
Practical guides and AI updates your team can use after the workshop.
- Guides
- Real workflows
- Tool updates
Trusted by teams at


















Hands-on AI training built around real work.
Six tracks. A program usually draws on three or four of them, chosen after we see how the team works.
How GenAI Works
Models, context, hallucinations, research modes and why the quality of AI output changes.
AI for Everyday Work
Research, writing, meetings, presentations and workflows connected to participants’ roles.
Data, Dashboards and Design
Analyse files, identify insights, create charts and turn findings into clear visual outputs.
Workflow Automation
Connect steps, tools and information to reduce repetitive work and manual handovers.
Building AI Agents
Understand agent systems and build practical agents using no-code or coding tools.
Governance and Data Security
Protect company information, verify output and manage permissions, copyright and human review.
Every team ends up somewhere different.
The way we get there is the same.
Nothing here is a fixed curriculum. This is the sequence we run with every client, from a 40-person function to a leadership group of eight.
We look at your work
We meet your team lead and a few people who do the job. We check how much AI they already use, what you expect AI to change, and which chatbots and tools you are licensed for.
Your people learn by doing
The workshop runs on your live tasks, not on sample data. Everyone practises in the room, with help when something does not behave.
We come back every month
AI changes every month, so we do too. We share what is new and fix the real problems your team hit when they tried to automate their own work.
AI Academy keeps it going
Everyone keeps access after the program ends. The guides stay current as the tools change, so learning does not stop at the workshop.
Built across functions, levels and industries.






What clients say about the experience.
What surprised us was how practical it was. People were solving real work problems during the session itself. We saw adoption jump within weeks.
The workshop simplified complex concepts and showed practical tools that power everyday work, from prompt engineering through to problem solving.

AI for Work, grounded in corporate reality.
Gaurav Patel designs practical AI training across industries and business functions. Each session is customized around how participants actually work, the tools they use and the outcomes they need.
The training draws on daily use of leading AI tools and first-hand experience building the Practice Lab, AI Coach and Actions Engine. This brings real product development and implementation knowledge into every session.
Short videos on AI changes that affect work.
New videos are added every week, focused on what changes for employees and organizations.
AI capability that continues after the workshop.
Practical guides and current AI updates help your team apply what they learned to everyday work.
Practise on real tasks
Apply with practical guides
Keep capability current
How GenAI Works
- How Generative AI Differs From Other AI
- What Are Tokens and Why Do They Matter?
- What Is an AI Context Window?
AI for Everyday Work
- Browser, Desktop or Phone: Where Should You Use AI?
- Chat vs Work: Which One Should You Use?
- How AI Projects Keep Your Work and Context Together
Data, Dashboards and Design
- Why AI Dashboards Are Harder to Share Than They Look
- What AI Can and Cannot Build Without Coding Knowledge
- How AI Generates Images and Video
Workflow Automation
Building AI Agents
Governance and Data Security
The Six Types of AI Agents and What You Can Actually Build?
A simpler way to understand is to think of AI agents as different levels of AI automation. As you move up, the AI gets more access to information, more ability to use tools and more freedom to decide what steps to take.
Read the full articleWhat should employees do better with AI?
Share the audience, tools available and workplace outcomes that matter. The program can be designed around those realities.



