The World Economic Forum’s Future of Jobs Report 2025 expects 39% of workers’ core skills to change by 2030. Put another way, if your company had 100 employees, 59 would need some training by then. For engineering teams, much of that change is already here, and corporate AI training has to catch up. People are being asked to ship AI features, run models in production, and support AI tools inside the business, often without having been trained for any of it.
This guide is for engineering managers and L&D leads deciding how to close that gap. It covers how to work out who needs what, which formats suit which situations, and what it costs.
Corporate AI training: start with roles, not courses
The most common mistake in corporate AI training is sending everyone to the same course. A backend developer, a DevOps engineer, and a product manager need very different things from “AI training.” Map roles first, then choose programs.
| Role | What they need to be able to do | Program | Hours |
|---|---|---|---|
| Software and backend engineers building AI features | Build LLM apps, RAG pipelines, and agents | GenAI and Agentic AI BootCamp | 74 |
| DevOps, platform, and data engineers | Deploy, monitor, and retrain models and LLM apps | MLOps BootCamp | 60 |
| Solutions engineers, consultants, client-facing engineers | Build AI solutions and get them adopted at clients | AI Forward Deployed Engineer BootCamp | 90 |
| Solution and enterprise architects | Design AI systems and defend them on cost and security | GenAI & Agentic AI for Solution Architects | 16 |
| Product owners and product managers | Scope AI features and decide when they’re good enough | GenAI & Agentic AI for Product Owners/Managers | 12 |
| Engineering and business leaders | Choose use cases, fund them, and govern them | AI Transformation for Business Leaders | 16 |
| Anyone who needs the basics first | Understand how AI works and where it fits | The AI Blueprint | 4 |
The time commitment, side by side
Time away from delivery is usually the real constraint, more than budget. Here’s what each program asks of a participant.
Including self-paced pre-work where the program lists it
Source: AgileFever program pages, October 2026.
Bootcamps spread their live sessions over several weeks, so engineers can usually take them without stepping away from their projects. The role courses are short enough to schedule as a block.
A sensible rollout order
AgileFever’s corporate programs follow four stages: assess, upskill, analyze, and scale. In practice, that looks like this:
| Stage | What happens | Typical output |
|---|---|---|
| Assess | Map roles and current skills, and pick one or two real use cases | A short list of who needs which program |
| Upskill | Train a first group, ideally leaders and one delivery team together | People who can scope and build the first use case |
| Analyze | Look at what the first group shipped and where they got stuck | Evidence for what to change before the next group |
| Scale | Train further teams, adjusting the program based on what you learned | A repeatable path for new joiners |
Training leaders alongside the first delivery team matters more than it looks. When engineers come back with new skills but their managers can’t judge AI proposals, the work stalls at approval.
Choosing a format
| Format | Best when |
|---|---|
| Public live virtual cohorts | You’re sending a few people from different teams |
| Private corporate group | You’re training a whole team with a shared goal, and want exercises based on your own systems |
| Classroom | The team is in one location and you want a focused block of time |
| Self-paced | You need broad awareness across many people at low cost |
| Expert-guided | A team is working on a specific use case and needs hands-on help, not a course |
For a longer comparison of the first two, see in-house vs public cohort training.
What it costs
Current public cohort prices per participant are below. Group pricing for private cohorts is quoted separately, based on team size and how much the program is tailored.
| Program | US price | India price |
|---|---|---|
| AI FDE BootCamp | $2,200 | ₹1,25,000 |
| GenAI and Agentic AI BootCamp | $2,000 | ₹85,000 |
| MLOps BootCamp | $2,000 | ₹75,000 |
| AI Transformation for Business Leaders | $1,000 | ₹75,000 |
| GenAI & Agentic AI for Solution Architects | $450 | ₹25,000 |
| GenAI & Agentic AI for Product Owners/Managers | $450 | ₹25,000 |
Prices are current as of October 2026 and can change.
Additional discounts are available. Contact us to know more.
How to tell if it worked
Completion certificates tell you people attended. They don’t tell you the training paid off. Better measures:
- Did the team ship the use case they trained on, and how long did it take compared with before?
- Are AI proposals getting through architecture and security review faster?
- Has the team reduced its reliance on outside contractors for AI work?
- Can new joiners follow the same path without you redesigning it?
Agree on one or two of these before training starts. It’s much harder to measure afterward.
FAQ
Can the programs be adapted to our stack?
Private corporate groups can use exercises based on your systems and use cases. Public cohorts follow the standard syllabus.
What’s the minimum group size for a private cohort?
It depends on the program. Talk to the team via the corporate training page.
Should we start with leaders or engineers?
Both at once if you can. If you have to choose, start with a small group of leaders, so the engineers you train next have someone who can approve their work.
Source
Skills figures are from the World Economic Forum Future of Jobs Report 2025.
