90% AI Adoption Across 13 R&D Teams
Heureka Group
AI & Automation, Strategy & Training
90%+ of R&D using AI tools
50% time savings on key tasks
13 teams onboarded in 3 months
Detail
Strategy & Training, AI & Automation
AI and OpenAPI Training for Enterprise IT
We helped banking IT teams align how they use AI, API design, and OpenAPI Specification.
Program Goals
01
Align Team Language
Bring analysts, developers, and testers to a shared baseline in AI, REST API, and OAS.
02
Connect AI to Practice
Show where AI can speed up daily work without losing control over output quality.
03
Split OAS by Role
Prepare separate tracks for API design, specification-driven development, and API testing.
04
Iterate from Feedback
Turn participant feedback into more practical exercises, materials, and workshop pacing.
Training participants - Česká spořitelna
Training participants
Česká spořitelna
“The training had a clear structure and the instructors explained both the theory and practical steps well. Some foundations were familiar, but we still took away concrete tips for OpenAPI, mocking, and tooling that we can bring back to the team. In the AI sessions, we appreciated that the content worked even for less experienced colleagues and used practical examples that make it easier to get started.”
Challenge
Česká spořitelna runs a large IT environment where analysts, developers, testers, and other specialist roles collaborate on digital products. Each team had a different level of AI experience, different tooling habits, and a different way of working with API documentation. That made cross-role collaboration and handover harder than it needed to be.
At the same time, teams needed to understand OpenAPI Specification not just as documentation, but as a practical source of truth for API design, implementation, testing, and validation.
Goal
The goal was to create a scalable training program for banking IT. The program needed to align AI fundamentals, strengthen practical OAS usage, and adapt the learning path to what each role actually handles in day-to-day work.
Our Solution
We split the program into several connected parts. AI training helped teams understand where AI could realistically speed up work with text, analysis, development artifacts, and automation. The OpenAPI part became a hands-on role-specific workshop track for analysts, developers, and testers.
In the OAS track, participants worked through concrete scenarios: designing an API from a blank page, reading and interpreting YAML/JSON specifications, working with oneOf, allOf, $ref, versioning and deprecated endpoints, importing specs into Postman or Insomnia, validating with Spectral, and testing against a mock service.
We treated feedback as product input. Participants valued the clear theory, prepared materials, and the ability to discuss concrete topics from the banking environment. The feedback also gave us clear iteration points: more guided hands-on walkthroughs, earlier prerequisite communication, prepared answers for less experienced participants, and a tighter bridge between theory and practice.
Results
The result was a repeatable training program for 270+ people across IT roles. The AI and OAS parts together covered 26 training runs, including three specialized OAS variants for analysts, developers, and testers.
The program did not stop at theory. Participants left with a practical model for using OAS as a shared contract between roles, applying AI to create and review work artifacts, and connecting API design, development, and testing more effectively.
Related Reading
- Improve API adoption with Open API Specification — why OAS works best when teams treat it as a shared contract, not just documentation.
- How to recognize quality AI training? — what to check before you choose an AI training partner.
- 90% AI Adoption Across 13 R&D Teams — how a broader AI adoption program combines training, ambassadors, and hands-on pilots.
