Candidate — Chief Data & AI Officer, Generali Česká pojišťovna
#simple#fast#efficient
I'm finding elegant and fast ways to design and deliver innovations and solutions. My priority is to keep things simple and understandable and keep moving them forward.
Philosophy
#people first
not ai
People are needed to bring on the change. They need to be convinced, enabled, and motivated. Technology and AI are just enablers.
Track Record
Projects
Three engagements that shaped how I think about scale, architecture and data as a product.
4→13countries
Global Telco Client
Overall Architecture & Technical Integration Lead
Scaled the program from 4 to 13 countries, owning overall solution architecture end-to-end
Led technical integration with external vendors across markets
Personally responsible for the implementation rollout in Qatar
Enterprise scale · multi-market delivery
Data Mesh
Data Product Hub
Technical Architect
Designed the data asset model underpinning the mesh
Owned governance model for data products across domains
Drove implementation from architecture into production
Governance · asset modelling · data-as-a-product
Multi-Agent
Personal Agent Management
Founder & Architect
Built a harness running autonomous agents across multiple personal projects and roles
Manages context, memory and skills per agent, shared where it matters
Centralized MCP tool and credential management across the whole fleet
Personal project · agent orchestration
First 90 Days
The Plan
Not a rollout of AI everywhere — a golden path for the use cases that earn it, governed end-to-end.
01 · Listen
Get to know people
Questionnaires, 1:1s and research across the business to understand real needs — before proposing a single use case.
02 · Mobilize
Ambassador network
Build a team of ambassadors and send them across the company to surface needs and champion adoption from within.
03 · Define
The golden path
Standardize the pattern for proven use cases — one well-lit path, not a hundred one-off experiments.
04 · Govern
Govern every use case
One governance model, applied consistently — from idea to production, no exceptions.
Not everything needs AI
Part of the plan is saying no. Knowing — and stating clearly — where AI does not belong is as important as defining where it does.
Looking Ahead
Future
Questions I want a CDAIO role to help answer — not just for Generali, but for how the industry works.
01
Revenue per employee
AI broke the old limits here in tech — companies are starting to measure it seriously. Can the same be done in an insurance business?
02
Treat AI agents as people
Train them, enable them, give them feedback — the same discipline we already apply to developing people.
03
Who do you trust more?
Who will be more reliable — who will run a process or task end-to-end better: the person, or the agent?