The intelligent club is not created by another tool.
It emerges when sporting development, availability, talent, experience and technology are connected through a shared decision logic.
The starting point
Many clubs already have data, specialist systems and experienced teams. Value comes from connecting, understanding and applying that information in everyday work. That decision is not made in a specialist unit but at executive level, where priorities, budgets and responsibilities come together.
The vision
An intelligent club does not work against existing expertise, it extends it. Medicine, athletic performance, analysis, talent development, scouting and sporting leadership keep their responsibility. Data and AI help to make patterns more visible, to recognise risks earlier and to make decisions easier to follow.
Possible fields
Decision architecture
Clear roles, data logic, priorities and processes instead of disconnected pilot projects.
Talent and transitions
Development profiles, individual pathways and a more structured transition between academy and first team.
Sporting development and availability
Load, development, prevention and return to play as a shared and responsibly used basis for decisions.
Responsible AI
Transparency, professional oversight, data protection and acceptance as the condition for lasting, sensible use.
How we work
OMG E-Commerce does not begin with a technical solution. The entry point is a potential analysis: which decisions matter, which data and roles already exist, and what is the most realistic first step?
The role is that of an external contributor who both advises and works alongside the team: where the direction is decided, and where it is put into practice day to day. Not a concept that belongs to no one after handover.
Experience
A football club and a regulated group have more in common than it first appears: highly specialised units with their own responsibility, sensitive personal data, and staff who will only use a new application if they trust it. That is where AI initiatives fail — not on the technology.
The experience comes from an environment in which AI is nothing experimental. Eight years of project work at Allianz, from 2018 until the mandate ended in 2026, in the Allianz AI Marketing Lab on automating content production and quality assurance and on testing GenAI-based assistance and review modules — inside a regulated group where every application needs an approval.
That includes the work rarely spoken about: identifying and assessing use cases, evaluating tools, defining workflows, writing guidelines and documentation, enabling business units through training and playbooks.
The football connection comes from practice: in 2018 an interim mandate at Goalplay, a goalkeeper training app, alongside a linguistics master’s thesis on football reporting.
What follows stands at the beginning of every project: a sensible use of AI does not start with the technology but with a concrete problem in the business unit — and with the question of whether the organisation will carry the solution in everyday work.
Develop a perspective that holds.
The starting point is the organisation, the strengths it already has and a concrete question about what comes next.