From AI readiness to an effective organisation.
Many tools. Many pilots. No organisational logic — or still right at the start.
AI has arrived in most companies — and where it has, the impact falls short of expectations. Leaders know AI matters, but not which decisions are due now. HR sees the technology and is expected to guide the change, yet has not been brought along itself. Employees are curious, overwhelmed or sceptical — and nobody translates AI into concrete work.
The AI Maturity Model by SheFox
Companies are at different levels of maturity in their use of AI. The organisation as a whole, HR, business units and leadership develop at different speeds and on different levels. The AI Maturity Model by SheFox translates these differences into a measurable assessment of where you stand — creating a sound basis for decisions on priorities, investments and the next steps of the AI transformation.
HR becomes an architecture function.
Strategic AI sparring & workshops
Where do we stand, and what takes priority?
For whom: boards, managing directors, heads of division and HR.
Goal: anchor AI in HR and the organisation strategically and in line with your maturity level.
Focus: determining where you stand, assessing suitable AI technologies, prioritising fields of action and investments.
Outcome: a shared AI agenda: clear priorities, named responsibilities and an agreed roadmap for the next twelve months.
Maturity level: from level 1–2 to level 3.
AI-Ready Work Sprints
How do we get from decision to day-to-day work?
For whom: HR and business units, leaders with their teams.
Goal: priorities become practice. Existing processes become real AI-enabled use cases and integrated processes.
Focus: one process, one team, one result: reviewing the data situation and system landscape, selecting suitable tools, working on your own use case and embedding the new way of working in the team.
Outcome: a use case in productive use, measurable effects on time and quality, a blueprint for further processes.
Maturity level: from level 2 to level 3–4.
AI governance
How do we stay legally compliant and able to prove it?
For whom: managing directors, those responsible for HR, compliance, IT and data protection, employee representatives.
Goal: scale AI responsibly. The EU AI Act and GDPR as guard rails, not brakes.
Focus: inventorying applications and classifying risks — because HR systems often fall into the high-risk category. Clarifying roles, human oversight, transparency and bias control.
Outcome: a ready-to-use framework: use-case inventory, role model, AI policy and evidence logic — auditable for regulators, internal audit and customers.
Maturity level: from level 3 to level 4.
Leadership development
How do we lead when systems share in decisions?
For whom: leaders at all levels, leadership teams, talent pools.
Goal: realign leadership work and consciously retain responsibility for decisions.
Focus: a competency model for AI-native leadership, dealing with AI-supported decisions and their limits, leading change and resistance.
Outcome: a shared understanding of leadership, clear roles between people and systems — and leaders who carry their teams through the change.
Maturity level: relevant at every level, decisive from level 2.
AI training & enablement
How does everyone get there in the end?
For whom: employees, subject-matter experts, internal multipliers — AI natives.
Goal: build AI competence across the board — from a solid basic understanding to confident use and supporting internal teams.
Focus: role-based learning paths, prompting and tool skills, critical evaluation of AI results and building internal learning structures.
Outcome: demonstrable AI literacy within the meaning of Art. 4 EU AI Act — and people who actually use AI in their day-to-day work.
Maturity level: from level 1 to level 2.
Use-case design
Which use cases are really worth it?
For whom: process and project owners as well as HR and business units.
Goal: ideas become assessed use cases, ready for decision.
Focus: systematically identifying use cases, assessing them by impact, effort and risk, reviewing the data basis and feasibility.
Outcome: a prioritised use-case portfolio with benefit logic, risk classification and a clear implementation sequence — ready for board and budget decisions. Real delivery and implementation guaranteed.
Maturity level: from level 2 to level 3.
Certified AI manager. Lecturer at universities and universities of applied sciences.
Fluent across C-level, HR, transformation, legal, IT and business — this combination of HR depth, AI understanding and strategic delivery is rare.
Is this an IT project or an HR project?
Neither on its own. AI transformation is organisational work at the intersection of leadership, HR, processes and culture. IT provides the systems, HR shapes roles, skills and collaboration — and leadership decides on priorities and pace.
We already have tools and pilots. Isn't that enough?
Tools alone don't change how people work. Impact comes when roles, processes and decision-making space move with them. That is why I don't start with the technology, but with the use cases: assessed by impact, effort and risk — independent of tools, vendors and partnerships.
How quickly will we see results?
That depends on the process itself — realistically, within six weeks to the first robust result in one process. The internal effort stays manageable: kick-off, two guided work steps, wrap-up. In between, your team works at its own pace — I steer and secure the result.
What does the EU AI Act mean for us in practice?
It is relevant to the whole organisation — but in HR it is a baseline requirement, because systems used in recruiting, selection and performance evaluation often fall into the high-risk category. That brings requirements for risk management, transparency, human oversight and documentation — plus the AI literacy obligation under Art. 4 EU AI Act for everyone who uses AI.
Let's talk about your organisation.
Tell me what you're working on — and we'll find out where I can make the biggest difference.
Reply usually within 24 hours.
