Services that make AI work. Responsible,
human-centred and applicable.

What this involves

To make truly good use of AI and experience its many benefits, it is important to first understand whether your organisation is sufficiently prepared for AI. This is called AI readiness and consists of generally applicable components, such as laws and regulations and AI literacy, as well as organisation-specific components, such as governance. Only with a good foundation and governance does implementing and integrating AI become successful in the short and long term.

What you can expect

• Tailored and well-substantiated support: joint alignment and periodic evaluations.
• Human-centred, holistic and inclusive approach by involving all relevant stakeholders and fostering sustainable collaboration.
• Greater self-reliance by involving you and relevant players in your organisation in the process and helping you become future-proof for AI.

My approach

1. Assess the current AI readiness
   • For example by conducting interviews and observing workflows.
   • For example by mapping the AI landscape in your organisation and the relevant stakeholders.
2. What is the desired situation & what is needed to get there
   • For example by defining goals, vision, scope and risks.
3. The roadmap towards the desired situation
   • For example realistic steps to grow towards the desired situation.
   • For example a checklist to monitor progress.

Deliverables

The deliverables depend on your wishes and needs in the field of AI. Together we align what the deliverables are and what they should meet. Examples of deliverables are:

• A roadmap with or without an implementation plan.
• An advisory report with implementation strategy or implementation plan.
• A roadmap with strategy and checklist to monitor progress.

What this involves

AI is complex technology and can provide highly valuable contributions for you and your organisation, but correct implementation is crucial. It is essential to involve all relevant stakeholders, such as users, directly in the process. This ensures efficient, effective and sustainable use and integration of AI in your organisation.

What you can expect

• Support at the point where your organisation currently is: from selecting the right AI tool(s) and running a pilot to scaling up, implementing and integrating.
• Human-centred, holistic and inclusive approach by involving all stakeholders and fostering sustainable collaboration.
• I act as a 'linking pin' between stakeholders to strengthen collaboration.
• The ultimate goal is to make you and your organisation more self-reliant for future AI implementations.

My approach

1. Map the current situation & required preparation (for example AI readiness).
2. Evaluate and validate the intended AI tool(s).
3. Set up the implementation plan, strategy and AI governance (for example compliance with privacy legislation, KPIs for evaluation and monitoring).
4. Execution, evaluation & next steps and integration possibilities.

Deliverables

The deliverables depend on your wishes and needs in the field of AI. Together we align what the deliverables are and what they should meet. Examples of deliverables are:

• Business case.
• Implementation plan and/or implementation strategy.
• AI governance proposal.

What this involves

Choosing the right AI tool(s) that fits the problem to be solved and suits your organisation can be difficult. There are many AI tools available on the market, each with their own goals, functions and characteristics, different vendors and ways of use. It is essential to have a holistic, appropriate and understandable evaluation, validation and monitoring framework that aligns with generally applicable aspects, such as laws and regulations, and with your organisation.

What you can expect

You receive an approach that helps not only to choose or use AI, but also to continuously assess and adjust it. This helps you keep control of performance, risks, compliance and organisational fit, with clear agreements on ownership and follow-up.

My approach

• Set up an evaluation framework (what do we measure, why and how often).
• Determine validation criteria (quality, reliability, safety and organisational fit).
• Make monitoring agreements (ownership, signals and escalation).
• Set up an improvement loop (feedback, updates and documentation).

Deliverables

The deliverables depend on your wishes and needs. Together we align what the deliverables are. Examples:

• Holistic and multidisciplinary evaluation and validation framework for AI (digital as a support system or as a protocol/work instruction).
• Advisory report.
• Business case.

What this involves

Scientifically researching AI in order to objectively measure its impact, effectiveness, functioning and applicability is becoming increasingly important. Good validity and reliability of the entire study is crucial for laws and regulations (such as the AI Act and EHDS) and can influence AI adoption.

My approach

The approach depends on the type of research (such as qualitative, quantitative or experimental), the scope and sector (such as healthcare, public or commercial), the type of AI and your needs. We discuss all these aspects in order to jointly align on a suitable way of working.

Areas where I can support you

• Research proposal: for example incorporating laws and regulations into data management & data processing, and selecting suitable AI training and testing methods with justification.
• Research preparation: for example informing the study population for data collection.
• Execution of the research: for example monitoring agreed data management and data policy.
• Promoting collaboration between direct and indirect stakeholders.
• Next steps after completion of the research: for example translating TRLs into concrete steps to bring a developed or researched AI system to the market.

What this involves

When you and your organisation use AI in your work, it is important to have the right knowledge and skills regarding AI. This is called AI literacy and has become a legal requirement under the AI Regulation. Setting up and carrying out a good and demonstrable AI literacy programme requires customisation and inclusiveness.

What you can expect

• You do not have to figure out all laws and regulations yourself or determine what does or does not apply to your organisation.
• A well-substantiated and demonstrable approach, aligned with the AI Regulation and your practice.
• An approach that fits your organisation, roles, workflows and desired AI literacy levels.

My approach

• Assess the current situation.
• Determine the required AI literacy levels.
• Design the training programme and self-assessments.
• Maintain and continue growing: a tailored monitoring strategy.

Deliverables

• Tailored AI literacy self-assessment (evaluation & monitoring).
• Slides and materials from training sessions.
• Tailored AI curriculum (programme, rationale and strategies).
• Tailored e-learning for different AI literacy levels (from beginner to expert).