AI Drive

Turn AI ambitions into priorities, governance and implementation

From ambition to the adoption of AI, with safety and sound judgement

AI Drive is a consultancy service supported by its own framework and platform for the strategic acceleration and adoption of Artificial Intelligence.
It does not start with the question “where can we use AI?”, but rather “where does AI create real value, with what data, what risks, what architecture and what governance model?”. From there, it structures priorities and decisions so that the adoption of AI proceeds judiciously, rather than under technological pressure.

How AI Drive brings structure to AI decision-making

Structure the project

In logical and progressive stages

Supports the diagnosis

Digital, analytical and organisational maturity

Identifies and prioritises use cases

AI with a real-world business impact

Assesses and defines

Technical feasibility, architecture, data, security and ethics

Build a model

AI Governance and the company’s operational model

Develop a strategic roadmap

Innovation through the growing, sustainable and continuous adoption of AI

Supports cycles

Measurement, optimisation and continuous improvement

At the end of the project, the organisation is left with a clear set of deliverables: a maturity assessment, an inventory and prioritisation of use cases, an assessment of technical and organisational feasibility, a risk map, AI governance principles and an actionable adoption roadmap.

AI Drive acts as a unifying and controlling force, reducing fragmentation, isolated initiatives and over-reliance on suppliers or technology.

When does it make sense to go ahead with AI Drive

Adopting AI strategically

With a clear ambition to create value and avoid isolated pilot projects that have no impact

Responding to the reality of the advance of AI

Eliminating the existence of scattered initiatives lacking a common thread

Operating in regulated or sensitive environments

It is necessary to assess risk, transparency, data quality, human oversight, documentation, robustness, cybersecurity and compliance with the AI Act, without turning the adoption of AI into a purely legal exercise.

Structuring architecture and AI governance

With alignment across data, the cloud, security and processes, and a clear model for decision-making and accountability to enable scaling

Ensure that the business is fully aligned with technology

to boost the efficiency and effectiveness of the company’s value creation, with the involvement of senior management, operational units and technology

accelerating what matters

Decisions supported by AI Drive

Where and how to get started with AI

Rather than focusing solely on the technology, clarify the priorities, feasibility and impact of AI on the business, with clear priorities in place to ensure a measured approach.

Technology compliance

Anticipate regulatory risks and ensure the adoption of safe and ethical AI, with AI governance and compliance factored into the decision-making process.

Frequently Asked Questions

Is AI Drive an AI tool?

No. It is a consultancy service designed to help structure strategy, priorities, governance and the adoption of AI. It does not replace technological tools; it helps organisations decide where to apply AI, which operational model to use, which risks to manage and which initiatives should be prioritised.

Does AI Drive include AI implementation?

No, but it supports implementation. AI Drive focuses on decision-making and preparation for adoption, with responsible governance and a focus on value creation, whilst providing practical support for the implementation of AI.

Does AI Drive offer immediate automation?

No. This approach ensures AI governance and a thorough assessment of the feasibility of any automation before proceeding to implementation, thereby eliminating errors arising from automation carried out without an assessment of its impact, risk and return.

How do they manage ethical, regulatory and organisational risks?

AI Drive assesses these risks from the outset. It evaluates the impact, data quality, transparency, human oversight, security, robustness and necessary documentation, helping to determine which use cases can proceed, which require additional controls, and which should be reassessed before implementation.

Accelerate alignment between business and IT to reduce risk and turn decisions into action.

Assess maturity, prioritise use cases and define an actionable roadmap to scale AI in a sustainable and progressive manner.