Guide· Rumbo
An expert, independent voice where decisions are made.
AI assessment, strategy and governance to define ambition and priorities. We build decision-making capability: what to ask, which risks are real and which metrics matter.
From the Greek stratós–ágō, “to lead the army”, the art of the general: strategy is choosing the course before you accelerate.
Who it's for
Designed for those who make the strategic decisions
- Boards that need to oversee the AI strategy.
- CEOs looking for a trusted strategic partner on AI.
- Executive committees that need to align technology with business vision.
What we see
Why do AI strategies fail?
A technology strategy, not a business one
solution looking for a problem
It starts from “what do we do with AI?” or “what do we do with the data?” instead of “where does it create value?”. The tool goes looking for a problem to justify the purchase.
The master plan
A complex problem is treated as if it were merely complicated, and a closed three-year roadmap is designed. AI is a change of mindset. Technological acceleration forces design times to shrink.
Moving piece by piece, not as a system
Frankenstein adoption
A technology platform chosen by IT. Training chosen by HR. Business needs that find no answer. Individual tools or areas are optimized and the interactions ignored. Work stays in silos.
Handing the decision to the vendor
Whoever sells the platform ends up defining the strategy. The conflict of interest decides for you.
Governance that paralyses
death by committee
A committee is set up that blocks instead of giving speed with judgment. Governance is experienced as bureaucracy and avoided.
Deciding without measuring risk
Money is invested with no risk map and no investment criteria. When something goes wrong, there was no safety net.
How we develop it
What we draw on to develop Guide
Tap each point to see what it involves.
Maturity assessment
An AI maturity assessment across five dimensions, with a sector benchmark and a prioritized roadmap. An honest picture of the starting point: where the organization is, where its sector is, and where to begin.
AI strategy
Designing an AI roadmap aligned with the business strategy. Use cases prioritized by real impact, built into a strategy that combines capability development, a shared semantic layer, and technology and data foundations that let value scale over time. Iterative, incremental development.
Strategic guidance
An ongoing presence in the leadership team as an expert voice on AI: taking part in committees, reviewing technology decisions and translating between technical and strategic language.
AI advisory board
Setting up and facilitating an independent AI advisory board, with access to a network of experts to validate strategic and technical decisions from complementary perspectives.
Conscious governance
Designing the AI governance model: roles, responsibilities, oversight processes and regulatory compliance (AI Act, GDPR), with semi-automated mechanisms to monitor risks, traceability and controls continuously. Governance that enables, rather than paralyses.