AI adoption is accelerating across organizations, and a growing number of them need clear, shared principles for governing it. VINT Technologies helps companies build an AI management system aligned with ISO/IEC 42001 that is auditable and works as part of day-to-day operations.
Only a handful of companies in Finland have completed this relatively new certification, among them the technology company Siili Solutions. This article describes how a certification project progresses with VINT's support, from kickoff to implementation, so that the outcome serves the organization's business in a tangible and transparent way.
Why and for whom is ISO 42001 relevant right now?
Published in 2023, ISO/IEC 42001 is the international standard for AI management systems. It belongs to the same family of management system standards as ISO 27001 for information security and ISO 9001 for quality management.
AI is moving from experimentation to a normal part of business operations, and tools are being adopted quickly, often on the initiative of individual employees. As adoption spreads, organizations need to establish shared principles and practices for tool usage, risk assessment, procurement and accountability.
At the same time, customers and other stakeholders increasingly expect organizations to demonstrate that they have their use of AI under control.
ISO 42001 certification is a sensible goal particularly when AI plays, or is expected to play, a central role in the business and in customer deliveries. The greatest benefits go to organizations with diverse internal processes, where AI can significantly improve the efficiency of knowledge work.
How an ISO 42001 certification project proceeds in practice
An ISO 42001 project typically moves through four phases: assessing the current state, defining the appropriate level of control, integrating the management system into the organization's own processes, and finally implementation.
1. Current-state assessment and choosing the path forward
When an organization first hears about ISO 42001 certification, the initial question is usually what achieving it requires. The project typically begins with a gap analysis that assesses whether the business is mature enough for certification and whether certification would bring the organization tangible value.
Full certification is not always the most sensible starting point. An organization can gain considerable value from the standard by adopting selected practices without pursuing certification. The initial assessment determines which path makes the most business sense for each organization, so that a heavy process is not built unnecessarily.
2. Defining the level of control through risk
Once the path has been chosen, the next step is to define an appropriate level of control. This phase requires the most deliberation, since not every AI use case should be treated in the same way.
Controls are scaled to risk: the higher the risk, the stronger the safeguards and the more detailed the procedures required. Risk management is built so that risks are identified, anticipated in advance, and covered by agreed procedures in case they materialize.
Publicly available and rapidly evolving AI tools call for particular attention. For these, the organization clarifies where data is stored, how it is encrypted and how confidential information is prevented from reaching external parties. It is equally important to ensure that data can be removed from external environments when necessary.
On the basis of these principles, the organization gets a clear evaluation model for new tools. When a tool is proposed, its risks are assessed according to the agreed model. Based on the assessment, the tool can be approved for production use, restricted to internal use or rejected. Once the procedure is documented and known to everyone, tool adoption takes place in a controlled manner.
3. Integrating governance into the organization's own processes
A management system does not work if it remains a separate, standalone system. For this reason, AI requirements are integrated into the organization's existing processes, and no parallel management system is built. Tailored in this way, the management system supports the actual business and stays part of daily work.
Existing ISO certifications, such as ISO 27001, offer a clear advantage at this stage. Risk management, responsibilities, internal audits, management reviews and continual improvement are already familiar practices that AI governance can build on. ISO 42001 complements them with AI-specific considerations such as impact assessment, transparency, human oversight and the AI system lifecycle.
A systematically built model gives employees consistent ways of working and speeds up the start of AI adoption. With a shared model, effective practices spread across the whole organization instead of each person developing their own in isolation.
4. Phased implementation and audit readiness
The project is best implemented in phases. An incremental approach limits financial risk and keeps costs under control. It also leaves room to adjust direction, since objectives become clearer as the project progresses and some areas may turn out to be unnecessary or to change.
Before the certification audit itself, internal audits verify that the management system works in practice. Certification is not the end point, as the results should continue to be put to active use so that the benefits of the management system are fully realized.
How do the benefits of the management system show in practice?
After an ISO 42001 certification project, responsibilities, risk assessment and working practices are clearer and more consistent, and the organization has better visibility into where and how AI is used.
In daily work, the benefit shows up as smoother customer projects. There are fewer surprises, because potential risks have been documented and prepared for in advance. If a deviation does occur, the response has already been agreed, so a solution does not have to be improvised under pressure.
The management system also clarifies the role of people. Final decision-making and accountability remain with the human expert, whose expertise becomes even more valuable as AI takes on routine tasks.
A successful ISO 42001 project requires expertise in management systems, information security, risk management, AI and technology at the same time. When the requirements of the standard are combined with the technology in use and the organization's existing processes, the result is both auditable and effective in everyday operations.
Want to find out which path suits your organization?
VINT helps assess your current state, choose the right approach and put AI governance into practice reliably and efficiently.