More and more organizations are using AI not just as an experiment, but as an integral part of their processes. A large consulting firm recently became one of the first to officially obtain certification for its AI management system according to ISO 42001, the new international standard for responsible AI management. At first glance, this may seem far removed from your reality as a Flemish or European SME, but the message is clear: AI is maturing, and governance, ethics, and safety are becoming just as important as the technology itself.
In this blog, we'll briefly explore what's happening, why such an AI management system is relevant to your company, and how you can already take practical, down-to-earth steps toward responsible and sustainable AI deployment.
What exactly is going on
A large international consulting firm in India has achieved ISO 42001 certification from an independent certification body. ISO 42001 is a new international standard that provides guidelines for establishing, implementing, maintaining, and continuously improving an AI management system within organizations.
In concrete terms, this means that the organization has demonstrably set up processes to:
- To develop and deploy AI applications in a targeted and controlled manner;
- systematically manage risks related to data, security, ethics and quality;
- clearly define responsibilities and roles around AI;
- to continuously measure, evaluate and improve how AI is used.
Just as ISO standards for information security (such as ISO 27001) or quality (ISO 9001) are used internationally, ISO 42001 is positioning itself as the standard for structured AI management. This makes the topic very concrete: AI is no longer just a matter for the IT department, but a management issue.
Impact on people and society
The move to a formal AI management system demonstrates that AI is increasingly influencing decision-making, processes, and service delivery. This directly affects people: employees, customers, and citizens. When AI plays a role in credit assessment, personnel selection, logistics planning, or customer service, errors, bias, or unclear decision-making have real consequences.
On the positive side, a standard like ISO 42001 forces organizations to take this human impact seriously: who is affected by an AI decision, how transparent is that decision, where can someone turn if something goes wrong? At the same time, it implicitly warns against blind faith in technology: AI should be embedded in human checks, clear responsibilities, and understandable processes.
For your company, this means that AI must not only "work" in a technical sense, but also be sound in terms of fairness, explainability, and reliability. This mindset shift—people before technology—is precisely what society is increasingly demanding.
Ethical and sustainable considerations
ISO 42001 addresses several themes that are becoming increasingly important for European and Flemish companies:
- Ethics and honesty: Who decides which data is used, which decision rules are incorporated into a model, and what constitutes "acceptable" behavior from an AI system? An AI management system requires you to make this explicit, document it, and review it periodically. This prevents arbitrariness and increases the likelihood of fair outcomes.
- Transparency: Customers and employees deserve clarity: when does AI play a role, on what basis does it make decisions, and who can intervene? Transparent processes and clear documentation are a core component of structured AI management.
- Bias: Data is never completely neutral. A framework of standards obliges you to systematically consider biases in data and models, and to take appropriate measures: bias audits, diverse test sets, human review, and clear escalation paths.
- Safety: Not just cybersecurity, but also functional safety: what happens if a model fails, if the context changes, or if a system exhibits unexpected behavior? By developing scenarios and fallback mechanisms in advance, you make AI more robust.
- Energy consumption and the environment: Large AI models require significant computing power. A mature AI approach forces you to consider efficiency: smaller models where possible, reuse components, and consciously balance accuracy and power consumption. This reduces costs and environmental impact.
Responsible AI, therefore, goes beyond simply "not giving wrong answers." It encompasses the entire lifecycle: from concept and design to development, deployment, monitoring, and dismantling—always with people, the environment, and society in mind.
Safety and risk dimension
As AI becomes more prevalent in your processes, certain risks also increase. A systematic approach, as described in ISO 42001, helps you manage these risks instead of avoiding or ignoring them.
- Hacking and abuse: AI systems can be the target of targeted attacks (e.g., prompts that attempt to leak a model or manipulate training data). By implementing clear access controls, logging, and security guidelines for prompts and data, you can mitigate this risk.
- Data leaks and privacy: AI applications often work with sensitive data. Without agreements on data retention, anonymization, and access control, you run unnecessary risks. An AI management system integrates privacy-by-design with your AI processes, in line with GDPR.
- Operational risks: What if a model suddenly performs worse after a market change or seasonality? Monitoring, thresholds, fallback to human review, and clear incident procedures ensure you can make timely adjustments.
- Reputational risk: An AI decision perceived as unfair or discriminatory can cause reputational damage. Clear guidelines, end-user testing, and a complaints and redress mechanism are essential, not luxuries.
The bottom line: risks are inherent, but you can make them manageable with mature processes. No fear, no blind euphoria – just sensible risk management, just like you do for finance, quality, and information security.
What does this mean for your business?
As an SME, you don't need to be ISO 42001-certified overnight to work responsibly with AI. But the underlying principles are certainly relevant to your context in Belgium or Europe. Increasingly, customers, partners, and governments will want to know how you use AI, what risks you identify, and how you address them.
In practice, this means that you don't approach AI as a separate experiment, but as part of your business operations:
- You define clear goals: what problem should AI solve, and how do you measure whether it actually does so?
- You specify who is responsible for which aspect: data, models, legal review, security, user feedback.
- You think about ethics, privacy, sustainability and safety in advance, instead of only when an incident occurs.
This way, you can gradually build an internal AI framework that suits the scale of your organization. It doesn't have to be cumbersome or bureaucratic; it should be clear, workable, and people-focused.
3 concrete recommendations for Flemish and European SMEs
- 1. Start with a lightweight AI policy: Write down on one or two pages what you do and don't want to use AI for, what data can be used, and who is allowed to experiment. Don't write a legalese, but provide a clear framework.
- 2. Link AI to existing processes: Connect AI to what you already have: your GDPR processes, your information security, your quality management. This way, you avoid duplication of effort and AI doesn't remain a separate "toy" of one team.
- 3. Build a small governance team: Establish a multidisciplinary core team (e.g., someone from IT, business, HR, and legal/compliance) to review all AI initiatives. Their role: clear objectives, risk assessment, and monitoring the impact on people and the environment.
Conclusion: AI that works for people
The rise of standards like ISO 42001 demonstrates that AI is maturing. Not as a magic bullet, but as a technology that only truly adds value when properly embedded: ethically, securely, transparently, and with respect for people and the environment. That's good news. It means your company shouldn't compete on "most models" or "largest datasets," but on common sense, clarity, and responsibility.
At Canyon Clan, we help SMEs and organizations in Europe use AI and software for genuine process improvement: human-centric, sustainable, and without hype. If you'd like to explore what a down-to-earth AI framework could look like in your context—from initial policy to practical applications—feel free to contact us. Together, we build solutions that are not only smart, but also sensible.