ISO 42001 Isn't Just for Tech Companies

When most executives hear "AI management system," they picture a San Francisco startup or a cloud software giant. After more than eight years helping 200+ organizations navigate complex compliance frameworks, I can tell you that assumption is not only wrong — it's expensive.

ISO 42001:2023 is the international standard for artificial intelligence management systems, and it applies to any organization that develops, deploys, or uses AI — regardless of industry. That means a regional hospital network using AI-assisted diagnostics, a national bank running automated credit decisions, a logistics firm using route-optimization algorithms, and a law firm using AI contract review tools are all within scope. Every single one.

The misconception that ISO 42001 is "a tech thing" is the single most common error I see in non-tech sectors, and it consistently costs organizations time, money, and reputational risk. This article is my attempt to close that knowledge gap permanently.

What ISO 42001:2023 Actually Governs

Before we address what industries get wrong, it's important to establish what the standard actually covers.

ISO 42001:2023 is structured around a Plan-Do-Check-Act (PDCA) management system model — the same architecture used in ISO 9001 (quality), ISO 27001 (information security), and ISO 14001 (environment). If your organization has ever implemented any of these, you already have significant transferable knowledge.

The standard requires organizations to:

• Establish an AI policy and assign accountability at the leadership level (Clause 5)
• Identify and assess AI-related risks and impacts on people, processes, and society (Clause 6.1)
• Define objectives for responsible AI use and measure progress toward them (Clause 6.2)
• Manage AI system lifecycle from design through decommissioning (Clause 8)
• Conduct internal audits and management reviews (Clauses 9.2, 9.3)
• Implement corrective actions when the system underperforms (Clause 10)

Notice what's absent from that list: any requirement to build AI. ISO 42001 governs how you manage AI — the policies, controls, oversight mechanisms, and accountability structures surrounding your use of it. That distinction is everything for non-tech industries.

The Scale of AI Adoption Outside the Tech Sector

Let's anchor this in data, because the numbers are striking.

According to McKinsey's 2024 Global AI Survey, 72% of organizations reported using AI in at least one business function — up from 55% just one year prior. The sharpest growth was not in technology companies; it was in financial services, healthcare, manufacturing, and retail.

A 2023 Deloitte survey found that 68% of healthcare organizations were actively deploying AI tools for clinical decision support, administrative automation, or patient engagement. Yet fewer than 15% of those same organizations had a formal AI governance framework in place.

The World Economic Forum estimates that AI adoption in financial services will generate $1 trillion in additional value annually by 2030, driven largely by credit scoring, fraud detection, and algorithmic trading — all of which carry significant regulatory and ethical risk.

The gap between AI adoption and AI governance is widest precisely in the industries where AI errors carry the most human consequence: healthcare, finance, law, manufacturing, and infrastructure. ISO 42001 is the internationally recognized mechanism for closing that gap.

The 6 Most Common Mistakes Non-Tech Industries Make

Mistake 1: Assuming "We Don't Build AI, So This Doesn't Apply to Us"

This is the most pervasive misconception I encounter. Executives in healthcare, finance, legal, and manufacturing routinely tell me some version of: "We just use an AI vendor's tool — we didn't build anything."

ISO 42001 explicitly addresses this. The standard uses the term "AI system operator" — an organization that deploys or uses an AI system in products or services, even if a third party developed the underlying model. Clause 4.3, which defines the scope of the management system, makes clear that operators bear governance responsibility for the AI systems they put into use.

If your hospital licenses an AI radiology tool from a vendor and that tool produces a misdiagnosis, your organization owns the outcome risk. ISO 42001 requires you to have controls, oversight mechanisms, and documented accountability in place — regardless of who wrote the code.

Mistake 2: Treating AI Governance as an IT Problem

In non-tech organizations, there's a reflexive tendency to route anything with the word "AI" to the IT department. This is organizationally dangerous.

ISO 42001:2023 Clause 5.1 requires top management — not IT — to demonstrate leadership and commitment to the AI management system. AI governance decisions affect legal liability, human resources, clinical outcomes, financial risk, and brand reputation. These are enterprise-level concerns that require cross-functional ownership: legal, compliance, operations, HR, and the C-suite.

At Certify Consulting, one of the first things I do with non-tech clients is help them establish an AI Governance Committee with representation across these functions. The IT team is a stakeholder, not the owner.

Mistake 3: Conflating AI Compliance with Cybersecurity Compliance

Many organizations in regulated industries — particularly finance and healthcare — already carry heavy compliance burdens: HIPAA, SOC 2, PCI-DSS, GDPR. When ISO 42001 comes up, a common reaction is: "We're already compliant with everything. Surely this is covered."

It isn't. These frameworks address data security and privacy. ISO 42001 addresses something categorically different: the ethical use, fairness, transparency, and accountability of AI-driven decisions. A hospital can be fully HIPAA-compliant and simultaneously running an AI triage tool that systematically disadvantages certain demographic groups — with no framework in place to detect it.

ISO 42001's Annex A controls specifically address AI-specific concerns like bias and fairness (A.6.2), explainability of AI outputs (A.8.4), and human oversight of AI decisions (A.9.3). These have no meaningful equivalent in cybersecurity frameworks.

Mistake 4: Underestimating the Regulatory Tailwind

Non-tech industries often approach ISO 42001 as optional — a "nice to have" for companies that care about PR. That window is closing fast.

The EU AI Act, which entered into force in August 2024, imposes binding obligations on high-risk AI applications in healthcare, critical infrastructure, employment, and financial services. Many of the Act's conformity assessment requirements map directly to ISO 42001 controls.

In the United States, the Executive Order on Safe, Secure, and Trustworthy AI (October 2023) directed federal agencies to develop sector-specific AI governance guidance. Banking regulators, including the OCC and FDIC, have issued supervisory guidance on AI model risk management that aligns with ISO 42001 principles.

Organizations with a certified ISO 42001 AI management system will have a documented, auditable governance record that regulators in any jurisdiction can evaluate. That's not an abstract benefit — it's a tangible liability shield.

Mistake 5: Failing to Address AI Risks in the Supply Chain

Manufacturers, logistics companies, and retailers often deploy AI across complex supplier and vendor networks — without mapping those AI touchpoints as part of their risk picture.

ISO 42001 Clause 8.4 specifically addresses AI supply chain relationships, requiring organizations to understand and manage the risks introduced by AI systems embedded in the products and services they receive from third parties. A manufacturer using an AI-powered predictive maintenance platform from a vendor, for example, needs documented controls around that vendor's data practices, model updates, and failure modes.

This is new territory for most non-tech procurement and supply chain teams, and it frequently surfaces as a gap during readiness assessments.

Mistake 6: Skipping the AI Impact Assessment

ISO 42001 introduces the concept of an AI impact assessment (referenced in Clause 6.1.2 and elaborated in Annex B). This is a structured evaluation of the potential harms an AI system could cause to individuals, groups, or society — analogous to a Data Protection Impact Assessment (DPIA) under GDPR, but broader in scope.

Non-tech organizations frequently skip this step because they assume the vendor has already done it. In most cases, the vendor has not — or has done so only from their own narrow risk perspective. The deploying organization is responsible for assessing impact in their specific operational context.

A financial services firm deploying an AI credit-scoring model, for example, must assess whether that model produces disparate outcomes for protected classes of applicants — in their customer population, with their data. That assessment cannot be outsourced to the model vendor.

Industry-Specific Considerations at a Glance

What Implementing ISO 42001 Actually Looks Like in a Non-Tech Organization

The implementation path for a non-tech organization is more straightforward than most anticipate — particularly if you already operate under a management system framework.

Here's the typical engagement arc I walk non-tech clients through at Certify Consulting:

Phase 1: Gap Assessment (Weeks 1–4)

We map your current AI use cases — including shadow AI, vendor-embedded AI, and AI tools used by individual employees — against ISO 42001 requirements. Most organizations are surprised by how many AI touchpoints they have. One regional bank I worked with identified 23 discrete AI applications during this phase, when they had estimated roughly six.

Phase 2: AI Governance Structure (Weeks 4–8)

We help establish the governance architecture: AI policy, AI Governance Committee charter, roles and responsibilities (including the AI system owner role), and the AI risk register. This phase directly addresses clauses 4, 5, and 6 of the standard.

Phase 3: Controls Implementation (Weeks 8–20)

We work through Annex A controls relevant to your specific AI use cases. Not every control applies to every organization — ISO 42001 allows for a Statement of Applicability that documents which controls are in scope and why. This is where non-tech organizations often gain the most practical value: building human oversight mechanisms, explainability protocols, and bias monitoring processes into their operations.

Phase 4: Internal Audit and Management Review (Weeks 20–24)

Before certification, we conduct a full internal audit against the standard and facilitate a management review. At Certify Consulting, this phase also includes pre-audit coaching to prepare your team for the certification body's assessment.

Phase 5: Certification Audit

With proper preparation, certification audits are straightforward. Our clients maintain a 100% first-time audit pass rate — a track record I attribute entirely to thorough preparation and the discipline of treating this as a genuine management system, not a documentation exercise.

The Business Case Beyond Compliance

I want to be direct about something: compliance is rarely the most compelling reason to pursue ISO 42001 certification. It's the floor, not the ceiling.

The organizations I've seen get the most value from ISO 42001 are those that treat it as an operational excellence initiative. The standard forces you to inventory your AI use cases, assess their risks, assign clear accountability, and monitor their performance over time. For most non-tech organizations, that discipline alone surfaces costly inefficiencies and unmanaged risks that have nothing to do with regulatory exposure.

A manufacturing client, for example, discovered during their AI impact assessment that a vendor-supplied quality-control AI had been systematically misclassifying a particular product defect for 14 months — a finding that led directly to a process improvement worth approximately $2.3 million annually.

ISO 42001 certification also functions as a market differentiator. In competitive procurement processes, particularly in government contracting and enterprise B2B sales, a certified AI management system signals governance maturity that your competitors likely cannot match. As AI governance requirements proliferate in RFP language — and they are proliferating rapidly — certification becomes a qualifying criterion, not just a differentiator.

Frequently Asked Questions

Getting Started: Your Next Step

If you're leading a non-tech organization that uses AI in any capacity — and by now, virtually every organization does — the question is not whether ISO 42001 applies to you. It does. The question is how far behind your governance posture is relative to your AI exposure, and what it will take to close that gap before a regulator, a client, or a public incident closes it for you.

At Certify Consulting, we've guided healthcare systems, financial institutions, manufacturers, law firms, and professional services organizations through every phase of ISO 42001 implementation. We bring the same discipline to non-tech clients that we bring to the software companies everyone assumes are the "real" audience for this standard.

If you'd like to understand where your organization stands, explore our ISO 42001 readiness assessment services or contact us directly to speak with me personally about your situation.

The organizations that move first on AI governance will set the standard that everyone else is measured against. That's a position worth holding.

Last updated: 2026-03-21

Jared Clark, JD, MBA, PMP, CMQ-OE, CPGP, CFSQA, RAC is the Principal Consultant at Certify Consulting and has led ISO 42001, ISO 9001, ISO 27001, and regulatory compliance engagements for 200+ organizations across North America and Europe.