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AI Governance for Mid-Market Companies: Practical, Proportionate, and Done in 60 Days
You don't have a compliance team, a DPO, or a dedicated AI function. You do have AI tools across your business and growing regulatory exposure. This is the realistic governance programme for companies with $10M-$200M revenue who need to get this right without the enterprise overhead.
Key Takeaways
Mid-market companies (broadly $10M-$200M revenue) need AI governance proportionate to their actual risk — which is real, but different from enterprise risk. The governance programme should take 60 days, not 18 months.
The three AI risks that matter most for mid-market companies: using AI with customer data in ways that breach privacy law, using AI in employment decisions that create discrimination liability, and being an unaware deployer of high-risk AI from a vendor platform.
Most mid-market AI exposure is in off-the-shelf tools — CRM with AI, HR platform with AI screening, accounting software with AI anomaly detection. Governing these is about vendor due diligence and appropriate use policies, not technical model governance.
The minimum viable governance programme: an AI tool inventory (one day), a written AI use policy (two days), updated vendor agreements (one week), and a privacy review of AI data flows (one to two weeks).
Mid-market companies in regulated sectors — financial services, healthcare, education — face higher obligations and should treat this guide as the floor, not the ceiling of their governance programme.
"Apenas para fins informativos. Este artigo não constitui aconselhamento jurídico, regulatório, financeiro ou profissional. Consulte um especialista qualificado para orientação específica."
The honest mid-market AI governance situation
Most AI governance guidance is written for large enterprises with dedicated compliance functions, legal teams, and the resources to implement comprehensive governance programmes. Mid-market companies — broadly, those with revenue between $10M and $200M — do not have these resources. They often do not have a dedicated compliance officer, a data protection officer, or an AI governance function. What they do have is a growing number of AI tools embedded in their operations, real regulatory exposure, and a genuine need to get this right without building an enterprise compliance infrastructure.
The good news is that proportionate AI governance for a mid-market company is achievable in 60 days with focused effort. The key is identifying the actual risks — which are real but specific — and addressing them directly rather than attempting to implement enterprise-grade governance frameworks designed for organisations ten times larger.
The three risks that actually matter
Privacy law is the first. If your AI tools process personal information about customers, employees, or other individuals, your obligations under the Privacy Act (Australia), GDPR (EU/UK), or equivalent legislation apply regardless of your company size. The most common mid-market privacy risk from AI is using customer data with commercial AI tools — feeding customer information into ChatGPT, using client data in AI-assisted analysis, or connecting CRM data to AI platforms — without understanding how those platforms handle that data. Most commercial AI platforms process and retain input data by default. A data breach from an AI platform using your customer data is your data breach.
Employment discrimination is the second. If your company uses AI in hiring — an applicant tracking system with AI screening, a job board that uses AI matching, or a background check service with algorithmic scoring — you are deploying AI in a context where anti-discrimination law applies with full force. Discriminatory AI hiring does not require intent — if the system produces disparate impacts on protected groups, it can be the basis of a discrimination claim regardless of what you intended.
Vendor AI liability is the third and most commonly missed. The enterprise software platforms most mid-market companies use — HR software, CRM, ERP, accounting software, marketing platforms — have added AI features in the last two years. You are deploying this AI as a deployer in the regulatory sense — you are responsible for the AI's outputs in your business context. The vendor's terms of service do not transfer that responsibility to them.
The 60-day governance programme
Week 1-2 (Discovery): List every software tool your company uses and identify which ones have AI features — including features that may have been added without announcement. For each tool with AI: what does the AI do, what data does it process, what decisions does it influence? This is your AI inventory. It will probably be longer than you expect.
Week 2-3 (Policy): Write a one-to-two page AI use policy that addresses what AI tools employees can use for work purposes, what information they can and cannot put into AI tools, who is responsible for approving new AI tools, and what to do if something goes wrong. This does not need to be legally sophisticated — it needs to be clear and practical.
Week 3-5 (Vendor review): For your three to five most significant AI tools, review the vendor's data processing terms. Key questions: does the vendor use your data to train their models, where is your data stored, what happens to your data if you terminate the relationship, and what security certifications does the vendor hold? Update your vendor agreements if the terms do not adequately protect your data.
Week 5-8 (Privacy and hiring review): Review your AI data flows against your privacy obligations. If you have a website that uses AI personalisation or analytics, does your privacy policy disclose this? If you use AI in hiring, has the AI been tested for demographic disparities? These reviews may identify specific issues that require remediation — address them before they become complaints or enforcement actions.