AI Governance: Why Small Businesses Can’t Afford to Ignore It
Introduction
Artificial intelligence (AI) is no longer just for tech giants. From chatbots handling customer service to AI-powered analytics optimizing operations like logistics, research, and product improvement, small businesses are increasingly integrating AI into their workflows. Yet, many overlook a critical piece of the puzzle: AI governance - the framework and processes that ensure AI is used responsibly, transparently, and in compliance with data protection laws.
AI legislation with international scope of application is already on the books in the European Union (EU). In due course, United States (US) based companies will be faced with domestic compliance obligations for AI systems. Now is the time to get ahead of this wave.
Why AI Governance Matters for Small Businesses
For small and medium-sized enterprises (e.g., companies with fewer than 100 employees and revenues under $100 million), it’s easy to assume AI governance is a concern reserved only for larger businesses. But failing to establish clear policies can lead to data privacy violations and regulatory fines, reputational damage, and biased or unreliable AI-driven decisions that undermine your bottom line. Even small businesses must develop a structured approach to managing AI risks while maximizing its benefits.
Key Considerations for Responsible AI Use
1. Data Protection and Privacy Compliance
As businesses increasingly adopt AI-driven tools, data privacy and compliance must remain top priorities. AI systems process vast amounts of personal data, making it essential for organizations to navigate the complex landscape of data protection laws. Whether operating domestically or internationally, businesses must ensure they meet legal requirements and safeguard sensitive information. Key considerations include:
Compliance with State and Local Regulations: In the US, businesses may need to adhere to laws like the California Consumer Privacy Act (CCPA) and New York City’s Bias Audit Law (Local Law 144).
Global Data Protection Requirements: Companies working internationally or engaging with EU vendors may want to embrace a streamlined compliance approach that satisfies the most comprehensive and widely reaching regulations. These likely include the General Data Protection Regulation (GDPR) and the EU AI Act (2024).
Establish Clear Data Protection Policies: Businesses should define strict guidelines for data collection, storage, and usage to protect customer and employee information while staying compliant.
2. Bias and Fairness
As artificial intelligence becomes more integrated into business operations, ensuring fairness and accountability is essential. AI systems are only as unbiased as the data they are trained on, and without careful oversight, they can unintentionally perpetuate discrimination. To mitigate these risks, businesses should take proactive steps, including:
Recognizing Bias in AI Models – AI can reinforce existing biases in training data, leading to unfair or discriminatory outcomes.
Auditing AI for Fairness – Regularly reviewing AI tools and avoiding sole reliance on automated decisions in critical areas like hiring and lending helps ensure ethical and equitable outcomes.
3. Transparency and Accountability
Transparency is key when integrating AI into business operations, ensuring that both employees and customers understand when they are engaging with AI-driven systems. To maintain ethical use and compliance, businesses should designate an AI governance lead - whether a dedicated role or an existing team member - to oversee AI implementations and mitigate potential risks.
Employees and customers should know when they are interacting with AI-driven systems.
Assign an internal AI governance lead (even if it’s just a team member responsible for oversight) to review AI implementations and ensure ethical use.
4. Security and Vendor Management
When relying on third-party AI tools and services, businesses must ensure vendors adhere to strong security, compliance, and data protection standards. Even small businesses should maintain appropriate contractual terms to ensure vendors satisfy regulatory standards and liability risks are limited. Moreover, implementing encryption and strict access controls further reduces security risks, safeguarding sensitive data from unauthorized access or breaches.
If using third-party AI tools, businesses must assess how vendors handle security, compliance, and data protection.
Implement strong encryption and strict identity and access management (IAM) controls to minimize security risks.
5. Leverage Free AI Governance Frameworks
Small businesses don’t need large budgets or dedicated specialists to establish responsible AI governance. Free resources like the NIST AI Risk Management Framework and Singapore’s open repository of AI governance tools provide Free structured guidance and practical solutions are available to help businesses manage AI risks effectively. These include the National Institute of Standards and Technology AI Risk Management Framework (NIST AI RMF) in the US and tools from the AI Verify Foundation in Singapore.
Small businesses can use free resources to develop AI governance strategies without hiring dedicated specialists.
The NIST AI Risk Management Framework provides structured guidance on managing AI risks with its Playbook and Core (Govern, Map, Measure, Manage).
Singapore’s open repository of AI governance tools offers practical resources for businesses looking to implement responsible AI practices.
Practical Steps for Small Businesses
1. Start with an AI policy
Establishing an AI governance program does not need to be complex. Starting with a simple one-page policy on AI use, data protection, and ethics can provide a strong foundation. Businesses can also integrate AI governance into existing risk and compliance frameworks, using it as an opportunity to strengthen overall data protection and accountability.
Even a simple one-page document outlining AI use, data protection, and ethical guidelines can set the foundation for responsible adoption.
Leverage existing governance, risk, and compliance strategies, programs, policies, or tools; incorporate AI governance into these existing practices, or use this as an opportunity to put more meat on the bones of those data protection and risk programs.
2. Educate Employees
Educating employees on AI best practices is essential to ensuring responsible and secure adoption. Training should focus on privacy, security, and ethical considerations, empowering staff to use AI tools effectively while minimizing risks.
Train staff on AI best practices, emphasizing privacy, security, and ethical concerns.
3. Continuous Monitoring
Regularly auditing AI systems, even on a small scale, helps businesses identify risks and ensure responsible use. By tracking AI-driven decisions and updating governance, risk, and compliance (GRC) policies as needed, organizations can adapt to evolving challenges and maintain transparency.
Based on the resources available, begin a reasonable audit practice, no matter how small.
Keep track of AI decisions and update GRC policies as needed.
Begin your AI Governance Journey Today
AI governance is not just a corporate buzzword - it is a business necessity, even for smaller companies. By proactively implementing basic AI policies, leveraging free governance frameworks, ensuring transparency, and safeguarding data, small businesses can use AI responsibly while minimizing legal and reputational risks. In today’s digital landscape, embracing AI governance isn’t an option. It is the key to sustainable, ethical growth.
Contact Us
If you want to learn more about how 1 Global Data Protection Advisors can help your business, please reach out for a free consultation. 1GDPA assists organizations that want to leverage their data and new technologies like AI systems in a responsible and legally compliant manner. We will be happy to help you create, update, and mature your data protection, privacy, and AI governance, risk, and compliance programs.
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