AI is being integrated into small and mid-sized businesses (SMBs) at a remarkable rate—often faster than governance can keep up. Indeed, 45% of respondents to a recent Propulsion survey  reported that employees are using these tools without formal approval. The widespread use of unauthorized AI tools suggests that employees see immediate value in AI and aren’t waiting for official policies to leverage its benefits. While this bottom-up adoption underscores the technology’s transformative potential, the accompanying lack of oversight raises potential risks—including data security vulnerabilities, compliance concerns, and inconsistent strategies.

Rather than restricting AI adoption, SMBs benefit from implementing structured AI usage policies that enable innovation while safeguarding compliance, security, and business goals. A well-crafted policy provides clarity for employees, ensuring AI tools are used responsibly and effectively. This guide walks SMB leaders through the process of moving from informal AI experimentation to a strategic, well-defined AI usage policy:

1. Assess current AI usage in your organization

Before drafting a formal AI usage policy, SMBs need to take stock of how AI is currently being used across teams. Employees often integrate AI tools into their workflows out of necessity—whether to uncover efficiency gains or find new ways to solve problems. Yet without a structured approach, this can lead to fragmented adoption, where different departments use disparate tools with varying levels of oversight.

An initial assessment helps business leaders understand not just what AI tools are in use but also how employees perceive and engage with them. Are teams experimenting with AI in ways that align with company goals? Are employees encountering AI roadblocks, such as unclear expectations or security concerns ? Recognizing these trends early allows SMBs to shape policies that encourage responsible AI use without stifling innovation.

Key questions to ask include:

• Which AI tools are in use? (both approved and unapproved applications)
• How are the tools being paid for? (Are employees expensing them, using corporate cards, or paying out of pocket?)
• Who is using them? (Are certain teams or individuals leveraging AI more than others?)
• What is AI being used for? (customer support, marketing automation, content creation, data analysis, etc.)
• Are there any risks? (data privacy concerns, security vulnerabilities, regulatory issues)
• What challenges are teams facing? (Are they unclear on use cases, struggling with implementation, or unsure how to get value from the tools?)

Beyond simply cataloging AI adoption, this assessment provides an opportunity to engage employees in the policy-setting process, and to lay the groundwork for broader implementation. Teams using AI day-to-day can offer valuable insights into what’s working, where they’re running into friction, and what support they’d need to adopt tools more effectively. This input helps ensure your AI usage policies reflect real-world applications—not just theoretical risks. It can also surface opportunities to support employees with resources like effective prompt techniques for generative AI , which boost both output quality and confidence.

Just as importantly, the assessment can surface organizational considerations for future expansion:

• What training or change management will be needed?
• Are there infrastructure gaps (e.g. data access, security layers)?
• What guardrails or governance frameworks should be in place before scaling up?

By taking stock of both current usage and future readiness, SMBs can develop policies that support thoughtful, responsible, and scalable AI adoption.

2. Define your organization’s AI objectives

After assessing how AI is currently used across teams, the next step is to define a clear vision for its role in the business. While understanding existing adoption patterns provides insight into employee needs, SMBs need to consider alignment with the company’s broader business strategy. Defining business objectives is an exciting process—it's where companies set their vision for growth, innovation, and impact. When viewed through this lens, AI governance isn’t about constraints; it’s about making that vision a reality. Rather than imposing limits, governance can serve as a powerful framework for driving efficiency, sparking innovation, and strengthening competitive advantage.

To create an AI usage policy that fuels growth, SMBs must first ask: What role should AI play in the business? AI’s potential is vast, with a growing number of high-impact use cases, but it must be applied strategically to deliver real impact.

Key questions to ask include:

• What overarching business challenges could AI help address? (reducing inefficiencies, improving decision-making, enhancing customer experience, unlocking new revenue opportunities, etc.)
• Where within the organization should AI be applied for the greatest impact? (personalizing customer interactions, optimizing inventory management, streamlining content creation, automating administrative tasks, etc.)
• How might AI help with key near-term business priorities? (e.g., yearly goals)
• How does AI align with the company’s long-term strategy? (Is it helping scale operations, improve decision-making, or enhance agility?)
• What would a successful outcome of AI adoption look like?

By defining AI objectives early, SMBs create a roadmap for responsible adoption—one that encourages employees to explore AI’s potential while ensuring every initiative contributes to measurable business outcomes. Instead of a scattered collection of tools, AI becomes a strategic asset that strengthens the business from within.

3. Establish clear AI usage policies

Once AI objectives are defined, businesses must translate them into clear, company-wide AI usage policies that provide clarity, consistency, and accountability. A structured AI usage policy ensures that AI is leveraged effectively while maintaining oversight and ethical integrity.

These guidelines should be easily accessible—whether housed in an employee handbook, company intranet, or a dedicated AI governance document—to ensure everyone understands how AI can and cannot be used.

Key elements to include in your AI usage policy:

• Approved AI tools: Clearly define which AI software and platforms employees are authorized to use. This prevents shadow AI adoption and ensures all AI tools meet company security and compliance standards.
• Appropriate AI applications: Specify which tasks AI can support and where its use is discouraged or restricted. For example, AI may be approved for automating data entry but restricted in areas like legal document review where human judgment is critical.
• Data restrictions: Clearly outline which types of data must not be entered into AI tools—such as confidential financial records, personally identifiable information (PII), or protected customer data—to prevent accidental exposure or compliance violations
• Data privacy and security measures: Define how sensitive company and customer data should be handled when using AI. Employees should know which data types are off-limits (e.g., financial records, PII, or regulated health data), and when they must use approved tools that offer enterprise-grade protections like encryption and role-based access. Choose vendors that comply with industry standards (e.g., GDPR, CCPA, HIPAA, SOC 2), and clearly communicate expectations around responsible data use. Regular audits or built-in logging features can help ensure compliance and flag potential misuse early.
• Ethical considerations: Address bias, fairness, and transparency in AI decision-making. Many AI providers incorporate safeguards to mitigate bias, but SMBs must still be vigilant in evaluating AI outputs—especially in areas like hiring or customer segmentation. Choose reputable vendors that offer transparency into their ethical commitments.
• Ownership and IP considerations: Specify who retains ownership of AI-generated content , including whether materials created with AI are treated as company property and how intellectual property rights are handled across different tools and use cases
• Human oversight requirements: Identify situations in which employees must review AI-generated content before implementation—particularly in high-stakes decision-making areas. For example, AI-generated financial forecasts might be useful for trend analysis, but final budget approvals should remain in human hands. Similarly, AI-generated customer responses should be reviewed in industries where accuracy and compliance are critical—such as healthcare or legal services.

By embedding AI usage policies directly into company culture, SMBs can ensure the technology is used responsibly while empowering employees to innovate with confidence. A well-structured policy provides the guardrails needed to explore AI’s benefits securely and strategically. (Of course, for policies to truly take hold, employees need the training, context, and support to put them into practice.)

4. Assign AI governance & accountability

Without clear and ongoing ownership, AI adoption can become fragmented over time. SMBs don’t need a complex governance structure—but they do need defined roles, monitoring processes, and a clear approval system for AI tools.

Key questions to ask include:

• ‍‍Who owns AI governance? AI oversight works best when it’s shared across relevant teams rather than falling on a single person. IT or security teams can handle privacy and security concerns, operations and leadership can ensure AI aligns with business goals, and AI champions can provide real-world feedback. In smaller businesses without dedicated compliance or IT teams, a COO, CTO, or department head can serve as the AI lead.
• How is AI usage monitored? Governance isn’t about micromanagement but about establishing feedback loops to ensure AI is used responsibly. This can include regular audits, employee feedback mechanisms, and performance reviews to assess AI’s impact on workflows and decision-making. Many AI tools come with built-in reporting features, making it easier to track AI interactions without adding extra overhead.
• Who approves new AI tools? Without a structured process, businesses risk employees using unapproved tools that may compromise security. SMBs can simplify AI adoption by requiring leadership, IT, or a governance lead to vet new AI tools for compliance, alignment with business goals, and cost-effectiveness.

Without clear accountability, AI governance can become reactive rather than strategic. By assigning ownership, monitoring AI use, and creating a structured approval process, SMBs ensure AI is not just being used, but being used effectively, securely, and in ways that drive measurable business value.

5. Regularly review & update AI policies

AI is evolving at a rapid pace, and an effective AI usage policy must evolve with it. New tools, regulations, and risks emerge constantly, meaning that what works today may be outdated tomorrow. Without periodic reviews, businesses risk policies becoming too rigid to support innovation or too vague to provide real guidance.

The responsibility for reviewing AI policies, staying informed on AI advancements, and evaluating new tools depends on who the company has designated as AI governance leads (as outlined above). In most SMBs, this role is best suited to IT or security teams, operations, or AI champions or power users.

To keep AI policies relevant, SMBs can:

• Establish a regular review cadence: AI policies should be reassessed quarterly, annually, or as needed, depending on how frequently AI is adopted or updated in the organization.
• Incorporate employee feedback: Employees working with AI daily can offer valuable insights into what’s working, where gaps exist, and how policies could be refined.
• Stay informed on AI advancements and regulations: AI-related laws and industry best practices are still developing. Governance leads (whether from IT, legal, or leadership) should track new compliance requirements (e.g., updates to GDPR, CCPA, or AI-specific legislation) and adjust policies accordingly.
• Evaluate new AI tools and use cases: As AI capabilities expand, governance teams should vet new tools before adoption and assess whether existing AI applications remain effective and compliant.

Rather than treating AI policies as static documents, SMBs benefit from embedding policy updates into company culture—whether through annual leadership reviews, dedicated AI governance meetings, or team-wide discussions on AI usage. By taking a proactive, iterative approach, businesses can ensure that AI remains an asset rather than a liability.

The impact of a well-defined AI usage policy

By proactively implementing an AI usage policy, SMB leaders can ensure AI is used responsibly, unlocking its full potential (and its highest ROI) while mitigating risks. A structured approach to AI governance enables businesses to harness AI’s transformative power while safeguarding against unintended consequences.

In today’s rapidly evolving digital world, AI has shifted from a novelty to a necessity, giving businesses that use it a decisive edge. With clear AI usage policies, ongoing oversight, and a culture of responsible adoption, business leaders can create a future-ready AI strategy that empowers employees, strengthens operations, and fuels long-term growth. As you move from policy to implementation, choosing the right technology partners can make all the difference—be sure to ask the right questions before committing to any AI solution .

Propulsion helps SMBs create AI strategies that are both powerful and responsible. From drafting your first usage policy to selecting the right tools and guardrails, we’ll guide you every step of the way. Let’s talk about your AI readiness.

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