Is AI Putting Your Business at Risk? 10 Things SMBs Need to Do Now

Your next data exposure could start with an employee trying to finish work faster.

A customer spreadsheet pasted into an unapproved AI tool. A meeting bot recording a confidential conversation. An AI agent given permission to read files, send emails, and change records before anyone checks what it can access.

The task may take seconds. Understanding where the information went—and what the tool did with it—can take much longer.

AI can save your team time. But who decides what it can see, what it can do, and when a person needs to step in?

AI security for small businesses starts with knowing which tools employees use, protecting sensitive data, and controlling what connected agents can do. These ten actions help SMBs reduce AI risks and manage compliance responsibilities, with a practical 30-day plan to get started.

Need help assigning security responsibilities or building a practical governance program? Explore Inception Security’s cybersecurity advisory services to discuss your priorities.

This guide focuses on U.S. SMBs adopting AI tools and agents, with additional considerations for regulated data and international operations. It provides security guidance; specific legal obligations depend on your business, location, and use case and should be confirmed with qualified counsel.

1. Find the AI tools your employees are already using

Ask each department which AI tools it uses, including personal accounts, browser extensions, meeting assistants, coding tools, and AI features inside existing business software. Explain that the goal is to establish a safe way to work so employees can report usage openly.

Create a simple inventory with one entry per use case:

• Tool, subscription tier, and business owner.

• Purpose and employees using it.

• Information entered, uploaded, recorded, or retrieved.

• Connected systems and read, write, or administrative permissions.

• Retention settings, contract review, and approval status.

For example, using an assistant to improve public marketing copy is a different approval decision from connecting the same assistant to payroll files.

Review available application, browser, identity, and expense records to supplement employee answers. Record visibility gaps: a discovery tool may miss personal accounts, unmanaged devices, or AI embedded in an otherwise approved service.

2. Tell employees exactly what they can share with AI

Give employees an approved tool list, clear data boundaries, and a named person who can answer questions. Make the approval path easy enough that employees can use it during real work.

The following is a suggested internal policy baseline, not a legal classification:

Removing a person's name does not necessarily make a document anonymous. Details such as dates, job titles, locations, and account information may still identify them.

Also define who can install AI extensions, invite meeting bots, connect applications, and publish AI-generated material. Train employees using examples from their own jobs.

3. Check what the vendor actually does with your data

A vendor's brand name is not enough to approve every product, subscription, feature, and integration it offers.

For each proposed workflow, document answers to these questions:

• Can prompts, files, outputs, or feedback be used to train or improve models?

• How long is information retained, including logs and backups? What does deletion cover?

• Who can access it, including subprocessors and support personnel?

• Where is it processed and stored?

• Are company-managed accounts, multifactor authentication, access revocation, and useful audit records available?

• What contracts cover the specific service, and how are incidents reported?

• Do web search, agents, connectors, or optional models introduce different terms or data flows?

“Not used for training” answers one question. It does not establish zero retention, authorize a disclosure, or prove that a workflow meets your obligations.

Record the actual settings and contract version you approved. Reassess when the vendor introduces material changes or your team connects another data source.

4. Fix file permissions before connecting AI

For Microsoft 365 organizations, examine SharePoint, Teams, OneDrive, guest access, and broad sharing groups before rolling out AI access to business content.

Microsoft documents that its commercial Copilot experience surfaces organizational content within the user's existing access permissions. That makes permission hygiene especially important: content that was broadly accessible but hard to find may become easier to discover. Microsoft also documents that prompts, responses, and Microsoft Graph data are not used to train foundation models, while agents and other optional capabilities require attention to their terms. Microsoft's data, privacy, and security documentation.

Start with payroll, HR, finance, customer records, and confidential projects. Ask each data owner who should have access, remove unnecessary permissions, and test access using a normal employee account.

Require company-managed identities and MFA where supported. Restrict who can grant application consent and connect new services. Apply suitable classification, sharing, retention, and data-loss controls, then test the actual workflows. Verify feature availability and licensing before relying on a control.

5. Limit what AI agents can do on their own

An assistant that drafts a response has a different risk profile from an agent that can send it, change a customer record, execute code, or approve a payment.

AI can also encounter malicious instructions inside an email, document, or website. This is called indirect prompt injection: external content attempts to redirect the system's behavior. OWASP describes risks including data disclosure and unauthorized actions, and recommends controls such as least privilege, validation, and human approval for sensitive operations. OWASP prompt injection guidance.

For a first agent deployment, we recommend:

• Start with read-only access to a narrowly defined set of information.

• Separate permission to read from permission to send, edit, delete, or spend.

• Enforce authorization in the connected application, not solely in the agent's instructions.

• Require approval for external messages, payments, destructive changes, and access changes.

• Show the reviewer the intended action, destination, and relevant data before approval.

• Set transaction and usage limits, keep action records, and test how to disable access quickly.

Before launch, test with synthetic information. Can one customer retrieve another customer's records? Can a hostile document trigger an unapproved action? Can a revoked user still reach the agent? Fix failures before connecting production data.

6. Check the rules that apply to your business

Begin with your existing responsibilities for the information and decisions involved. Then determine whether AI-specific requirements add to them.

Healthcare and HIPAA. If a covered entity or business associate uses a cloud provider to create, receive, maintain, or transmit electronic protected health information on its behalf, business associate requirements may apply. HHS explains that even an encrypted, “no-view” cloud service can be a business associate. Confirm that any required business associate agreement covers the exact AI service and use; also assess permissible disclosures, safeguards, and risk. A signed agreement does not complete that work. HHS cloud computing guidance.

Employment decisions. Existing federal employment discrimination laws still matter when AI is used to assess applicants or employees. Involve HR and counsel before using it to screen, rank, recommend, or make employment decisions. Evaluate accessibility and discriminatory effects rather than accepting a vendor's assurance alone. EEOC guidance on employment discrimination and AI.

Financial information, personal data, and customer contracts. Have your compliance owner identify applicable sector rules, state privacy requirements, contractual confidentiality restrictions, retention duties, and notice or consent requirements. Include meeting recording and transcription in this review. Document the authority to process and share data before enabling the workflow.

EU-related operations. Assess whether the EU AI Act applies to your role and activities. Its requirements vary by use case and role; the Commission describes phased obligations including AI literacy and transparency, with separate timelines for high-risk systems. Do not assume every small business has the same duties or that every requirement started on one date. Check the current official guidance when approving an EU-related deployment. European Commission AI Act guidance.

Frameworks and vendor assurances. NIST's AI Risk Management Framework is voluntary guidance for managing AI risks. It can help organize your program, but adopting a framework or collecting a vendor assessment does not establish legal compliance for your particular use. NIST AI Risk Management Framework.

Keep a short record for every sensitive use case: applicable requirements, reviewer, decision, controls, supporting evidence, and next review date.

7. Put a qualified person in charge of important outputs

Assign an accountable person to check important outputs against reliable source material before they affect a customer, employee, system, or financial decision.

Define what they must check. A marketing reviewer checks claims and publication rights. A developer checks generated code for correctness and security before release. A finance reviewer verifies payee details and authorization through established channels.

The reviewer must have enough expertise, information, and time to reject or correct the output. A routine click on “approve” is weak protection.

8. Train your team to spot risky AI requests

Use short examples from everyday work: a spreadsheet with customer details, a meeting that includes confidential information, or an assistant asking to connect an entire mailbox. Have employees practice choosing the approved tool, removing unnecessary information, and asking for help when the rules are unclear.

Teach employees to verify important AI outputs against the original source and to report unexpected requests for access or actions. Make the reporting route easy to find. Include new hires and repeat training when tools or approved uses change.

Keep a record of who completed the training and which scenarios they covered. A policy employees have never practiced is difficult to rely on.

9. Plan for the day something goes wrong

Add AI scenarios to your incident response process: a sensitive upload, an exposed conversation link, a compromised connector, or an agent taking an unexpected action.

Tell employees where to report problems promptly. Have IT or your security provider disable affected connections or sessions as appropriate, preserve available records, identify exposed information and recipients, and coordinate with the vendor and compliance owner. Rotate any exposed credentials.

Evaluate contractual and legal notification obligations based on the facts. Do not assume deleting a conversation removes every copy or resolves the incident. Protect investigation records too; prompts and logs may contain sensitive information.

10. Keep evidence that your safeguards actually work

Give the AI program a named owner and maintain a record of approved tools, uses, data sources, and permissions. Keep vendor reviews, configuration records, test results, training completion, and incident procedures together.

Set a recurring review and reassess whenever a tool gains a new feature, connector, data source, or business purpose. Revoke unused access and retest important restrictions. Track gaps with an owner and a deadline so findings turn into fixes.

You should be able to answer three questions: What AI are we using? What have we allowed it to access and do? How do we know those limits work?

A practical 30-day starting plan

This is a suggested implementation sequence, not a promise that every business can complete compliance in a month.

Give your team a safe way to use AI

Your employees should know which tools they can use, which information they can share, and which actions need approval. Your business should be able to explain those decisions and show that its controls work.

Start with one useful workflow, give it an owner, limit its access, and verify the result before expanding.

Need help assessing the Microsoft 365 environment your AI tools depend on? Start with Inception Security's free Microsoft 365 assessment to identify security gaps and prioritize improvements. AI-specific workflow and legal compliance reviews should be scoped separately.