The Latest And “Greatest” AI Tool Could Introduce Risks You Haven’t Considered

The Latest And "Greatest" AI Tool Could Introduce Risks You Haven't Considered

I believe AI can provide value to any organization. It can reduce repetitive and mundane work, help employees analyze information, and improve how teams operate. But I also believe organizations need to be careful about implementing the "latest and greatest" AI tool before understanding what they are introducing into their environment.

A slick sales rep can provide a compelling demonstration of what a product can do. It rarely tells you everything you need to know about what that product can access, where your information goes, or how it affects your existing security controls.

Those questions need to be answered before implementation.

What concerns me most is how easily a seemingly minor productivity decision can become a much larger security and compliance issue. An employee connects a random AI assistant to their mailbox. A department uploads internal documents to generate a summary. A team enables a new feature within an application the organization already uses.

Each action may have a legitimate and good business purpose. Each can also change how organizational data is accessed, processed, retained, or shared.

The intentions may be good. The consequences still be significant.

Consider an AI assistant connected to a document repository. If employees already have broader access than they need, the assistant may make sensitive information much easier to find and consolidate. The tool does not necessarily have to bypass various permissions to create a problem. It may simply expose the practical consequences of permissions that were never properly reviewed.

That is why any AI implementation should include an assessment of the environment it will operate in, along with the product itself.

Organizations should understand what data the tool needs, which permissions it requires, and whether those permissions are appropriate for its intended purpose. They should also determine whether their existing monitoring, data loss prevention, and retention controls cover the new workflow. Assuming those protections carry over automatically can leave gaps that are difficult to recognize until something goes wrong. And it will.

The implications become more significant when an AI tool can take action.

There is a meaningful difference between a tool that drafts a response for someone to review and one that can send messages, modify records, or execute tasks. As that authority increases, so does the need for clear limits, approval requirements, and an audit trail.

An incorrect answer is a concern. An incorrect answer that triggers an action across connected systems can create a much larger problem.

Compliance deserves the same attention. A vendor's security certifications can be useful evidence during a review, but they do not establish that every use of its product is appropriate for your organization. The specific data, configuration, contractual terms, and business process still matter.

Before approving any tool, I would want clear answers to several questions:

• What information will it access, and does it need that information?
• Where is that information processed and stored?
• What are the terms for retention, deletion, and use of submitted data?
• Can we enforce appropriate identity and access controls?
• Can we monitor its activity and investigate an incident?
• Which actions require human approval?
• Who owns the implementation and its ongoing review?

These questions should be part of the purchasing and implementation process. Security, compliance, legal, and the business owner should be involved while there is still an opportunity to influence the decision.

At the same time, organizations need to give employees a practical path to approved AI use. If the review process is unclear or unnecessarily difficult, people may start using tools on their own. Actually they probably will. Clear guidance and approved options help employees get the benefits without having to guess what is acceptable.

My approach would be to start with a defined use case, evaluate the tool against that need, and run a limited pilot using appropriate data and permissions. Confirm that the controls work before expanding access. Revisit the assessment when features, integrations, or permissions change.

AI adoption is a technology decision with huge business consequences. Leadership should be able to explain both the value it expects and the risks it has agreed to accept.

Organizations should benefit from AI. And I also want them to understand what they are giving a tool access to before they turn it on. The productivity gains should be measurable, and the security and compliance implications should be understood well before the rollout.

@johnjrice | Linktree John is a seasoned IT & Cybersecurity expert with 25+ years of experience leading IT transformations. Skilled in…