Every promising innovation also carries its share of new risks. The Internet connected everyone, but also opened new avenues for scammers and spammers. Cloud software gave us infinite storage and new security vulnerabilities. The key is to recognize and manage risks while taking advantage of the benefits.

AI is the latest technology to offer amazing opportunities and dire challenges. Our latest guide, The CIO’s guide to reducing AI-related risk, can help you navigate this emerging landscape. Here’s a preview to get you started.

4 key AI risk vectors

AI tools—and particularly agentic workflows—come with a unique set of risks. Some are new spins on old concerns, while some are fresh new problems. 

1. Security vulnerabilities

AI agents can execute workflows across multiple applications. The fine details of how they accomplish tasks can be opaque, making them vulnerable to bad actors. An agent with access to personally identifiable information (PII) could be duped into exposing it, for example. Or it could grant administrative privileges to someone who shouldn’t have them.

Think of the knowledge that your employees have—all the training they’ve been through, and the security protocols they follow. Even with all these precautions on board, humans still slip up. It would be naïve to think AI would be immune to these kinds of errors.

2. Compliance failures

Even without a scammer pulling the strings, AI agents could introduce compliance issues. They might mishandle personally identifiable information, for example, pulling data from a compliant, secured source to a database not intended for sensitive information. Or an agent could skip a crucial step for a particular compliance requirement, like speeding past required documentation or failing to retain critical data.

3. “Shadow AI”

Shadow IT has been causing CIOs headaches for decades. When teams or individuals use unauthorized software, they can introduce security and compliance risks. At worst, shadow IT creates an entire ungoverned infrastructure that the IT team can’t see.

The same habits that drive shadow IT are likely to cause shadow AI: Frustrated employees who find authorized workflows too inconvenient will bring their own AI tools to work. Combine unauthorized software with autonomous agents, and you compound the risk.

4. Software sprawl and experience erosion

As your business adopts more and more AI tools, it gets harder for employees to use them all optimally. Employees get frustrated trying to maximize effectiveness when tools have overlapping functionality or unclear paths to value. Ironically, the tools you purchase to boost productivity can end up introducing inefficiency and torpedoing morale.

What these risks have in common

These four AI risk vectors have diverse origins and modes of attack, but they’re all symptoms of a lack of visibility and transparency for the IT team. To minimize the risk, CIOs need to know:

  • How AI tools and agents are performing 
  • How employees are interacting with them
  • Which tools and agents are driving ROI, and which can be consolidated

The CIO’s guide to reducing AI-related risk can help you build an AI program that minimizes the downfalls and sets up your organization for success in the agentic era.