Artificial Intelligence and Risk Management: How Businesses Can Embrace AI Safely

Artificial Intelligence (AI) is transforming the way businesses operate—from automating workflows to enhancing customer service. But while many companies are eager to explore its benefits, others remain cautious. A recent study by The Hartford found that nearly 50% of business leaders have concerns about AI—particularly around cybersecurity, job displacement, data privacy, and ethical implications.

At McKnight Insurance Services, we believe AI shouldn’t be feared—it should be managed. Like any emerging technology, AI comes with risks, but also tremendous potential. When implemented thoughtfully, AI can help reduce workplace injuries, improve decision-making, and even enhance cybersecurity protocols. The key is understanding the risks and putting the right safeguards in place.

AI: Risk or Opportunity?

The conversation around AI often centers on fear—fear of job loss, of data breaches, or of losing control over decision-making. But this isn’t the first time technology has disrupted traditional business models. The printing press, the steam engine, the internet—all were initially met with resistance. And yet, each ushered in new industries and more efficient ways of working.

AI has the potential to do the same, provided we manage its risks early.

For example, AI-powered tools can now detect fraudulent activity or unusual system behavior in real time—flagging issues faster than any human. But to fully realize these benefits, companies need clear cybersecurity strategies, updated insurance policies, and a workforce that’s trained to collaborate with smart technology.

Four Key Steps to Manage AI Risks Effectively

If your business is exploring or currently using AI, consider these four essential steps to reduce risk and drive long-term success:

1. Build a Cross-Functional AI Risk Team

AI risk management requires a diverse team—not just IT and developers. Bring in legal experts, compliance officers, data scientists, risk managers, and insurance professionals. This group can evaluate system design, test for bias, and put in place controls that align with both legal requirements and your company’s values.

A 2023 study by Deloitte highlights the importance of this approach, emphasizing that AI projects succeed more often when risk professionals are involved from day one.

2. Prioritize AI Testing and Data Quality

Just like software requires quality assurance, AI systems need continuous testing to ensure they operate safely. Bad data in = bad results out. Testing must include:

• Bias detection and correction
• Model performance monitoring
• Fail-safe protocols for system malfunctions

Companies should also run scenario planning to simulate “worst-case” AI failures—and know what to do if something goes wrong.

3. Understand Liability and Insurance Coverage

Introducing AI into operations—especially robotics or autonomous decision systems—creates new liability questions. Who’s responsible if an AI makes a mistake? The manufacturer? The end user?

Make sure your business insurance policy includes AI-related coverage. You may need endorsements or a separate cyber liability or technology errors & omissions (E&O) policy. For example, if an AI-powered warehouse robot injures an employee, the claim may fall under multiple policies depending on how the risk was defined and managed.

Let McKnight Insurance Services review your current coverage and help you close any gaps before they become claims.

4. Consider Human Impact

Even if AI reduces certain risks—like heavy lifting or exposure to hazardous environments—it may introduce new risks, like increased stress on employees monitoring AI systems or reduced morale from automation fears. Train your team to work with AI, not against it, and keep communication transparent as roles evolve.

AI in the Real World: A Balanced Approach

AI can be a powerful partner in risk mitigation. For example:

• Manufacturing firms use AI for predictive maintenance to avoid costly breakdowns.
• Construction companies use AI drones to assess jobsite safety.
• Medical offices leverage AI for secure patient data entry and faster diagnostics.

Each use case improves efficiency—but only when risk is carefully considered.

AI, Risk, and Your Insurance Strategy

The future of AI is happening now. Businesses that prepare early—by building smart teams, updating insurance, and implementing strong governance—will be best positioned to thrive.

At McKnight Insurance Services, we help business owners in Texas navigate evolving risks like AI liability, cyber exposure, and emerging tech disruptions. If you’re adding AI to your operations, let’s make sure your insurance strategy evolves too.