Artificial intelligence is rapidly becoming part of everyday business operations. From drafting emails and summarizing reports to analyzing data and brainstorming ideas, AI-powered tools are now widely used across industries.
According to Microsoft’s 2025 AI Diffusion Report, one in six people worldwide now use generative AI tools. This means it’s highly likely that your employees, vendors, and even your customers are already interacting with AI in some way.
At the same time, cybercriminals are also leveraging these technologies. The cybersecurity firm CrowdStrike reported in its 2026 Global Threat Report that AI-enabled cyberattacks increased by nearly 90% in 2025, enabling attackers to automate phishing campaigns and accelerate attempts to access business systems.
As AI adoption expands, it’s important for business leaders to understand not just the benefits of these tools, but also how they actually work and where potential risks can arise.
How AI Processes Information Differently Than Humans
When a person reads a question, they interpret it using experience, context, and judgment.
AI systems operate very differently.
Instead of reading a sentence as a whole, AI breaks the text into small pieces called tokens—fragments of words, punctuation, and structure. The system then analyzes patterns from its training data to predict what information is most likely to answer the question.
For example, if you asked an AI tool:
“Review this vendor contract and identify any red flags.”
A human reviewer might consider:
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Your company’s prior relationship with the vendor
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Industry-specific risk exposures
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Negotiation dynamics
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Legal implications of certain contract terms
AI, however, does not inherently understand your business, risk tolerance, or regulatory environment unless that context is explicitly provided. It generates a response based on language patterns it has learned from large volumes of data.
The quality of the output often depends heavily on the quality and specificity of the prompt.
AI Predicts Patterns — It Doesn’t Truly “Understand”
Large language models (LLMs), such as generative AI tools, are trained on vast datasets of text. They learn how language is typically used and generate responses based on those patterns.
In practice, this means AI is:
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Predicting the most likely next word in a sequence
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Constructing responses one piece at a time
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Delivering answers extremely quickly, which can sometimes create the impression of deep expertise
While these tools can be extremely useful, they are not verifying facts in the same way a human expert would. Their responses still require careful review.
A Real-World Example: AI Drafting Business Policies
Consider a contractor using AI to draft a workplace safety policy.
The tool might generate a document that includes:
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Personal protective equipment guidance
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Chemical hazard awareness
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Incident reporting procedures
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Safety training recommendations
However, AI will not automatically know:
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Which Occupational Safety and Health Administration (OSHA) regulations apply to your specific operations
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Your insurer’s loss-control recommendations
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Your company’s unique risk exposures
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State-specific compliance requirements
Without this information, the output may sound polished but still miss critical details.
To improve results, businesses must provide relevant background information, company policies, and industry-specific context when using AI tools.
AI Has Limits to What It Can Remember
AI systems also operate with what is known as a “context window.”
This refers to how much information the model can actively process in a single interaction.
If you provide a small amount of information, the system can keep track of everything easily. But when large documents, multiple policies, or long conversations are added, the system may begin to lose track of earlier details.
This can lead to responses that:
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Overlook important information
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Contradict earlier content
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Miss key compliance considerations
For this reason, AI outputs should always be reviewed carefully before being used in business decisions.
Where AI Can Be Valuable for Businesses
When used appropriately, AI can help organizations work more efficiently by supporting tasks such as:
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Creating first drafts of documents
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Summarizing long reports
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Brainstorming ideas and strategies
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Generating checklists and outlines
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Analyzing large volumes of data
In these cases, AI can significantly reduce administrative workload while still allowing human experts to review and finalize the output.
Why Human Oversight Still Matters
AI should not be the final decision-maker in business operations.
Important decisions should always involve human expertise and professional judgment, especially when legal, financial, or regulatory risks are involved.
Attorneys, accountants, insurance advisors, and internal subject-matter experts provide critical oversight that AI tools cannot replicate.
Managing AI-Related Business Risks
Organizations adopting AI should establish clear guidelines before implementing these tools across their operations.
An effective AI governance approach may include:
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Creating an AI usage and ethics policy
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Training employees on appropriate use of AI tools
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Restricting the input of confidential or client data into public AI platforms
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Verifying sources and accuracy of AI-generated information
Without clear policies, organizations may face new liability exposures.
Potential risks include:
Cyber and data privacy exposures
Sensitive data entered into AI tools could unintentionally violate privacy or intellectual property regulations.
Errors and omissions liability
Relying on inaccurate AI-generated guidance when advising clients could create professional liability risks.
Security vulnerabilities
Public-facing AI tools, such as chatbots, can potentially be exploited by hackers attempting to access stored information.
The Bottom Line
Artificial intelligence can be a powerful tool for improving productivity and efficiency, but it should be viewed as an assistant—not a replacement for professional expertise.
Businesses should combine the speed of AI with the experience and judgment of human professionals.
As AI adoption grows, organizations should also review their cyber liability and professional liability coverage to ensure their risk management strategy evolves alongside emerging technologies.
If you have questions about managing technology-related risks in your business, the team at Bender Insurance Solutions can help guide you through the evolving risk landscape.
