AI is creating new opportunities for businesses, from improving customer service to automating everyday tasks. But as these tools become more connected to business systems and customer data, they also raise important questions about security, privacy, and compliance. 

How can businesses take advantage of AI while protecting the information they’re responsible for? And what should they consider before bringing new tools into their operations? 

Those were some of the questions explored during our recent webinar, Compliance, AI & Cybersecurity: How They Work Together, featuring Nikki Fisher, Manager of Sales & Account Management, and Justin Elder, Senior Compliance Consultant and licensed attorney. 

Here are three key themes from the conversation, along with answers to common questions from attendees.

1. Cybersecurity Is Becoming More Complex

Cybersecurity requirements continue to evolve as businesses rely on more technology, cloud services, and third-party providers. Cyber insurance is part of that conversation, too. 

Insurance applications may ask businesses to demonstrate that they have safeguards such as multifactor authentication (MFA), endpoint detection and response (EDR), and properly configured firewalls in place. Requirements vary by insurer and policy, making it important to understand what your coverage actually requires. 

During the webinar, Nikki and Justin discussed why simply having a firewall or antivirus software may not be enough. Businesses also need to consider how their security tools are configured, monitored, and maintained. 

What can businesses do? 

• Review your cyber insurance policy and understand its security requirements.
• Confirm that your firewall and other security tools are appropriate for your business. 
• Make sure your systems are maintained and monitored. 
• Work with your IT or cybersecurity provider to identify gaps before an incident occurs. 

Cyber insurance can be an important part of managing risk, but it shouldn’t replace a proactive approach to protecting your business.

2. AI Needs the Right Data Safeguards

AI tools can help businesses work more efficiently, but the information employees share with those tools matters. 

Pasting customer information, financial reports, or confidential business documents into an AI tool without understanding its privacy and data-use policies can create risk. Different tools handle user inputs differently, so businesses should never assume their information will remain private simply because a platform is familiar or requires a paid subscription. 

Before adopting an AI tool, understand how it handles your data, whether your inputs may be used to train models, who can access the information, and what controls are available. 

The same principles apply when AI connects directly to business systems. For example, an AI voice agent might need access to a phone system, scheduling software, or customer relationship management (CRM) platform to complete its tasks. That access should be limited to what the agent actually needs. 

A few questions to ask before adopting AI: 

• What information will the tool access? 
• How is that information stored and protected? 
• Will the provider use your data to train its broader AI models? 
• Which applications and systems can the AI access? 
• What safeguards are in place to prevent unauthorized use? 

It’s important to understand how a tool works and put the right safeguards in place before using it.

3. Compliance Still Matters When You Use AI

AI doesn’t remove a business’s existing responsibilities around privacy, security, or compliance. If your business is subject to regulations, contractual requirements, or cyber insurance conditions, those obligations may affect how you can use AI and what information you can share with it. 

During the webinar, we discussed the importance of considering these requirements when implementing AI tools, particularly in industries that handle sensitive information. 

Protecting sensitive information 

For businesses that handle protected health information, payment card data, or other confidential information, AI workflows need to be designed with those requirements in mind. 

For example, businesses considering AI for customer calls should understand how call recordings and transcripts are handled, whether sensitive information can be removed or restricted, and how the system manages customer payment information. 

One approach to payment security is directing customers to a secure payment page rather than asking them to provide card details directly to an AI agent. Any solution should be reviewed to confirm that it meets the applicable security and compliance requirements.

Understanding how AI may be reviewed 

AI-related activity may become relevant during a regulatory investigation, legal proceeding, or cyber insurance claim. Businesses should understand what information their AI tools retain, what records are available, and how those records are protected. 

Before introducing AI into a business process, identify the rules and obligations that already apply to that process. Then confirm that the proposed tool and workflow can meet them. 

Navigating cybersecurity checkboxes, compliance standards, and AI integration can feel like a lot to manage, but you don’t have to tackle it by yourself. 

If you want to explore how an AI voice agent can streamline your customer service, or you want to ensure your firewall meets next-generation insurance requirements, watch the webinar to learn more.

 

 

Questions Business Leaders Asked 

Can an AI voice agent do more than just answer calls? Can it help route calls, summarize voicemails, and help manage customer interactions? 

Absolutely. An AI agent can perform complete workflows. You can train it to do almost anything a human can do on a computer—from logging into a CRM to summarizing a call, updating an account, and setting a task. It also performs sentiment analysis, flagging frustrated customers. It can even determine your busiest phone hours so you can optimize employee staffing.

What should businesses consider when giving AI access to their phone systems and customer information? 

You must ensure the AI has access only to the applications it needs to perform its job, and absolutely no more. You don’t want it to have lateral access to employee files or HR databases. At ALLO, we address this during our consulting and design phase by assigning specific “licenses” or restricted credentials (like a standard receptionist license) to the AI agent.

What are some common cybersecurity risks businesses might overlook when adopting a new AI tool?

Outside of standard encryption, one major risk is uncontrolled API usage. Because AI services are often billed “per token” or “per minute,” a malicious competitor or bad actor could repeatedly dial your system just to run up your AI bills. You need strict guardrails to prevent exploitation of your agent.

If I wanted to run a projected profitability report through AI, is it best to use a free tool or a paid platform? 

It depends on if you want the world to see it. If you don’t care, you can use a free one. But if you want to keep those numbers private, you must use a paid, secure, enterprise-grade AI system. However, don’t assume a tool is secure just because it’s paid—you must verify that they explicitly guarantee data ownership and promise not to use your inputs for training their general models.

Can next-generation firewalls that ALLO sets up stop employees from utilizing free AI assistants at work? 

Yes. We can specifically block access to public AI websites (like free ChatGPT, Grok, etc.)

using content filtering. However, you should also establish an Acceptable Use Policy (AUP). Just like a car’s engine doesn’t physically stop you from speeding but the law does, an administrative policy creates clear guidelines and consequences for your team.

Compliance feels very overwhelming. How can a small business figure out which regulations apply to them when using AI? 

The simplest way to think about it is: any rule, contract, or insurance policy that applies to your regular business also applies to your AI use. If you have a client contract promising to keep their blueprints secure, or an insurance policy requiring MFA, those parameters automatically dictate how you must handle data when feeding it into an AI tool.

How do AI sentiment analyses fare in the realm of HR and employee evaluations? Can AI be used to write up employees? 

We are at the cutting edge of this legal landscape, and several states are already passing laws to restrict AI from making automated HR decisions. While AI can collate data (such as identifying customer frustration trends), people should always make the HR decisions. AI can help generate a factual report of an incident, but an official reprimand or evaluation should always be handled by a human manager.