Exercising Caution with AI: What MSPs Should Consider

The AI revolution, and more specifically the explosion in GenAI tool adoption, has touched an extraordinary number of businesses in today’s modern economy. The channel isn’t an exception to this trend. AI represents an opportunity for MSPs and enterprises alike to enhance business performance through internal operations optimization and highlight ways to better serve customers through automation.

However, AI adoption and use aren’t all candy and roses. What MSPs and other providers should consider when using AI as a tool is that AI is not realized intelligence, but rather learned intelligence based on examples, models, and rules provided. AI is only as intelligent as what is put into it and not infallible. There are plenty of areas where MSPs and their clients should practice vigilance with their AI use.

Where to use caution with AI as an MSP

According to EchoStor CIO Daniel Clydesdale-Cotter, when it comes to AI and security, it’s important to understand who owns the data and who owns the AI model.

“Every single time you ask a language model a question, it’s training itself and there have been instances where internal information is put into one of these prompts, and now that information is part of the language model training which obviously has scared a lot of enterprises,” Clydesdale-Cotter said. “In that scenario, if you don’t own the language model and you don’t own the training of that model, you could be in a situation where you’re using a managed service and providing potentially proprietary information to gain some kind of business value from the AI that you’re using, or the AI that the MSP is using specifically.”

“If you don’t actually own the model you could be giving them information that could be used across all of their customers,” he continued.

There are various areas where MSPs should be cautious when using AI. Employing AI as a tool that enhances services and verifying AI-generated outputs—rather than as a device to run your operations uninhibited—reduces putting your organization at risk.

Below are a few areas where MSPs should practice attentiveness and caution when it comes to AI use:

• Security threat detection: While AI can be a good tool to identify potential security threats, it can also produce false positives or fail to detect more sophisticated threats. Relying on AI to manage security for your organization can result in missing threats or flagging false alarms. It is key for a security expert to verify threats flagged by AI and to recalibrate AI models so that it can learn and produce improved results.
• Predictions and forecasting: Sudden market changes and unique business factors may not be accounted for in business forecasting by AI that generates its predictions based on historical data. This can trigger poor decision-making for your company. It’s important to update models with recent data and external economic factors to produce accurate forecasts.
• Hiring and HR moves: Many companies these days utilize AI to screen resumes and filter through candidates. However, AI can introduce bias into the process, as well as overlook important human factors. You don’t want to overlook strong candidates due to built-in bias, so it’s important to combine AI hiring tools with human judgment during the recruitment process. Organizations should also regularly audit AI systems for bias and diversify training data.
• Customer service chatbots: Have you ever tried to call a company and an automated voice service spun you in circles while you’re trying to troubleshoot a problem? Frustrated customers may abandon support interactions, impacting customer satisfaction. AI chatbots can typically handle routine inquiries, but issues with greater complexity may be beyond the chatbots capabilities. These AI chatbots shouldn’t be the final phase of customer assistance and should provide a path to human support to handle the more complicated problems. The chatbots should also be monitored for recurring issues.
• Content creation: From the business world to the classroom, people are increasingly using AI as a means to create content. While this is a simple way to complete tasks, it doesn’t come without risks. The AI-generated content may appear off-brand and be factually incorrect. If you choose to use AI to create marketing content or social media posts, always review for accuracy, tone, and branding consistency.
• Decision-making processes: AI can provide data-driven insights but shouldn’t be the sole decision-maker. Much like the other areas here, AI should be utilized to supplement human decision-making, not completely replace it. The insights provided should always be scrutinized.

Where to use caution when MSP clients use AI

Clients are going to have continued excitement when it comes to adopting AI. The power of its capabilities is enticing, and the adoption rate doesn’t appear to be slowing down as even small- and mid-sized businesses are seeing success with the technology.

According to a 2023 study by Constant Contact, small businesses and their CEOs are getting in on AI adoption. The study, which surveyed over 1,000 small business owners, found that 91% of businesses that implemented AI have seen an increase in their success.

Much like any other software, AI systems have vulnerabilities that threat actors can exploit. One of these vulnerabilities that can affect the MSP and client is if the client is using AI services or platforms from third-party vendors. This widens the security vectors for attackers. Clients must assess third-party security practices to ensure compliance with their own security standards. 

As trusted advisors, MSPs can offer strategic advice to help clients align their technology investments with their business goals, including keeping clients cognizant of security trends and best practices as they relate to AI.

Read more about how MSPs can safely and securely help their clients meet their goals with our guide to AI managed services.