Using AI in Customer Service? Don’t Make These 4 Mistakes

AI is omnipresent in 2025 in all areas of the business sphere, including customer service. And for good reason. Used right, AI can provide invaluable insights into your customers’ behaviors and preferences, boost the efficiency of your customer service team and increase overall satisfaction.

Between dynamic personalization, streamlined purchase processes and predictive customer support, many small businesses are leveraging AI to level the playing field and provide enterprise-grade customer service.

However, despite AI’s massive potential, there are several potential pitfalls when using AI in customer service. At worst, AI can scare off customers or generate frustration, rather than helping to streamline processes.

Here are the four most common mistakes — and how to avoid them.

Related: How Small Businesses Can Leverage AI Without Breaking the Bank

1. Frustrating generic chatbots

To start with, chatbots can be a great asset to your team members and customers alike. They can speedily handle routine queries, free up your agents’ capacities, respond to customers even outside regular business hours and reduce wait times.

However, to be effective, chatbots need to be well-trained and personalized.

Unfortunately, many companies — in a rush to stay ahead in the AI race — deployed chatbots that ask too many questions, give generic answers and fail to solve queries.

In one hilarious example, NYC’s MyCity chatbot kept giving wrong answers even six months post-deployment and after $600,000 in investments, misinforming users about legal requirements for business owners and even basic facts such as the minimum wage.

Overall, 80% of people reported that interactions with chatbots have increased their frustration rather than leading to quicker solutions to the issues they were facing.

To avoid this, it’s crucial that chatbots are trained well on company-internal data. Ideally, they should be able to leverage customer-specific data across a number of different channels in order to provide personalized, efficient support to every person who reaches out.

2. Unaccessible siloed data

On that note, another common pitfall to avoid when implementing AI in customer service is data siloing. One of AI’s greatest strengths is its capacity to process huge amounts of data and unearth patterns and trends, condensed into actionable insights. These insights can then be leveraged for personalization and targeted strategy adjustments.

However, that’s only possible if AI actually has access to all the necessary data elements — and that is a challenge many small businesses are currently facing.

In fact, a recent study by Nextiva, a market leader in customer experience software solutions, found that among company leadership, data siloing was identified as one of the most common barriers to AI implementation. In the study, 39% of respondents agreed that they “struggled with accessibility, aggregation, integration and structure of real-time and historical data.”

To avoid this limitation, it’s essential to audit data storage and integration as soon as you start planning your AI implementation strategy. Making sure from the start that the systems you are considering integrate well — or that bridge solutions are at least available — will avoid unnecessary siloing and frustration down the line.

Related: AI Can Give You New Insights About Your Customers for Cheap. Here’s How to Make It Work for You.

3. Going overboard on hyper-personalization and automation

On the other end of the spectrum are businesses that go overboard in their enthusiasm for AI, to a degree that can appear off-putting to many customers. This includes hyper-personalization and automation processes.

While personalization is a key advantage of AI and can boost the efficiency of customer service agents and the satisfaction of the people they interact with, you don’t want to appear omniscient either. Having the impression that a company knows everything about them before they even talk to you is seen as acutely creepy by many customers.

Salesbots, in particular, often trigger the uncanny valley effect, or scare off potential customers by leveraging information they don’t feel they ought to have access to.

To steer clear of this particular pitfall, it’s essential to carefully calibrate the level of personalisation you implement and weigh its potential benefits in boosting conversions against customers’ perception of intrusiveness.

4. Forgetting human escalation options

Finally, a widespread mistake small businesses make in leveraging AI for customer service is to neglect human escalation options, especially in customer support. No matter what your AI can do, it’s always necessary to offer customers the option to talk to a human agent instead.

There is nothing more frustrating for a customer facing an urgent problem than being stuck in an ineffective conversation loop with a chatbot or a virtual phone agent when an actual person would clearly help them reach a solution far more efficiently.

Outside business hours, when AI is the only one holding down the fort, it’s often enough to offer customers the option to leave a message and assure them you will contact them as soon as possible. Other than that, though, you need to give people the option of a human lifeline to help put out an urgent fire.

Related: Does AI Deserve All the Hype? Here’s How You Can Actually Use AI in Your Business

Conclusion

In 2025, AI is an incredible asset that small businesses can leverage to elevate their customer service. It is, however, not a panacea.

To effectively harness the potential of AI and avoid common pitfalls, it’s necessary to carefully plan and train the systems you’re deploying, exercise discretion with respect to personalization and implement a human failsafe option.

By sticking to these tenets, though, you’ll be able to make the most of the opportunities AI has to offer for small businesses in customer service and increase your overall customer satisfaction.