Many years ago, I decided to give online shopping a try. It wasn’t really popular at the time, but I had caught wind of it and thought to myself, “Why not give it a try?“
So I placed my first order on one of the popular platforms at the time, and waited for it to get shipped. A few days went by, and my package hadn’t arrived yet. And that’s when buyer’s remorse started kicking in.
“Why did I even put my money into this?“
The following day I decided to cancel the order at around 5 in the evening—which was outside of business hours. There was no straightforward way to cancel. I was greeted with a chatbot that just made my experience worse. It was of no help at all.
So I reached out to support the next morning and cancelled the order.
Today, AI has grown far beyond what those simple chatbots could do. But it’s still anything but perfect. In fact, just recently Google’s Gemini was in the news because it told a user to “Please die”. Those stories can be pretty discouraging.
So, should you embrace AI or not? And what are the pros and cons of using AI in customer service? That’s what we’re going to discuss in this post.
How Small Businesses Are Using AI in Customer Service
AI tools are streamlining processes and enhancing interactions in ways we couldn’t have imagined a few years ago. Let’s break down some of the key areas where it’s making a real impact.
First, chatbots and virtual assistants offer 24/7 support. They handle routine questions—like order tracking and password resets—so customer support teams can tackle more demanding issues.
Then there’s AI-powered analytics, which helps personalize experiences. By understanding customer data and behavior, AI tools like Insider can recommend products, offer relevant content, and tailor interactions to individual needs.
For smoother operations, automated ticket routing and prioritization can use machine learning technologies to ensure that inquiries reach the right agents at the right time.
If your business offers phone support, voice analysis is a game-changer. AI can understand customer intent and even analyze emotions, making calls more efficient and empathetic.
And speaking of emotions, sentiment analysis digs into customer feedback—reviews, social media posts, etc.—to gauge overall feelings about your brand. This helps you identify areas for improvement, and celebrate what you’re doing right.
For businesses looking to expand globally, multilingual support powered by AI breaks down language barriers, making your customer service accessible to a wider audience.
Finally, self-service resources like knowledge bases and FAQs can be supercharged with AI, so it’s easier for customers to find answers on their own.
AI doesn’t replace human customer support; it augments your existing team. During customer interactions, AI can provide real-time information and suggestions, helping agents resolve issues faster.
The Advantages of AI in Customer Service
Given all of the above, what are the pros and cons of AI in customer service? Let’s start with the positives.
24/7 Availability
One thing about online businesses is that you’ll serve customers in different time zones. Suppose a customer wants to make a purchase on your website late at night, but has a quick question before they proceed.
In the past, they might have had to wait until your business hours to get an answer, potentially losing interest or going to a competitor.
But with an AI CX agent like Helply, customers can get instant responses, any time of day or night. That means reduced churn rates and more sales.
An AI agent is a virtual assistant programmed to handle common customer inquiries. However, it has greater autonomy, learning capabilities, and problem-solving skills than old-school chatbots. You can integrate it into your website, messaging apps, or social media platforms.
Faster Response Times
Being on hold or waiting days for an email reply can be frustrating, leading to negative customer reviews and experiences.
This is where solutions like AI-driven knowledge bases come to the rescue. These tools can significantly reduce response times, providing instant assistance to your customers.
AI-driven knowledge bases use natural language processing to understand customer queries, and provide relevant articles or guides in real-time. The result is minimized delays and increased satisfaction, which is important for boosting customer loyalty.
So if a customer is struggling with setting up your product, instead of searching through a lengthy FAQ page, they can type their question into your website’s search bar. The AI-powered knowledge base instantly suggests a step-by-step guide, resolving their issue within seconds.
Personalized Experiences
When you have a lot of online interactions, personalization can make your business stand out and create a stronger connection with your customers. AI plays a crucial role in achieving this level of personalization at scale.
AI-powered onboarding flows and in-app messaging systems analyze user behavior and usage patterns to deliver customized support and guidance.
Suppose a new user signs up for your project management software, and they’re struggling with setting up their first project. The system automatically triggers a personalized in-app message offering a quick tutorial video focused on project setup.
This personalized guidance helps users overcome hurdles quickly, and discover the full potential of your software. This increases the likelihood they’ll becoming long-term, satisfied users.
Consistent Support
One common challenge in customer service is maintaining consistency. When you have multiple support agents, chances are they’ll provide different answers. And the quality of support might vary depending on who each customer interacts with.
This inconsistency can lead to confusion and frustration for your users.
Fortunately, AI-powered knowledge bases and automated email responses ensure that customers receive the same accurate information, regardless of the channel or time of day.
Say you have two customers contacting your SaaS company with the same question about your billing process. One uses the chatbot on your website, while the other sends an email to your support team.
In both cases, they receive the same clear and concise answer, either directly from the chatbot or via an automated email response linked to your help center. This consistency builds trust, and reassures customers that they’re receiving reliable information.
Proactive Support
Waiting for customers to report problems can lead to frustration and churn. That’s why you need to anticipate their needs beforehand. That’s the power of proactive support, and AI makes it possible.
AI-powered monitoring tools like Mphasis.ai and Mixpanel constantly analyze user behavior within your SaaS product.
For example, if a user suddenly stops using a key feature they previously relied on, the system can automatically trigger a personalized in-app message:
We noticed you haven’t been using [feature name] lately. Is everything alright? Here are some resources that might be helpful.
This proactive approach shows that you’re paying attention and genuinely care about their success. It reduces frustration, builds stronger relationships, and fosters a sense of being understood.
Disadvantages of AI in Customer Service
Sure, all of that sounds pretty great. But AI definitely has its limitations, and it’s vital to be aware of those too.
Now that we’ve reviewed the pros, let’s look at the cons of using AI tools in customer service.
Lack of Empathy and Human Touch
AI excels at automation and efficiency. But it naturally falls short of genuine human connection. Sometimes, customers need more than just a quick answer; they want empathy and understanding.
Let’s say a customer is clearly upset about a faulty product they received for their child’s birthday. An AI might respond with:
I understand you’re experiencing an issue with your product. Here are the steps for our return process...
But a human agent could say:
I’m so sorry this happened, especially on your child’s birthday. That must be really disappointing. Let’s see how we can make this right for you…
The difference is clear. AI can’t replicate the warmth and understanding that a human can provide in sensitive situations.
Difficulty Handling Complex Issues
AI is great at handling straightforward inquiries. But it can struggle with nuanced, complex, and/or unusual problems.
Let’s say a user is experiencing a unique technical issue within your SaaS platform, one that hasn’t been documented before.
An AI chatbot might offer generic troubleshooting steps or link to irrelevant FAQs, which leads to further frustration.
On the flip side, a human agent has problem-solving skills and the ability to understand context. Thus, they’re able to investigate the specific issue, offer tailored solutions, and even escalate the problem to the development team if needed.
Generic Responses and Lack of Personalization
While AI can personalize to some extent (as discussed above), it can also fall into the trap of providing generic, unhelpful responses.
For instance, let’s say a user asks about integrating your SaaS product with a specific third-party tool.
An AI agent might provide a generic link to your integration documentation, which may not address the user’s particular use case.
Meanwhile, a trained human agent can understand the user’s specific needs and offer tailored integration guidance. Even (and especially) if that requires going beyond the standard documentation.
This personalization is vital for customer satisfaction and successful SaaS adoption.
Complexity of Setup/Customization
AI sounds great in theory. But getting it to work just right for your business often requires a lot of work.
Take ChatGPT, for example. Sure, it can chat about anything under the sun, but to make it work for your specific business needs? That requires some serious prompt engineering skills. We’re talking hours of crafting the “perfect” instructions to get responses that actually help your customers.
It’s no wonder there are thousands of courses on just this subject!
Of course, you can purchase something from a developer that has already put in all that effort. But that can be a pricey solution, depending on your needs and the complexity of the product.
And that’s just the initial setup. AI needs constant ‘feeding’ – with data, that is. You’ve got to keep training it on new products, policies, and customer issues.
What’s the Best Way To Use AI for Customer Service?
AI in customer service isn’t about replacing your human team with robots. It’s about enhancing your agents’ capabilities and freeing up their time with targeted AI features.
Most successful strategies leverage AI for routine tasks, while leaving your agents to deal with complex issues that require a human touch. This balances the pros and cons of AI in customer service – you benefit from the advantages while mitigating the drawbacks.
So you may want to start small, such as by implementing AI for frequently asked questions and basic troubleshooting.
For example, you can use our own Helply AI Agent to handle Tier 1 customer questions. It processes common inquiries, and gathers essential information before passing cases it can’t fully handle over to your human agents.
This approach significantly reduces response times, and frees up your team to focus on high-value interactions. Plus, because it’s such a specific and targeted use case, it’s highly affordable even for startups.
Ready to experience the benefits of AI in your customer service workflow? Helply will:
- Automate up to 70% of tier-1 support tickets. Reclaim valuable time for your team.
- Provide instant, 24/7 support. Be there for your customers, any time, anywhere.
- Free up your team for high-value tasks. Focus on building relationships and tackling complex issues.
- Deliver consistent, on-brand responses. Ensure that every customer interaction aligns with your brand identity.
- Leverage your existing help desk data. Helply learns from the data in your help desk’s shared inbox, in order to provide accurate and relevant support from day one.
