Should AI be Talking to Your Customers?

2023 was the year of AI. It seems that every SaaS company was coming out with a new AI feature set – to write content, generate ideas, improve efficiencies… and to talk to your customers. 

When it comes to customer service, what role does AI play? How are businesses utilizing innovative technology to improve customer experiences, and how are they using technology to simply reduce costs and, in some cases, reduce quality?  

Only time will truly tell how powerful AI can get and the role it can play in your business and in your life. But right now, you may be asking yourself a very important question: Should AI be talking to your customers? 

Our answer is no. 

But that doesn’t mean AI doesn’t have its uses in customer service. 

Types of AI in Customer Service 

There are two broad ‘types’ or uses for AI in your customer service. They are: 

  • AI tools for your customer service team 
  • AI talking to your customers 

AI Tools 

This is exactly what it sounds like. It’s when AI is running in the background performing routine tasks, gathering data or making it accessible, creating workflows, or performing other useful tasks.  

Essentially, AI tools are AI that isn’t trying to replace the human element in customer service. Instead, it’s making the agents’ jobs easier, faster, and better. They’re tools that supplement your customer service agent, improving: 

  • Efficiency 
  • Productivity 
  • Cost-effectiveness 
  • Customer satisfaction 
  • Customer retention 

These AI tools may be interacting with your customers, but they’re doing it invisibly or through interactions with a real, human customer service agent.  

AI Talking to Your Customers 

This is when AI is replacing the person in the conversation when it’s the AI that’s talking directly to your customers. This could be in the form of chatbots, natural language processing (NLP), interactive voice response (IVR), or face and voice recognition. Instead of talking to support, your customers are reaching a robot who, with the true application of AI, is able to respond to their needs and provide them with solutions or resources like a person could.  

Most of the AI tools that talk directly to your customer are conversational AI, technology that can recognize and reply to speech and text inputs. They rely on machine learning, essentially learning and improving through use, to mimic human conversation and responses.  

Why We Prefer AI Tools Over AI Talking to Customers 

At the end of the day, your customers call, email, text, or schedule a meeting with the intention of talking to a real person. While AI can be incredibly efficient, it inherently lacks empathy, nuance, and the ability to be proactive with customer engagements.  

No matter how advanced your AI customer service is, it still can’t effectively mimic human empathy and lacks the ability to understand individuals as individuals, and not just as additional numbers in a growing data set. It isn’t human, so it can’t effectively understand and respond to humans.  

Customer Service AI tools also run the risk of: 

  • Misinterpretation: It is still very common for these tools to misunderstand colloquialisms like industry jargon and idioms, causing confusion and wasting time.  
  • Problems Understanding Context: When your customer service agents have conversations with customers, they have a lot of background that isn’t handled in that call. Disconnected details like how the product works, common problems, their own experiences, and broader context. If your conversational AI can’t connect these dots, it can cause circular logic and problems with your customers.   
  • Personal/Impersonal: Customer support is a big part of how customers build relationships with a brand. AI responding to a distressed customer can come across as uncaring, even when it’s providing accurate information, which could damage the relationship or cost the brand a customer.  

Removing the human element from your customer service sends the message that you’re trying to cut costs, and you’re willing to do it at the expense of your customers’ experiences.  

Maybe someday, AI will be so good that it can read people, respond like a human, and make leaps in logic. But that technology isn’t ready yet, and your customers need excellent experiences today. 

How Abby Connect Uses AI 

Abby Connect is a human receptionist service. Our customers get dedicated teams of 5-10 human receptionists who are specially trained in the art of customer service. Knowing this, you’d think we’d be anti-AI.  

But we aren’t! In fact, we utilize AI to give our receptionists superpowers by eliminating routine human error and increasing efficiency.  

We use AI tools every day to: 

  • Provide better back-end support 
  • Improve our service’s efficiency 
  • Gather and utilize actionable data 
  • Maintain a consistent quality 
  • Optimize our clients’ and their callers’ experiences 

We currently use AI to generate accurate call transcripts, call summaries, and sentiment scores, and we’re working on additional AI features. It’s part of how we set ourselves apart from traditional virtual receptionist services. The goal is to use the best of AI – efficiency-building, templating, transcription, etc. – and the best of our people – those customer service skills – to build the next generation of real, human customer service. We call our service AI-assisted because that’s what it is. Abby is your receptionist, and AI is our assistant. So, at the end of the day, your customers get the best possible experience. 


Written by

Anna Taylor

Anna Taylor

Anna is an accomplished marketing professional with an MBA and certification in marketing and eight years of experience in the field. More than half of that experience has been focused on customer experience and small business growth, exploring how businesses balance human and technology solutions. Above all, Anna is committed to human-first marketing and business development, ensuring that every initiative is focused on creating meaningful connections with customers and driving long-term growth.