Editorial
The Gist
- Navigating AI pitfalls. Awareness of generative AI's limitations is crucial for avoiding customer service blunders.
- AI enhances support. Leveraging AI in customer interactions speeds up responses and boosts confidence in service.
- Policy lag dangers. Continuous updates to company policies are vital to match the pace of AI advancements.
AI customer experience has been the talk of the town since ChatGPT launched in late 2022. In the business world, fewer topics have been more mentioned.
The prospect of AI replacing white-collar jobs stirs deep-seated fears rooted in economic uncertainty and technological upheaval. Professionals across various industries, from finance to healthcare, grapple with concerns about the automation of tasks traditionally performed by humans. The rapid advancement of AI algorithms and machine learning capabilities raises apprehensions about job security and the displacement of skilled workers.
As AI systems become more sophisticated in analyzing data, making decisions and even creative tasks, there is a palpable anxiety about the future job market and the redefinition of career paths.
In fact, the paragraph above was written by ChatGPT. (Insert wink emoji).
AI Chatbots: AI Replacing Staff or Assisting?
We have heard about the fear of AI customer experience replacing jobs in the service sector. There is a constant impression that all our interactions with brands will be replaced by interactions with AI chatbots. Insights and analytics will be conducted by server farms. Even I experience online meetings with more “AI recorders” than actual humans at times (good thing I don’t send an AI bot to speak for me).
Related Article: 8 Ways AI Can Elevate Your Customer Experience
AI Fail: Chatbot Blunder Sparks Lawsuit
Through all of this hype campaign, one thing has been very evident to me — AI customer experience is not yet ready to become a full-time customer service agent. I need only to point out the incident with Air Canada where a customer was ready to purchase a discounted bereavement fare ticket. The company's chatbot stated he could claim it within 90 days after purchasing a full-priced $1,200 ticket. However, when attempting to claim the promised discount, airline support staff informed him that the chatbot had been incorrect. Oops.
Further compounding the AI customer experience debacle was Air Canada’s refusal to acknowledge its mistake, insisting it did not owe the discount. The customer, asserting entitlement to the discount difference, took Air Canada to court — a clear sign that AI customer experience may need reevaluation. A tribunal ruled that the airline must honor the discount, leading to widespread negative publicity for Air Canada.
Related Article: AI Drives Unified Customer and Employee Experiences
AI Is Ready to Assist, Not Take Over When It Comes to Customers
Generative AI is a great tool, but when it comes to using it for customers, it needs more work. Internally, at my company, we have an AI tool that helps us to answer questions — sort of a quick tips without the need to search troves of digital presentations, documents and help files for the right answer. This allows our team to respond to inquiries that might not end up in a Frequently Asked Questions page or might be more technical in nature.
However, it is important to note that we do not give our customers access to this same tool for the same reasons mentioned above.
Ultimately, there is too much leeway in what the AI customer experience functions learn. It first starts with the completeness of the training model. I mention three areas where most of our information would come from, but the failure to include a set of materials or documents that might be hidden behind a firewall will make the information incomplete.
Second, as robust as a company policy might be (and lawyers take great care to ensure they think about every scenario), the updates of the policy might not keep up with the updates of a business, or gaps in the policy may leave room for interpretation.
Finally, there could be bias in setting up the AI customer experience training. It could be that top-tier customers get different treatment typically, but if that is not built into the training, they may get the same treatment as everyone else — particularly if the AI model does not know which customer it is speaking with.
Related Article: Applied AI in CX: Disrupting the Customer Service Space
AI Can Boost Speed, Confidence in Customer Care
Does that mean it is too early to leverage generative AI in improving the customer experience? Absolutely, not. It can help contact center representatives and — in our case — client success managers get access to answers quickly. This is especially true where the response may be more technical in nature where a representative may not normally encounter that topic.
This improves the customer experience in two ways: It allows for a quick response and instills confidence in the response because of that speed. As an added bonus, because it is curated, that representative could put it into a language that the particular customer would understand or reject an “obvious wrong” answer.
Related Article: AI Customer Experience Solutions: Using Emerging Technologies
Balancing AI and the Human Touch
AI can be used in so many more ways as well. I have previously suggested that retail workers can use AI customer experience on their in-store devices to help customers get to the right products and suggest the appropriate add-ons. It is easy to suggest a phone case when someone purchases a new phone, but it would be even better to suggest a charger since some new phones include them and others do not.
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This type of program is already being piloted in the U.S. retailer Target — allowing employees to give immediate responses to a customer about product locations, inventory levels and even customer reviews — all curated quickly by the employee.
Generative AI is here to stay, and someday we may mostly interact with “the machines,” but for now, brands need to be mindful of the customer experience and balancing the use of AI and the training of customer-facing agents to ask the right questions.
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