Adults have to do a lot of unpleasant jobs; it’s part of the gig. Taking out the trash, cleaning the toilet and making the daily school run are unavoidable when it comes to keeping life running smoothly.
But there’s one particular job that fills me with dread: calling a “helpline."
Every time I pick up the phone to discuss tax codes, remortgage rates, insurance quotes, doctor’s appointments or some other exciting aspect of modern life, my knees go slack and my head starts to pound. Cue generic hold music and a constant robotic reminder of my place in the virtual queue.
Once you do get through to a person, things rarely improve. The poor soul on the other end of the line guides me through mundane security questions before reading from a pre-prepared script. Often, they fail to offer up a single noteworthy piece of advice when questioned directly.
During one of these recent calls, it occurred to me everyone involved would benefit from letting artificial intelligence handle the task. I don’t mean the basic interactive voice response (IVR) program that routes your call based on how you answer recorded questions; I mean a full conversational AI agent capable of discussing and actioning my requests with no human input.
I’d get through the process faster (because the organization wouldn’t need to wait for available humans to assign) and it wouldn’t require a living, breathing person to spend their days on the phone to an aggravated person like me. Similarly, an AI doesn’t need to clock off at the end of a shift, so the call could be handled any time of the day or night.
Let me hear a voice
Plenty of companies have implemented browser or app-based chat clients but, the fact is, a huge amount of people still prefer to pick up the phone and do things by voice. And I think most industry leaders recognize this.
Humana, a healthcare insurance provider with over 13 million customers, partnered with IBM’s Data and AI Expert Labs in 2019 to implement natural language understanding (NLU) software into its call centers to respond to spoken sentences. The machines either rerouted the call to the relevant person or, where necessary, simply provided the information. This came after Humana recognized that 60% of the million-or-so calls they were getting each month were just queries for information.
According to a blog post from IBM, “The Voice Assistant uses significant speech customization with seven language models and two acoustic models, each targeted to a specific type of user input collected by Humana.
“Through speech customization training, the solution achieves an average of 90-95% sentence error rate accuracy level on the significant data inputs. The implementation handles several sub-intents within the major groupings of eligibility, benefits, claims, authorization and referrals, enabling Humana to quickly answer questions that were never answerable before.”
The cost of AI
The obvious stumbling block for most companies will be the cost. After all, OpenAI’s chatbot ChatGPT charges for API access while Meta’s LLaMA is partially open-source but doesn’t permit commercial use.
However, given time, the cost for implementing machine learning solutions will come down. For example, Databricks, a U.S.-based enterprise company recently launched Dolly 2.0, a 12-billion parameter model that’s completely open source. It will allow companies and organizations to create large language models (LLMs) without having to pay costly API fees to the likes of Microsoft, Google or Meta. With more of these advancements being made, the AI adoption rate for small and medium-sized businesses will (and should) increase.
According to recent research by industry analysts Gartner, around 10% of so-called agent interactions will be performed by conversational AI by 2026. At present, the number stands at around 1.6%.
"Many organizations are challenged by agent staff shortages and the need to curtail labor expenses, which can represent up to 95 percent of contact center costs,” explained Daniel O'Connell, a VP analyst at Gartner. “Conversational AI makes agents more efficient and effective, while also improving the customer experience."
You could even make the experience a bit more fun. Imagine if a company got the license to utilize James Earl Jones’ voice for its call center AI. I could spend a half-hour discussing insurance renewal rates with Darth Vader himself.
I’m not saying there won’t be teething problems; AI can struggle with things like regional dialects or slang terms and there are more deep-rooted issues like unconscious bias. And if a company simply opts for a one-size-fits-all AI approach, rather than tailoring it to specific customer requirements, we won’t be any better off.
Zooming out for a second, I appreciate that we’re yet to fully consider all the ethical questions posed by the rapid advancements in AI. Regulation will surely become a factor (if it can keep pace) and upskilling a workforce to become comfortable with the new system will be something for industry leaders and educational institutions to grapple with.
But I still think a good place to start is letting the robots take care of mundane helpline tasks — it’s for the good of humanity.