AI is now powerful enough to automate the back office
But that doesn't mean it's as easy as flicking a switch
In issue 28 of ITPro, John Loeppky writes that the business world is fascinated with artificial intelligence (AI), with most of the excitement centred around customer-facing services. The technologies used to make a Tesla stop or embedded in the soothing voice of your virtual assistant have grabbed most of the headlines, but what about AI’s role in supporting relatively unglamorous back-office functions?
According to industry figures, the use of AI in supporting the HR, IT, legal and financial departments within organisations is not only well underway but maturing. In the last few years, these automations have become increasingly widespread, with some organisations now assessing whether it’s viable to automate vast swathes of the business.
How robotic automation is being applied to the workplace
The automation industry is growing, with the market expected to grow from $140 billion in 2021 to $234 billion by 2028, according to the Insight Partners. Gartner, meanwhile, estimates the robotic process automation (RPA) software market, a subsection of automation used primarily in the back office, could reach $3 billion in the next two years.
Lost in translation
The first question organisations must ask themselves often centres on clarifying the terminology itself, according to the president of financial automation firm Beanworks, Karim Ben-Jaafar. “What are you looking for, machine learning or AI? Do you know the difference? Most companies don't. They think machine learning and AI are just synonyms – but they're not.”
For his fintech company, machine learning is an entirely passive – and far more expensive – tool, while AI allows for processes to be taught to a tool. He believes machine learning is falsely seen as a perfect solution that requires minimal effort to implement. In fact, choosing it for tasks it’s not fit for is prohibitively expensive and akin, he says, to being an early adopter of laser eye surgery (LASIK). “That's monstrously expensive right now,” he says. “That's like getting LASIK when it first came out at $100,000 an eye. The good news is the price is going down to the point where you're going to look at it like it's $500.”
For Jay DeWalt, chief operating officer of Arria NLG, meanwhile, the three key terms that frame his conversations about AI are natural language understanding (NLU), natural language processing (NLP) and natural language generation (NLG). He uses the analogy of children learning to speak as a way to frame the technology his company uses in a wide array of industries and departments. First, they learn how to understand commands from their parents, before learning the sentiments of those commands, and then beginning to understand meaning. It isn’t until later, though, that they articulate those words in a meaningful and insightful way.
Despite criticisms, DeWalt is betting on AI, and NLG specifically, as a world-changing tool.
“Someday, I'm going to just talk to my machines and they're going to talk back to me and give me the information I'm seeking.
I think NLG is a revolutionary technology that's going to change the world and how we interact with systems, how we get information from our data.”