The increasing meaninglessness of AI

The term artificial intelligence (AI) has become one of the most ubiquitous in the tech sector, with companies from financial services to retail, healthcare to agriculture all claiming to be harnessing the power of algorithmic automation.

But in the rush for competitive advantage, many may be spending money and time on irrelevant technology and further confusing consumers on what actually constitutes AI.

Darin Archer, chief marketing officer at digital commerce provider Elastic Path, suggested that the ever-increasing speed of the hype cycle means burnout is beginning, with the joke going around Silicon Valley right now being that you get kicked out of a pitch if you bring up AI.

“This is because AI, at the level of market perception, is unachievable by the vast majority of organisations,” he suggested. “The challenge is that you not only need data scientists that are being hoovered up by the likes of Facebook, Google and Microsoft, but you also need huge, richly codified training data – and most companies are struggling just to connect their own customer data.”

Archer continued that in reality, most of the buzz from software companies such as IBM and Salesforce amounts to nothing more than the mere evolution in natural language processing – meaning most can create chatbots and recognise written content from interactions.

“AI is meaningful and has changed everything, including its ability to interrupt every digital record that we’ve ever created, however, it still has a long way to go to take people’s jobs. Considering this, I think AI is dead... or at least we'll stop talking about it in 2019 with empty statements and start talking about business problems and business outcomes again.”

There has been a steady stream of scare stories about AI’s impact in recent years, from surveys suggesting that existing business models will disappear soon, to central bank warnings over how many jobs will be lost to the robots.

One thing’s for certain, AI is near the top of the agenda for most boards. Research in October showed that 45 per cent of IT purchasing managers in the UK plan to up investment into AI in the coming year.

Tim Carey, general manager for artificial intelligence at IPsoft, said that AI has become overused to the point at which it has no impact, noting that he has banned use of the term in meetings.

“It’s used to describe everything from the simplest Repeat Process Automation (RPA) through to the most advanced robotics, trying to surpass the Turing Test and reach the singularity,” he explained.

“So we prefer to say we’ve built technology that enables us to scale what humans can do,” continued Carey. “Our digital colleague Amelia is advanced cognitive AI, which is something that many people won’t initially understand, so we have to break it down.”

Tier1CRM's co-founder and chief executive Mark Notten agreed that everyone is talking about AI, but not many really know what to do with it.

“To cut through the noise, I think we need to isolate the key need for AI – in capital markets, for example, there is a need for a greater level of efficiency from a regulatory perspective,” he pointed out.

“It is natural for sell-side firms to apply AI because there is a need to better track their interactions with clients and AI is the next best call in this context. If machine learning and voice recognition can make it easier and faster than typing information to a call report for example then that becomes much more efficient."

Within financial services, more than three quarters of decision-makers polled by Intertrust late last year thought AI will play the biggest role in revolutionising the industry in the next five years – with common applications being to detect fraud and automate processes such as credit decision-making and customer interaction.

The same study found that a technology skills gap is emerging though, with almost 40 per cent of respondents admitting they have struggled to keep pace with hiring AI experts to fill positions.

Lee James, EMEA chief technology officer at Rackspace, suggested that it would make more sense for the abbreviation to be IA, as most of what’s available is intelligent algorithms.

“We’re getting good at making sense of large amounts of data, but these models are still essentially asking questions, not giving answers,” he said. “The next step is the ability for computers to actually make decisions based on less data – we’re not at Skynet [the Terminator’s precursor in the film] just yet, but cutting through the noise effectively and making better predictions is not far off.”

Adobe's industry marketing director Michael Plimsoll argued that AI is too often confused with machine learning.

"So machine learning might automate an email to a banking customer with a number of personalised offers for savings accounts based on defined algorithms," he explained. "AI, however, could provide a completely personalised website design for every single customer at scale, with targeted deals, images and text."

The possibilities for AI to improve customer experience are almost endless, but Plimsoll said organisations can fall at the first hurdle by viewing this technology as a tick-box exercise and not thinking strategically about why it has been applied in the first place.

"When implementing AI and machine learning, companies must evaluate their strategy against their core objectives, to ensure they’re using this technology for some purpose, rather than for technology’s sake," he concluded. "AI is complex – without a clear strategy, it can alienate customers and employees.”

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