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Why the Next Big Thing has already happened and why that matters for your business

This article was originally authored by Grant Wild on iTwire

 

GUEST OPINION: Will recent AI advances threaten human existence or, conversely, fulfil all our desires –or is this just the latest in a long series of repetitive hype cycles that will soon come crashing down?

First, the short answer. Maybe, but probably not, and even if AI is all that we either fret or fantasise about, so what? If AI, as some maintain, poses an existential threat to the human race or to commerce as we know it, then, frankly, it’s probably already out of our hands. And if it is, then stop worrying and instead focus (and profit) from the way exciting new technology has usually been adopted by the marketplace.

Luckily, we have history to help us with the hype. Since at least the days of the dot-com era, a pattern has emerged regarding technological innovation and the business landscape. Call me a market realist, but I’ve perceived the cycle beginning with a massive wave of hype, investment, eye-popping valuations, and magical thinking that overtakes not just the fabled “tech bros,” but the general public as well. After this honeymoon period, an inevitable crash ensues, when it turns out that for technical or even cultural reasons, the technology simply doesn’t deliver as promised… yet.

Sometimes this means the technology was a solution in search of a problem to solve. But, more often, it means both the technology and the business landscape wasn’t quite ready for the implementation at scale. After this disappointment comes what you could call a digital deflation for this new technology. The technology recedes into the background, waiting for deeper improvements in itself, infrastructure and networking to bring it to life. Once it does, presto, we have the Next Big Thing — which, as it turns out, is the Refurbished and Repackaged Old Thing finally ready for showtime.

A good example is what happened to Enterprise Resource Planning (ERP). When ERP first emerged, its champions claimed that it would unite all the disparate processes of an enterprise under one roof, driving incredible efficiencies that would do magical things for the bottom line of any enterprise that adopted it. It didn’t take long for the problems with ERP to emerge and the complaints to roll in: the software was cumbersome and inflexible and worst of all, it’s supposed benefits were utterly invisible to the customer. The upshot was that ERP lost its allure. Fast forward several years and it’s back, this time as Customer Resource Management (CRM). CRM cannily repackaged ERP, brought the customer to the fore and gave its users what they were actually looking for in the first place. In other words, the future finally caught up with the past.

A similar thing happened with the Internet of Things (IoT). At first, IOT was going to be in every object imaginable tracking every byte of data generated in our personal and business lives. Then, just like ERP, its limitations became apparent, not the least of which was that most people and businesses didn’t need data capture on this scale. Again, time passed, and the Next Big Thing eventually, and quietly, has become a critical technology intelligently integrated in those places where it makes the most sense, from Ring cameras offering homeowners peace of mind and unprecedented visibility and interactivity with their properties or smart sensors monitoring agricultural silos. Digital transformation of this kind simply takes time between the actual invention and its gradual application to our daily lives.

Turning to AI, the same shift will probably need to occur for us to evolve from Linguistic Big Data towards an AI which can truly collaborate interactively with its users. In order for that to happen, the AI will need to learn more about who is using it. With disputes such as the mammoth intellectual property lawsuits against ChatGPT currently roiling, it’s clear that we are nowhere near this sort of acceptance. Similar to ecommerce, this acceptance will come once end users see the efficiencies this sort of adoption will create and the critical features of a nurturing market exist.

And this is where consultancies such as McKinsey & Co. and Accenture come in. They’re the ones who end up packaging the inventions into the applications that become the Current New Thing. They are also the culture creators that rebrand and repackage all of the technologies of Past Yesteryear into relevant gains for modern enterprise. Sometimes, people and companies get used to a certain way of doing things. Demonstrating how new approaches can give a winning edge takes the communication of a new vision, which can seem like an uphill battle — until it isn’t.

Almost a quarter of the way into the 21st century, you would think we’d all be more relaxed about the Next Big Thing hype cycle, but we’re not because the new has a way of surprising us and making us think this time is really different.

So given the inevitable approach of the digital deflation when it comes to AI, what should someone in business or government do? Have your people realise that the only way to own the future is by nailing the fundamentals when it comes to systems, data hygiene and a cultural infrastructure that is tuned to the practical applications of technological change. The next big thing can sometimes mean thinking small.

However, this practical momentum is routinely obscured by hype campaigns, wishful thinking and the madness of crowds. For no sooner have we given up our technologies for dead than they re-emerge and realise their potential under a new name. And the most powerful lesson of these cycles for intrepid technologists and the companies that depend on innovation is that the best time to prepare to integrate a new technology is when everyone is rushing for the exit, and the digital deflation is starting.

It’s those people with the foresight to take another look at what was missed who end up creating and profiting from the future.

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