Gartner’s at it again. Every year it predicts what the next year (and beyond) in technology will look like. They’re not always right, of course, but their job is to identify broad trends by abstracting at just the right level of analysis where specific accuracy is hard to verify after the fact. Who could argue with the impending impact of AI or that IOT will be big? Perhaps worse, they like throwing percentages out there that are impossible to verify. Like this one: “By 2021, early adopter brands that redesign their websites to support visual and voice search will increase digital commerce revenue by 30%.” How could they possibly know this?
So, let’s pay homage to the annual ritual, and comment on what sounds right, what sounds wrong and what’s pretty obvious.
Good, Bad & Obvious Predictions
Gartner believes that (1) “Consumers Favor Visual and Voice Search.” They feel so strongly about this prediction that “by 2021, early adopter brands that redesign their websites to support visual and voice search will increase digital commerce revenue by 30%.” This prediction is good, unverifiable and obvious. There’s nothing new here. We’ve known for decades that users love talking to machines, searching and transacting with graphical interfaces and immersing themselves into video. It’s not the preference that’s important, it’s the state of the technology that matters. How will augmented reality (AR) help this process Not nearly enough on AR or VR here.
Gartner also predicts that (2) “Digital Giants (Will) Self-Disrupt,” and that “by 2020, 5 of top 7 digital giants will willfully self-disrupt to create their next leadership opportunity.” Yes, Gartner, Amazon, Apple, Google and Facebook, among others I assume, will continue to innovate as best and fast as they can. I’m not really sure what Gartner is telling us with its use of colorful phrasing like “self-disrupt.” This prediction redefines the word, “obvious,” though why is it only "5 out of 7"? Who are the two that don't plan to innovate?
The third prediction speaks to cryptocurrencies and blockchain, which Gartner believes will become legitimized: “by the year 2020, the banking industry will derive $1B of business value from the use of blockchain-based cryptocurrencies,” which, Gartner believes, is a “the tacit endorsement of cryptocurrency as a legitimate option by the banking industry” – which it already is. This prediction is good – and obvious.
The next prediction (4) is about fake news, but the prediction itself could very well be fake. How in the world could anyone predict that “by 2022, the majority of individuals in mature economies will consume more false information than true information.” While I agree that fake news will increase, it’s impossible to predict what regulations might appear, what real-time fact-checking might occur, and how the technology giants will address the fake news problem. Bad prediction.
Apparently, Gartner is worried about fake and counterfeit realities. The next prediction (5) incredibly suggests that “Counterfeit Reality Overtakes Reality,” and “by 2020, AI-driven creation of ‘counterfeit reality,’ or fake content, will outpace AI’s ability to detect it, fomenting digital distrust.” Wow! Does this mean that people will turn off their devices because they won’t know what’s real and what’s not? Or they will happily (or even begrudgingly) accept living in fake, counterfeit worlds? Bizarre – and vague – prediction.
The next prediction (6) is an obvious one (though the percentages are always suspect): “by 2021, more than 50% of enterprises will spend more per annum on bots and chatbot creation than traditional mobile app development.” Yes, we’re heading toward a “post-app era,” and, yes, the number of downloaded apps will decrease. But what does “more than 50%” mean? Easy, safe prediction.
The next prediction (7) – “by 2021, 40% of IT staff will be ‘versatilists’ holding multiple roles, most of which will be business rather than technology-related” – is bold on one level, but obvious on another. If the prediction refers to the changing roles of “IT” staff and the need for softer skillsets, it’s obvious. But if the prediction refers to wholesale skill swapping (“a complete transformation”), then it’s bold. It would be nice, however, if Gartner defined “versalitists” beyond the literal inferences attached to the word. How “versatile”? What are the specific “versatile” skills and competencies? How do they differ from the “generalists” we’ve heard about for years? Bad prediction: way too vague.
Number 8: “AI Creates More Jobs Than It Takes,” and “in 2020, AI will become a positive net job motivator, creating 2.3M jobs while only eliminating 1.8M jobs.” This prediction is strange, at best, since there’s no consensus on the number of jobs AI will create or eliminate. Most analysts avoid predicting specific numbers and percentages altogether, noting that at this point any predictions would be highly speculative, except perhaps when they apply to robotic automation – which is also mostly speculative. Providing a specific number of new AI jobs – 2.3M – while also predicting the number of jobs lost to AI – 1.8M – leaves one perplexed (and envious of the crystal ball that Gartner has hidden somewhere in Stamford). Good prediction if you have access to a crystal ball.
Number 9: “IOT in Everything.” Here they go again: everything? According to Gartner, “by 2020, IoT technology will be in 95% of electronics for new product designs.” While we can be confident that IoT connectivity will rise – even dramatically – 95% assumes unprecedented adoption rates – and connectivity (otherwise manufacturers would not tag their products). We’re almost in 2018. How do we get to 95% by 2020? Bad prediction. No one has any idea what the precise penetration/adoption rates will be. It’s anyone’s guess.
The last prediction (10) – “Assume IoT Security Vulnerabilities” – is definitely not a “why didn’t I think of that?” prediction. But Gartner takes it farther: “through 2022, half of all security budgets for IoT will go to fault remediation, recalls and safety failures rather than protection.” How the hell could anyone know what budget allocations for specific technologies or technology risk mitigation will be in 2020?
Okay, Take a Breath
I love annual predictions; we all do. They make fall more interesting and entertaining – and Gartner never disappoints. But one must wonder why the predictions are so content-free or so full of so much unverifiable content, why they’re essentially guesses, and if they’re guesses, what’s the point? My takeaways from the list are that AI is making progress, IoT is spreading, cryptocurrency and blockchain are real, lots of digital content is fake, and big, rich companies will continue to invest in innovation, even if it means cannibalizing some existing products and services. Honestly, how many of us are surprised by any of these “predictions”?
Annual predictions by research and consulting organizations are obligatory. Clients expect them, and they generate a modicum of credibility – which is why they’re usually vague (thereby providing plausible deniability after the fact). Let’s face it, no one wants a client to transform their entire business based on predictions that could easily be wrong. Annual predictions should therefore not be actionable, lest they be strategically dangerous. The trick is stay at the right level of abstraction that’s broadly informative (if often obvious), sometimes entertaining and occasionally even a little provocative. Gartner’s top 10 predictions for 2018 satisfy these criteria. At least 43.7% of the time.
