The next wave of AI innovation is around the corner
Do you understand the next wave of AI innovation? Here’s what you need to know.
How to prepare for the upcoming generative and responsible AI revolution.
What do you think of when you hear “Artificial Intelligence”?
AI is now part of our daily lives. Ideas that used to belong to science fiction or advanced academic research are real. Facial recognition technology helps us cross international borders and unlock our phones. Our favorite online stores point us in the direction of products we may want or need that we didn’t even know existed. And autocorrect saves us time when typing and prevents spelling mistakes (although left unchecked it can cause some embarrassing moments — just Google “autocorrect fails”).
We’re constantly hearing about the latest advances made possible by technologies such as computer vision, machine learning, natural language processing…the list is long, there are many use cases and several success stories. We’re already using all these technologies on a daily basis. Whisper it quietly, but some are now so readily available that they’re almost becoming a commodity.
So, what can we expect in the next wave of AI innovation?
While these technologies are here to stay, there’s so much exciting innovation around the corner. And this is why you need to prepare yourself and/or your organization for the next wave. Whether you’re a product manager, algorithm engineer or researcher; a leader in finance, marketing, sales or HR, it’s important to understand what new developments to expect in the next 2–5 years. Early-adopting companies that harness this coming wave smartly will be able to enjoy a significant advantage over their competitors.
I believe that the two most important buckets of innovation are generative AI and responsible AI — and I’ll go into more detail about both shortly. Of course, no one knows exactly what the future will bring. But by looking at dynamics and known models of technology adoption we can get some very strong indicators of what to expect.
A useful model to explore is the Gartner Hype Cycle — a methodology that represents the maturity and adoption of technologies graphically, showing how they will evolve over time.
When technologies are first developed, there’s a lot of hype and expectations can be seriously inflated (weren’t we all supposed to be driving automated cars, shopping in cashier-less supermarkets, living in a virtual reality world and having flawless interactions with our phone’s virtual assistants by now?). As a result, there’s normally some disappointment, but if you stick with the innovation it will eventually reach the plateau of productivity and change the world.
Gartner’s Hype Cycle model for Artificial Intelligence
As you can see in this graphic representing the AI sector, the technologies that most of us associate with artificial intelligence are already after the hype, and some (highlighted in grey) are on the way toward the plateau of productivity. This means that these technologies are appearing everywhere and adopters get a much smaller competitive advantage — if any — because in many cases they’re playing catch-up.
So there’s a huge opportunity here. Look at all those technologies that didn’t yet peak. Most people have never heard of them yet — but they’re going to change the world as well.
What’s the next wave?
In the next wave, we’ll see two major trends: responsible AI (highlighted above in purple) and generative AI (in pink).
Responsible AI is about making sure that we use these new technologies safely, fairly, and ethically — and to do so they need to be explainable. Artificial intelligence is an incredible, life-changing tool that will continue to revolutionize our world. And yet, as it becomes more advanced and more pervasive in our lives, the risks grow.
AI can develop biases or make mistakes. For example, Amazon had to stop using CV screening software that showed a bias against women and an algorithm used in US courts was biased against black people .
