In May I’ll be speaking at the Health 2.0 event in Europe, with our panel convening to both discuss and demo some of the interesting applications of artificial intelligence in healthcare at the moment.  In the health sector, it is very much the technology of the moment, with the vast majority of startups attending the event having some element of AI in their offering.

Except, of course, AI is not a new concept and has largely been floundering for several decades as it struggled to really cross the chasm and create much in the way of useful applications.

Now this presents us with a dilemma.  Is it AI that has advanced and thus found a use and value in the marketplace, or have other things improved to make the AI that was previously a fringe activity more attractive?  Despite the buzz surrounding it as a technology, I’m inclined to think it is as much the latter as it is the former.

Don’t get me wrong, there have been some tremendous advances made, both in academic research labs and those of tech behemoths such as IBM and Google, but I’m inclined to think that those advances have happened because the conditions are now right in a way they weren’t before.

Fertile ground

Let me explain.  A lot of the AI based systems we see today require huge amounts of data, and I’m sure we can all agree that data is more readily available now than ever before.  We have billions of IoT sensors, increasingly potent smartphones and mobile devices, wearable devices and so on.  What’s more, it’s increasingly common for data to be open and available, whether in the scientific world or via the numerous government projects to open up datasets to the world.

With Moore’s Law continuing to exponentially increase the computing power we have available, we are also now able to not only generate huge volumes of data, but process that data in a timeframe that simply would have been impossible to believe even a decade ago.  The original human genome was a multi-billion dollar project that took years to complete, but now you can get your genome sequenced in days for under $1,000.

We’ve also got increasingly powerful tools to ensure that data is kept secure, whether it’s advanced cryptography techniques or emerging technologies such as blockchain.

There are also social factors, with people increasingly demanding the ability to manage their own lives as much as possible, whilst healthcare systems are struggling to cope with both demographic pressures of an ageing population and financial pressures exerted by the demands placed upon them.

An idea whose time has come

French writer Victor Hugo famously said that there is nothing as powerful as an idea whose time has come, and I think the journey AI has gone on is a nice example of that.  The possibilities have largely been there for a while, but it needed various other bits of the jigsaw to fall into place before it could really take off.

It’s a process I suspect many innovations need to go through, and history is littered with great ideas that were simply in the wrong place, at the wrong time.  Indeed, in a recent TED talk, Bill Gross argued that timing was the single biggest reason why startups succeed.

Indeed, it seems increasingly common that first mover advantage has been replaced by fast followers who enter a market after others have tackled the systemic challenges that need to be overcome to make the market in the first place.

A classic example is that of the digital camera, which was famously invented at Kodak way back in 1975.  Not only was the timing not right at Kodak, but the infrastructure to support digital cameras didn’t exist.  Personal computers were a rarity, and there certainly wasn’t the capacity in them to store photos, either in the cameras themselves or on the computers of the day.  It was only when both began to improve 30 or so years later that digital cameras began to gain traction.

Getting the timing right

When you’re talking systemic things its hard for one single organization to really control and influence things sufficiently to ensure the timing is right, but governments can play a bigger role in prodding things along as they have the helicopter view of things required.

The annual innovation index from INSEAD and WIPO doesn’t explore particular sectors, but it does provide a systemic look at the innovation health of a nation.  It examines things like their academic landscape, the ease of starting a business or protecting ones IP.  It examines the ability to raise capital and investment in R&D.  Such systemic investments can help to provide a more fertile environment for innovation to thrive, and to ensure that when breakthrough innovations are made, the timing is just right.

What you can do as an individual organization, however, is ensure you have a good grasp of the wider ecosystem that you operate in so you can sense the changes in the market that may make innovations succeed (or fail), and then be agile enough internally to respond rapidly when you sense an opportunity presents itself.  It’s very hard to ever get the timing right all of the time, but this will give you a decent change.