We live hype cycles where the name of a technology type proliferates seemingly in everything we see as leading to the promised land of a new better situation. It came with cloud, which we are still evolving with, Big Data was a big offering as the solution to all our data insight needs and now we are experiencing the AI (Artificial Intelligence) hype. Everywhere you look from tech publications and events to job discussions and business articles and of course the movies are hyping up the change that AI will bring to our lives and angling AI into the conversation as a game changer solution.
AI has been repeated enough times now that its meaning has been fogged into a lessness by its sheer overpromise. No one went to market wanting to buy some ‘cloud’, what drove the cloud market was the application innovation, a business outcome that happened to be powered by and enabled through cloud compute power and flexibilities. The same bears true of AI.
Many purported uses of AI are far from it, simply in truth being uses of data or big data to advise you on something that removes your own estimation or decision. Look at examples such as toothbrushes touting AI capabilities, dig past the hype and you find its simply looking at your patterns of use compared to best practise and recommending what you do! Truly AI as we expect or just a great branding exercise to differentiate and grab the tech heads and early adopters purse spend?!
With AI the discussions are wide around where we could use AI, and there remains a big push on AI as the shiny buzzword selling chatbots, data intelligence and automation tools.
AI in truth of the real expectation and promised land is centred around machine learning and deep learning, utilising self-learning compute that truly provides business insight and optimised efficiencies to the business.
There is no doubt that used in the right application space and business process that AI can add fantastic value to a business, the use cases and market statistics all lead to this validation. However, where and when and what ‘true’ AI to use is the challenge I propose faces most businesses today.
Elsewhere I have talked of how AI (amongst Big Data, VR, IOT, etc) have been empowered to become mass market by the proliferation of affordable cloud compute power, however having the capability, experience and expertise to assimilate where and how to gain true advantage from this in your business is the greater challenge for most.
You do not simply buy some ‘AI’ switch it on and the world becomes a more successful place for you! The business use case, target outcome and alignment to an AI application base needs careful determining in order to gain the upsides promised.
What businesses want is better data insights, automation of processes (especially repetitive) away from expensive human effort and mundane tasks.
In the top 5 barriers to AI adoption are listed lack of clear strategy for AI (43%), lack of talent with appropriate skill sets for AI (42%), functional silos constraining AI solutions (30%) and lack of technology infrastructure to support AI (25%) (Source : McKinsey study).
What we can expect to see is the adoption of AI growth through an embedded go to market offering. What I mean by this is as we have seen in cloud already, many have bought a solution for its flexibility, outcomes and function and cloud as the platform has come as an inbuilt enabler, not as a conscious decision. We can expect to see may using AI through a similar route; for example, having selected an ERP system to find an inbuilt AI advantage comes through that vendor enhancing their offering with a function that is driven by an underlying AI component.