What Happens When AI Takes Over| By |Ben Plomion

A lot of people have been comparing the rise of Artificial Intelligence to the web, and it’s not hard to see why. Exponentially faster, and capable of using machine feedback mechanisms in order to “learn” AI is being talked about today as a technological breakthrough – albeit one that has been more than sixty years in the making.

Like the shift from intranets to the world wide web, and as Chris Anderson argued in 2010, the web to the Internet, AI is now widely viewed as the next great disruptor, capable of vastly improving human’s cognitive abilities.

But as with any new technology the future is still largely unknown. Some of the world’s leading companies have failed to make progress, or made missteps, as with IBM’s highly publicised setback with Watson to cure cancer, or Facebook and Google’s attempts to identify and manage content on their respective platforms. Despite some of these inevitable fumbles, AI holds a tremendous amount of promise and has the power to disrupt every industry. Businesses should care – perhaps more than they currently do, or they will not be prepared for the great changes that are coming, and they’ll be left behind.

Like any technology, AI is only as good as the people who help build it, and companies and individuals who have a seat at the table will be able to influence how AI develops and be able to design tools that have a positive impact on business and can create a better world.

However, there are several implications to consider as we get further along the road to AI and its benefits. Leadership teams should be asking themselves what their end goals are and what type of AI application works best to suit their needs. For example, education needs to happen in terms of the types of AI solutions that are currently being developed and offered – from neural network research being carried out in academic circles to AI-as-a-Service offerings, to applied AI in almost every vertical use case you can think of. The pace of AI is going to move fast, and companies are struggling to understand if they are better off to build or buy – and to attract and retain the talent and skills needed to succeed in either case.

Data is also an issue for companies. How do they leverage their existing data and how do they get it to work with outside data? The ability to gain understanding and actionable insights from data to inform critical business decisions is not to be taken lightly – International Data Corporation estimates that global data doubles in size every two years – the sheer volume of data alone has already surpassed a human individuals ability to process and analyze. According to a 2017 study from NewVantage Partners, 85.5 percent of executives report that their organization has taken steps to create a data-driven culture, but only 37.7 percent report that these efforts have been successful to date. Clearly, the value of being able to harness data and filter it down into usable information is there – but companies still aren’t able to capitalize on it, despite making investments in BI, ERP, cloud, and big data. What’s going to be different about AI?

First of all, AI isn’t going to be a choice. Jobs are changing – from automotive factories like Tesla and distribution centers like Amazon’s becoming automated, we’ve already had a glimpse of what the future will bring. Businesses and employees need to start thinking about our relationship to technology because it’s only going to become more symbiotic over time. Furthermore, it’s not all doom and gloom – according to a new study from Accenture, AI may be able to create as many new jobs as it replaces. Now is the time to start thinking about what skills will be needed in the future and which jobs will be enhances by AI’s help and participation.

There’s a reason we moved from the cellphone to the smartphone – now we just need to be smart about the technologies we’re creating for the future.

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