Artificial Intelligence (AI) is everywhere, from social media platforms using AI to analyse content and behaviours, to digital platforms like Amazon and Netflix that use AI for their recommendation engines. With (now) quantifiable benefits and proven success stories like the ones just mentioned, the investment in Artificial Intelligence continues to grow and is climbing higher and higher in the agenda of CXOs across global enterprises.What we are also seeing however is that although companies have realised that there is significant value in data, they are not as clear yet on how exactly to use the data in order to extract that value. This is a common problem we are seeing across different sectors; companies will procure a platform, ingest the data, but they’ll have no clear plan on how to monetise this data. This lack of clear strategy and planning often leads in delays, frustration between teams, and no ROI.
On the other hand, there are shining examples from sectors as diverse as trade floors, call centres and health care, that have been successfully using AI for some time now. In fact, US-based Crown College has been using Predictive Analytics since 2015 to retain at-risk students and as a result improving retention rates by 5% so far.
Growth potential of Artificial Intelligence
There is no doubt that applications driven by Artificial Intelligence will continue to grow and proliferate. In the next few years, AI will increase security, generate new services, empower businesses, improve healthcare, facilitate sustainability, blend the lines of digital and physical and make us smarter.
The most prominent developments we expect to see are around:
Tipping the scales
So how can business leaders ensure successful results from their AI investments? From our experience these are the four key areas that might tip the scales of success:
Final thoughts
Artificial Intelligence (or any other technology for that matter) can never be a silver bullet. AI is definitely helping solve problems that were difficult or impossible to solve in the past, but it’s still not a one stop solution for all the problems. It can only be an additional tool in the kit for tracking and addressing persistent challenges.
As with any technology, it is important to set the right expectations, and this is especially true for AI. One way of doing this, is by understanding more about it before developing and executing AI within your business.