AI and data innovation:
How to avoid the risks of going “all in” too early?
AI and business value are vital to securing future competitiveness and productivity. But like all forms of innovation, using AI and data intensive technologies are not without risks, so business leaders must carefully consider how they will make the best returns from their early AI innovation projects.
Common sense tells us that gambling without understanding the risks involved is a quick way to lose money. For this reason, savvy business leaders only invest in any new proposition or technology once they fully appreciate what had already been successfully achieved by other early adopters.
Faced with this challenge how do businesses avoid the trap of going “all in” on A.I. too early?
In the current race to successfully deploy AI there is a lot of hype about the tremendous potential of AI and data, but sadly there is also a dearth of useful information on what’s been successfully achieved to date. Indeed, when the competition to successfully adopt AI is so intense, opportunities to learn from others, who have useful and relevant experience to share, are hard to find.