For years now we have heard about the promise of Artificial Intelligence and the many potential uses there could be for it. Until recently, A.I. development has been primarily academic or scientific in nature. One of the more visible applications of this is with autonomous, or self-driving cars. But now we are starting to see A.I. being deployed and used at an enterprise level to help solve practical business issues and needs.
Massachusetts General Hospital is partnering with GE Healthcare to develop and integrate A.I. in their clinical operations. One example they are pursuing is enhanced diagnostic imaging, with systems capable of detecting even the slightest change in the body (such as tumor growth) and then using data analysis to determine optimal treatments tailored to the individual. Farmers Insurance is embracing A.I. to transform how they deliver services and meet customer expectations.
LinkedIn is a company that understood early on the value of A.I. and embraced it as a platform to help them provide a better user experience by employing machine learning to power many of its features such as ranking search results, selecting appropriate advertisements and news feeds, and recommending potential connections for each member.
However, A.I. in the enterprise is far from being mainstream. A recent PwC survey showed that 72% of US business and consumer leaders believe A.I. will be their biggest business advantage in the future, but very few of those companies have begun or are very far along in employing A.I. systems yet. There are several reasons for this. First, many IT leaders are skeptical of the value and/or benefit from A.I. Second, the investment necessary to implement and deploy A.I. solutions. Companies have to either build or buy their intelligent platforms, as well as procure new computing power to drive those platforms. Third, a proper foundation must be in place for A.I. to be successful e.g. robust data structures, new expertise/skills needed, and cutting-edge software and hardware. Those can be big investments for companies, so many take a measured approach to building their intelligent infrastructure.
So while we are starting to see A.I. beginning to be put to practical use in some industries, it still has a long way to go before it becomes commonplace in the enterprise solving complex business issues. The companies that start investing now will be in a much better position to take advantage of these technologies as they continue to grow and mature. Companies that do not start making these investments may be at a competitive disadvantage in the future. The next 3-5 years will be very interesting to see the impact A.I. will have on the enterprise IT landscape. Here at RUMJog, we believe that when it comes to the adoption of technologies like A.I. for the enterprise, it is expensive to be early, but it could be fatal to be late. We will continue to study and monitor the evolution of A.I. technologies and their impact.