The Magic Ingredient for Driving AI Success

Everyone is talking about AI, but what about the magic ingredient that makes AI intelligent in the first place?

If you’re plugged into the business and tech world, it’s almost impossible to escape the coverage of artificial intelligence (AI). From everyone’s favorite personal assistant Siri to Tesla’s AI-powered Autopilot, businesses across the globe are diving head first into new projects involving AI.

The enthusiasm surrounding AI extends beyond the business world as well. In the public space, AI has captured the hearts and minds of millions of consumers across the globe. As Microsoft Asia recently discovered, there is an entire generation of young consumers eagerly anticipating the maturation of AI—some even dream of one day having an AI-powered social companion.

Amidst all this buzz, what comes even more surprising is the comparable lack of conversation surrounding the magic ingredient that makes many of these AI-driven gadgets and gizmos possible: cognitive computing. Cognitive computing is what enables machines to “learn” and “think” as a human would through activities like pattern recognition, natural language processing and data analysis.

Without cognitive computing, AI and all these related technologies would be nothing. If machines can’t understand which data is important or what outcomes are desirable, the output is useless. And if they can’t be effective and efficient learners, then they won’t be able to process and synthesize all the relevant data today’s businesses are collecting. Cognitive capabilities are what make AI intelligent in the first place.

A Cognitive Foundation

As businesses look to capitalize on AI to harness the wealth of data they are collecting, the first step is embracing cognitive computing. However, this needs to happen at the foundational level of your technology stack if you want to make the best use of these cognitive capabilities. Every application your business deploys needs to be built from the ground up as a cognitive application—it shouldn’t be viewed as an afterthought that’s addressed at the end of development. Only when you begin developing applications with a “cognitive-first” mindset will you be able to truly harness the value of AI and reap the rewards.

Cognitive applications start with an AI architecture. Regardless of whether this foundation is built from scratch or on top of an existing system, it needs to encompass the necessary processes and tools such as machine learning, rules engines, natural interfaces and scalable, flexible backends. And the earlier cognitive capabilities are integrated into your application development process, the more connected your business will be as you are empowered to deliver AI-driven solutions and insights. Whether these applications are designed for internal use or built for consumer audiences, they need to be cognitive-ready.

As our CEO Yogesh Gupta said in his interview with SD Times, we see the future of business applications being cognitive-first. They will be developed from the ground up with cognitive capabilities, unlocking the applications to predict and anticipate business outcomes and thereby enabling enterprises to be even more successful. Just as the mobile-first approach has become standard practice these days, cognitive-first will be the standard of the future.

The cognitive era is on the horizon. We still have a long way to go before we get there, and there are many obstacles along the path. But it’s not that far away, nor are the obstacles insurmountable. It’s time to start thinking about how cognitive computing can impact the way your business operates.