It’s not just the stuff of futuristic IBM or Intel TV commercials: Artificial Intelligence (AI) technologies are indeed driving the next wave of digital transformation in the business world. And businesses that are already moving forward with cloud-based solutions and embracing big data analytical capabilities will be best positioned to be early adopters.
Companies that have caught the first wave of digital transformation already understand the importance of the convergence of various digital technologies. Cloud computing, data analytics, mobile, social media and multi-channel digital marketing lead businesses to cultivate a digital mindset. Such companies likely have also already adopted tech-centric operating practices like use-case driven product development, agile product delivery and data-driven decision-making. The results, ideally, lead to faster delivery and superior customer experiences.
At the same time, by the mid-2000s a number of AI-powered applications hit the consumer market, with products like Siri, robotic vacuum cleaners and internet-connected home devices. Having proven its value in the consumer world, AI was put to work in a number of business applications, from customer-facing interfaces and predictive data analytics to expert advisors analyzing complex medical and legal matters.
Today, continued advancements in AI technology are helping businesses deploy new user interfaces that are more natural and simple to use. Not only are interfaces becoming more intuitive, the underlying technologies are capable of self-learning, understanding the context of user journeys and, ultimately, reasoning toward desirable outcomes, be they conversions, frictionless experiences or deeper audience engagement.
We have seen AI technologies having an impact in virtually all business segments. JPMorgan’s Chase banking group has developed a contract intelligence system called COIN, which parses financial agreements. The COIN system does in seconds what took lawyers 360,000 hours to do. In agriculture, Blue River Technology’s AI-enabled crop management system LettuceBot helps farmers increase yields by removing weeds and sprouts less likely to thrive and applying plant-by-plant fertilizer where needed. Memorial Sloan Kettering’s cancer center uses the Watson Oncology system to help physicians interpret patients’ clinical information and identify individualized, evidence-based treatment options.
Businesses can think about adopting AI technologies in a couple of ways—as embedded capabilities or custom-developed solutions. The easiest and quickest path involves staying the course with overall digital transformation by moving to cloud-based, data-rich environments. Businesses that are already well along that trajectory will reach the next level more organically and with less disruption. This is because mature AI capabilities (machine learning and natural language processing) will be increasingly available as embedded components in commercial solutions.
The case for custom developed solutions is more challenging. This involves integrating new AI and cognitive computing technologies and filling skill gaps within existing product development teams. Perhaps the best approach would be to develop basic AI capabilities within the UI/UX team and to take advantage of the wealth of AI tools and APIs freely available from the open source community.
No matter what business you’re in, AI will present many opportunities in the not-too-distant future. To prepare, think about the kinds of applications that would most benefit your business, do some research and watch how AI is being implemented in your industry. And if you’ve already adopted some AI tech, let us know how it’s working out.