Principles for Artificial Intelligence Success

By Sunila Thelma Levi, CTO, Integral Care

From beer commercials to healthcare, AI has crossed over from movies to solving real life problems. AI’s role will grow in automation and process improvement at a new level. Machine learning and Natural process learning are its assets. It is a technology ready for adoption

Think process and process engineering in adopting AI. Do not patch work old processes with new technology. Think how process re-engineering can support adoption. Have a big strategy picture but think small in making changes. Single process, single system changes to impact single service delivered by the organization. This is where the ripple effect can start. Another principle to think through is to vet the question of ‘Why’ before you begin. Strategy should also have value-add. What is the “why” of the strategy? Why do we adopt AI? Spend time and effort? Process Improvement is not the ultimate answer. Improvements aligning with business goals of “growth and transform” can be the determining focus and motivation. Lastly do not neglect communication of adoption, remember that any amount communication is never enough!

AI? Is it for my organization? What? How?

Brief look into AI, the questions organizations and its leaders need to ask and answer on adoption.

Artificial Intelligence? Besides Terminator, Skynet and John Connor, Artificial Intelligence defined per wiki, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and animals. There is a progression to artificial intelligence, just like in humans, where learning consists of environment, language, vocabulary, and many other aspects. Learning is foundational to intelligence. AI Machines or systems supporting has to have a learning period. Understanding, thinking and intelligence come next. AI Systems  are of various types – learning systems - machining learning (ML), process languages - Natural Language Processing (NLP) etc. Their advantage is learning and processing at a much faster pace and making better connections through use of algortithms. Intelligence then results in applying learning to the situation at hand. Context is crucial in determining intelligence. Is the system-applying context to the learning or the facts it has to define the next best option to take? This decision-making and process is Artificial Intelligence.

Now that we defined Artificial Intelligence, where and how do we adopt to make an organization perform at higher levels of realizing efficiencies? In late 1900s and early 2000s, various technologies were adopted to make organization run faster and better, will AI be the technology to achieve next level of nirvana?

“The most important question to begin is not with what, where, how but the Why?”

The “Why” aspect of the technology is the first question an organization and its leaders have to ask in deciding whether the technology is right for adoption. This would be the million dollar, $M question to answer. Once this is defined, everything else is just work.

Artificial Intelligence is at play in Medicaid claims processing. AI is deployed to learn the format, standard values and recognize exceptions of a complex process. AI addition has reduced the rate of denials, streamlined claim approvers process and reduced manual verification efforts.

AI is also at play in call center solutions. Improving, assisting with pre, during, and post call processes. Pre call assistant notifies and gathers caller’s information so the crisis center call staff can make a better connection with the caller. During the call, AI assists with transcription and pulling relevant information for caseworker to assist with the conversation. With the data captured, post call analysis can become the breeding ground for innovation and process improvement for direct care.

AI can be an efficient tool in organizations tool belt. It does not have to be a buzzword and it does not require lofty initiatives and goals. AI can assist and support process improvements at much faster pace and leave to us, humans, to achieve the lofty, lifesaving goals.

So what can AI do for your organization? Start with behind the scenes operational processes. Where can it transform mundane and inefficient processes? However, start with question and main principle of defining ‘why”.