How to Explain AI, ML, and NLP to Business Leaders in Plain Language

Your capability to reveal artificial intelligence and its components to company leaders could suggest the change among acceptance and resistance. Here is how to do it.

When I pay a visit to with non-IT company executives and talk to them about artificial intelligence (AI), machine understanding (ML) and natural language processing (NLP), they inform me that they have initiatives underway. But they really don’t specifically know what AI, ML, and NLP are.

Striving to reveal what AI, ML, and NLP are, how they function, and how they produce benefits for the company is just not straightforward. Yet, all of these technologies have well known roles in analytics as IT deploys them. It is incumbent upon CIOs and IT leaders to find approaches to crack down these technologies and their company deliverables in plain language for non-technical stakeholders.

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How do you find straightforward approaches to reveal these technologies, how they function alongside one another, and why it would make company feeling to use them?

Listed here are some plain language explanations that could demonstrate handy.


AI is a computer procedure that can perform duties that had been previously carried out by humans. It performs in contexts the place the duties are repetitive, and the place the details to be reviewed is wide and would take lots of human guy-hours to method and digest. AI operates primarily based upon human-defined procedures and expertise programmed into it in the type of programmable logic and algorithms. AI are not able to perform effectively outside of the procedures that are defined for it the way that imaginative human reasoning can. That’s since AI strictly follows company procedures that consumers and experts system into it.

In company purposes, AI is most effective suited for highly customized certain use instances the place human experts outline very clear sets of company procedures.

A key case in point is a healthcare prognosis procedure that can pore via terabytes of details contained in healthcare journals, prognosis histories, and other details resources. The AI program evaluations all of this details in a portion of the time that it would take a human to do. Then the AI offers four or 5 attainable diagnoses for an elusive healthcare situation to a medical professional, who then employs his or her personal professional judgement, in live performance with collaborative conversations with other experts, to make the remaining prognosis.

AI can also be employed to predict weather styles primarily based upon weather historical past, to develop the most optimum vacation routes for logistics carriers, or to predict what e-commerce web site site visitors are most possible to invest in following, primarily based on their previous obtaining styles and what they’ve browsed on the web site.

A greater part of firms begin their AI deployments by working with AI for analytics. As firms achieve far more encounter, they seek to “train” their AI by introducing machine understanding, which is a sub-class of AI that enables the AI to achieve further insights into details on its personal by recognizing recurrent pattens of details and then drawing conclusions (and “understanding”) from these conclusions.


Equipment understanding is a sub-class of AI that enables an AI procedure to learn and adapt to new details and gatherings so the AI can come to be “smarter.” The ML element of AI learns by observing repetitive details styles, and then implementing a established of algorithms and logic created by human experts that enable it to make decisions primarily based upon the repetitive details styles it is observing.

An case in point in a logistics situation is a recurrent sample at a distinct highway intersection the place there are generally targeted visitors delays. If the sequence continues to recur, the ML element of the AI is possible to detect the sample and to conclude that it is improved to reroute targeted visitors a further way so that the busy intersection can be averted.


Like machine understanding, natural language processing is also a sub-class of artificial intelligence. NLP is employed to have an understanding of, interpret, and manipulate human language.

An case in point of this is SIRI on an Iphone. The SIRI NLP element of AI is able to recognize your human voice command and reply in kind in the same language.

Other NLP examples involve automatic telephone and chat methods that recognize human languages and carry out automatic conversations with you, or a home security procedure that acknowledges and responds to human voice commands 

NLP alongside one another with AI’s usual details processing and analytics is able of automating many company processes that include the studying, talking, and crafting of language.

Bringing it all alongside one another

Though at 1st glance lots of of these AI, ML, and NLP conversations may feel extremely simplistic to IT professionals who are employed to conversing in acronyms and technical abstractions, conversations like these can be instrumental in attaining and retaining government, board, and conclude-person guidance for AI, ML, and NLP projects.

Most importantly, plain language conversations that url the engineering to the company are essential for eradicating the feelings that lots of company executives and conclude consumers have about AI, ML, and NLP remaining mysterious “black containers.”

“A good deal of senior executives and company leaders these days are almost determined to have an understanding of how AI might have an effect on their corporations,” stated Thomas W. Malone, director of the MIT Centre for Collective Intelligence. “I believe leaders are increasingly apprehensive in lots of instances that if they never figure out how to use AI correctly, they’ll be remaining powering.”

For far more on AI in the enterprise, study:

How Information, Analytics & AI Shaped 2020, and Will Impression 2021

A Concern for 2021: Where’s My Information?

How to Develop a Profitable AI Application

Analytics Salaries Regular Amid COVID Disaster

Mary E. Shacklett is an internationally regarded engineering commentator and President of Transworld Information, a internet marketing and engineering providers agency. Prior to founding her personal corporation, she was Vice President of Item Analysis and Application Improvement for Summit Data … Check out Comprehensive Bio

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