Your ability to explain artificial intelligence and its components to business leaders could mean the difference between acceptance and resistance. Here's how to do it.
When I visit with non-IT corporate executives and ask them about artificial intelligence (AI), machine learning (ML) and natural language processing (NLP), they tell me that they have initiatives underway. But they don't exactly know what AI, ML, and NLP are.
Trying to explain what AI, ML, and NLP are, how they work, and how they deliver results for the business isn't easy. Yet, all of these technologies have prominent roles in analytics as IT deploys them. It's incumbent upon CIOs and IT leaders to find ways to break down these technologies and their business deliverables in plain language for non-technical stakeholders.
How do you find easy ways to explain these technologies, how they work together, and why it makes business sense to use them?
Here are some plain language explanations that could prove helpful.
AI is a computer system that can perform tasks that were formerly performed by humans. It works in contexts where the tasks are repetitive, and where the data to be reviewed is vast and would take many human man-hours to process and digest. AI operates based upon human-defined rules and expertise programmed into it in the form of programmable logic and algorithms. AI cannot perform well outside of the rules that are defined for it the way that creative human reasoning can. That's because AI strictly follows business rules that users and experts program into it.
In business applications, AI is best suited for highly tailored specific use cases where human experts define clear sets of business rules.
A prime example is a medical diagnosis system that can pore through terabytes of data contained in medical journals, diagnosis histories, and other data sources. The AI software reviews all of this data in a fraction of the time that it would take a human to do. Then the AI presents four or five possible diagnoses for an elusive medical condition to a physician, who then uses his or her own professional judgement, in concert with collaborative discussions with other experts, to make the final diagnosis.
AI can also be used to predict weather patterns based upon weather history, to develop the most optimal travel routes for logistics carriers, or to predict what e-commerce website visitors are most likely to purchase next, based on their past purchasing patterns and what they've browsed on the website.
A majority of companies begin their AI deployments by using AI for analytics.
