What does AI do? - Part I of The Business Leaders Guide to AI

A weekly series of 5min reads on AI. No buzzwords. No hype. No fluff.

One of the biggest challenges to understanding AI is that its benefits are so widespread.

It's not theory or exaggeration to say that with the right data and strategy, AI can help any company in any industry be more competitive.

"How can AI possibly help any company in any industry? This article must be just more AI hype."

Much as the internet is a tool businesses use to share information, AI is a tool used to analyze information

Think about the internet. These days virtually every company in every industry relies on the internet. It's become so commonplace we don't even give it a second thought.

The internet is its own broad and complex technology, but from a business perspective, the internet is fundamentally a tool to share information. It can be used to optimize virtually any business process by sharing information 100x faster and easier than legacy technologies.

For example, Amazon changed the game because customers no longer needed to make a phone call or physically visit a store to communicate information about what they wanted to order.

In a similar light, AI is a tool to analyze information. It too can be used to optimize virtually any business process by analyzing 100x more information, 100x faster than humans. This is important because it enables companies to make more informed decisions. For the first time, it is possible for companies to make decisions that consider more information than humans, and in such little time that they can be embedded in real-time business workflows.

For example, Amazon uses AI to analyze the information about customer orders to optimize sales, marketing, product, and customer service functions. Amazon's recommendation engine is one example of this we can all relate to - imagine how impossible Amazon's recommendations engine would be to implement with humans deciding what to suggest rather than AI - but this example is far from the only way AI is useful.

Don't trick yourself that AI can only help certain industries or companies (like eCommerce or Amazon). That's like saying the internet is only useful for eCommerce!

Obviously this analogy between the internet and AI only goes so far. Though both technologies can optimize generally any business process, they do so in very different ways. But there is a key takeaway from how the analogy breaks down as well.

Whereas sharing information (the internet) primarily changes how work is done, analyzing information (AI) primarily changes why work is done.

In other words, just because customers now shop online doesn't mean business still don't need to sell products. Businesses still need to make decisions such as "Do we carry Product A or Product B?"

Without AI, human business leaders and employees would make those decisions using some combination of:

• personal opinion
• experience
• intuition
• data, analytics, or evidence

"Why was Product B launched? Why was Project X prioritized?"

Traditionally, because of the boss' personal opinion or subjective belief, perhaps based on some (if any) anecdotal evidence.

AI fundamentally changes this, typically not by replacing human leader and decision, makers, but by augmenting the amount of empirical evidence and information they can weigh in making each decision.

This is what AI fundamentally does in business. It enables more informed, more rapid decision making for any business question. From the mundane ('which product to recommend?') to the strategic ('what is our market most receptive to?')

As you can imagine, adopting AI solutions thus brings both amazing new opportunities... as well as its share of new challenges, many of which are not technological in nature.

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This is part of a weekly LinkedIn series, The Business Leaders Guide to AI. If you have found this helpful or thought-provoking in any way I'd love to hear from you in the comments.

Even more importantly, if you have suggestions, requests for future topics, or found this unhelpful in any way I'd especially love to hear from you. Please drop a comment (was it too theoretical? too simplistic? too technical? not technical enough?) or, if you prefer, message me on LinkedIn.

Thanks for reading.