From chatbots that answer our questions to emails that write themselves, AI is increasingly present in our lives — and the advent of startlingly sophisticated and headline-making tools like ChatGPT suggest that presence is likely to grow.
As it stands, the technologies are advancing at a seemingly breakneck pace, impacting sectors as diverse as public health and transportation. Given the spread, it’s easy to assume AI could be used by just about any company — and there are plenty of adoptees.
The 2022 McKinsey Global Survey on AI reported in December that although it has stabilized in recent years, the proportion of organizations adopting AI in at least one business area has more than doubled since 2017.
Furthermore, “the average number of AI capabilities that organizations use has also doubled — from 1.9 in 2018 to 3.8 in 2022,” the report found.
But what are companies actually using AI for? And, what are some critical questions experts say companies should ask themselves before going all-in?
Let’s take a closer look.
Why AI is becoming increasingly useful
One reason AI is becoming especially useful is because by definition, it is the ability of machines to learn and make decisions based on data and analytics. And it should come as no surprise that companies now have access to more data than ever before.
How much more? Well, Gil Press — a senior contributor with Forbes — reported toward the end of 2020 that in the 10 years that came before, “the amount of data created, captured, copied, and consumed in the world increased from 1.2 trillion gigabytes to 59 trillion gigabytes.”
That’s almost 5,000 per cent growth, Press said.
And with the help of emerging technologies like AI, the University of Pennsylvania’s Wharton Online explained, companies are now able to capture user data that can help them make informed business decisions.
“AI is no longer an experimental technology only used by select brands,” it said. “For many companies around the world, it has become a core part of their operations.”
AI: What is it used for?
So, how is AI being used by companies and organizations?
Common applications cited by Business News Daily include the detection of cyberattacks and threats, digital personal assistants that manage calendars, and customer service chatbots.
The latter is also where some companies are using ChatGPT. Bloomberg reported on March 1 that the technology has already found a home on apps for Instacart, where customers will be able to ask it questions about recipes; Shopify, where it will offer suggestions; and Quizlet Inc., where it will provide users with a “tutoring experience.”
In more specialized fields like healthcare, AI’s uses include helping to make potentially life-saving cancer diagnoses. The New York Times reported on March 5 that AI known as “computer-assisted detection” is helping to detect breast cancer missed by mammograms.
More generally, some popular uses for AI include service operations optimization, contact centre automation, customer service analytics, sales and demand forecasting, and risk modeling and analytics, according to the 2022 McKinsey Global Survey on AI.
And when it comes to deciding how to apply AI, Wharton Online reported that companies often focus on driving growth.
That growth, according to Entrepreneur’s Auria Moore, is focused on three central areas:
- AI-powered analytics, which can allow businesses to gather information about users for better product creation.
- Customer service satisfaction, where AI chatbots can provide answers to users faster.
- Targeted digital marketing campaigns, which has AI granting marketers the ability to “enhance personalization at an individual level.”
Meanwhile, supply-chain management is where the highest-reported cost benefits from AI were identified in the McKinsey survey — while “the biggest reported revenue effects are found in marketing and sales, product and service development, and strategy and corporate finance.”
“The bottom-line value realized from AI remains strong and largely consistent,” the report said.
“About a quarter of respondents report this year that at least 5 percent of their organizations’ [earnings before interest and taxes] was attributable to AI in 2021, in line with findings from the previous two years.”
What to consider before going all-in
Given its vast possibilities for application and seemingly limitless potential, investing in AI could seem like a no-brainer for businesses. But some experts warn that it shouldn’t be.
“The first question to ask yourself when considering AI is what problems might be solved with the technology,” Inc.’s Ben Sherry reported last May.
While some companies would find AI genuinely useful — for example, Sherry said, an e-commerce company could use it to market specific products to customers based on data — others could wind up with an unnecessary expense.
“Ask yourself if automating part of your business has an easily identifiable benefit, or whether you have routine tasks that could easily be automated,” he suggested.
AI’s algorithms also need a lot of high-quality data to deliver valuable insights, Open Data Science (ODSC) explained in November 2021, and machine learning needs varied data to build its intelligence.
So before investing in AI, ODSC said, it’s critical to make sure your company has access to a sufficient amount of high-quality data sets.
“Without data and specifically, high-quality data, your AI investment is useless,” ODSC said.
“It’s essentially like purchasing an expensive car with an incredibly powerful motor without any access to a fuel source.”
Finally, some experts say a critically important question for companies considering AI to ask themselves is: what are the consequences if it fails?
“AI models work through very sophisticated algorithms and statistical correlations, but there is always a margin of error. Does the company want to implement AI in a process with high variability and a low accuracy rate, or the opposite? What risks and how much investment would be lost if it didn’t work out?” industrial IoT company Nexus Integra asked in a blog post.
“Depending on which systems and data are available, the company must evaluate whether the accuracy of these models is expected to be high enough to proceed.”
And Ricardo Baeza-Yates, director of research at the Institute for Experiential AI at Northeastern University, wrote in an August 2021 piece for Forbes that “as the usage of AI grows exponentially, so have the number of AI incidents.”
As such, Baeza-Yates said companies looking to use AI should first ask themselves if they have deeply considered the direct, and indirect, impact of their product or service.
“Here, the accuracy of your model is irrelevant. What matters is the impact of the mistakes you make, even if they are few,” he wrote.“In cases where people were falsely accused by facial recognition systems, killed by driverless cars or unethically targeted for fraud, the damage was severe and lasting.”