Artificial intelligence (AI) is one of the most ubiquitous terms in circulation today. “We are presently living in an age of ‘artificial intelligence’,” writes Emily M. Bender (@emilymbender), a professor of linguistics at the University of Washington, observes, “but not how the companies selling ‘AI’ would have you believe.”[1] Arvind Narayanan (@random_walker), an associate professor at Princeton, adds, “Most of the products or applications being sold today as artificial intelligence are little more than ‘snake oil’.”[2] Eric Siegel (@predictanalytic), a former computer science professor at Columbia University, writes, “A.I. is a big fat lie. Artificial intelligence is a fraudulent hoax — or in the best cases it’s a hyped-up buzzword that confuses and deceives.”[3] And, author Greg Nichols (@gcnichs) writes, “Artificial intelligence is one of the most marketed (hyped, you might say) and ill-defined technology categories being packaged and lobbed at those in the enterprise these days. You might think overexposure would lead to fatigue and a healthy dose of skepticism.”[4] However, the opposite seems to be true. Journalist Jonathan Vanian (@JonathanVanian) reports, “Artificial intelligence is so important for business success, executives said in a [2019] survey, that most of them fear their companies will fail without it.”[5] From those comments alone, it should be clear that business executives need to understand exactly what they are buying when they invest in so-called AI solutions.

Some basic facts

Generally speaking, artificial intelligence is an umbrella term under which reside a number of different technologies and methodologies. Tech consultant Aydın Fevzi Özçekiç writes, “AI is a methodology. That means the methods behind AI are (mathematical) learning algorithms that adjust the parameters of methods via learning rules.”[6] Bender adds, “If the media helped us cut through the hype, what would we see? We’d see that what gets called ‘AI’ is in fact pattern recognition systems that process unfathomable amounts of data using enormous amounts of computing resources. These systems then probabilistically reproduce the patterns they observe, to varying degrees of reliability and usefulness, but always guided by the training data.” As an example of what Bender is describing, Charles Simon (@FutureAI3), CEO of FutureAI, points to Google search. He writes, “Google has the historical data of trillions of searches, and which results the user chose. From this, it can predict which searches are likely and which results will make the system useful. But there is no expectation that the system understands what it is doing or any of the results it presents.”[7]

Does that mean so-called AI solutions aren’t valuable? No. As Siegel explains, “The much better, precise term would instead usually be machine learning — which is genuinely powerful and everyone oughta be excited about it.” At Enterra Solutions®, we often use a term coined by IBM — cognitive computing. Cognitive computing platforms augment human decision-making by leveraging machine learning along with other analytical techniques. Kevin Kelly (@kevin2kelly), founding Executive Editor of Wired magazine, once tweeted, “In the very near future you will cognify everything in your life that is already electrified.” That’s a bold statement considering he had to make up a verb (i.e., cognify) to describe how the business world is going to change. Jennifer Zaino (@Jenz514) agrees with Kelly. She writes, “Cognitive Computing increasingly will be put to work in practical, real-world applications. The industries that are adopting it are not all operating at the same maturity levels; there remain some challenges to conquer. The wheels are very much in motion to make cognitive-driven Artificial Intelligence applications a key piece of enterprise toolsets.”[8] Because cognitive computing systems are adaptable and useful in a variety of situations, a few years back Accenture analysts predicted cognitive computing would prove to be “the ultimate long-term solution” for many of businesses’ most nagging challenges.[9]

Cognitive Technologies in Business

There is a growing consensus that “artificial intelligence” is becoming more of a marketing term than a technical term. Nevertheless, no one has come up with a more acceptable term that encompasses all of the technologies and methodologies currently residing under that moniker. The point to be reiterated is that companies need to understand what they are buying when someone claims to offer them an AI-based solution.

One of the most important capabilities offered by cognitive technologies is improved decision-making. Bain analysts, Michael C. Mankins and Lori Sherer (@lorisherer), assert, “The best way to understand any company’s operations is to view them as a series of decisions.”[10] They add, “We know from extensive research that decisions matter — a lot. Companies that make better decisions, make them faster and execute them more effectively than rivals nearly always turn in better financial performance. Not surprisingly, companies that employ advanced analytics to improve decision making and execution have the results to show for it.” Business journalist Adam Uzialko adds, “Rather than serving as a replacement for human intelligence and ingenuity, artificial intelligence is generally seen as a supporting tool. Although AI currently has a difficult time completing commonsense tasks in the real world, it is adept at processing and analyzing troves of data much faster than a human brain could. Artificial intelligence software can then return with synthesized courses of action and present them to the human user. In this way, we can use AI to help game out possible consequences of each action and streamline the decision-making process.”[11] Some of the most common uses of AI in business settings today include:

• Cybersecurity. Uzialko explains, “Artificial intelligence is an indispensable ally when it comes to looking for holes in computer network defenses. … AI systems can recognize a cyberattack, as well as other cyberthreats, by monitoring patterns from data input. Once it detects a threat, it can backtrack through your data to find the source and help to prevent a future threat.”

• Customer relationship management. Thomas “Ai Nerd” Helfrich (@instarel_ai), CEO and founder of instarel.ai, explains, “Thanks to artificial intelligence, businesses now take customer experience to the next level through customer insights. … Artificial intelligence is also changing customer relationship management (CRM) systems.”[12]

• Internet and data research. Uzialko writes, “Artificial intelligence uses a vast amount of data to identify patterns in people’s search behaviors and provide them with more relevant information regarding their circumstances. As people use their devices more, and as the AI technology becomes even more advanced, users will have a more customizable experience.”

• Digital personal assistants. According to Uzialko, “Artificial intelligence isn’t just available to create a more customized experience for your customers. It can also transform the way your company operates from the inside. AI bots can be used as personal assistants to help manage your emails, maintain your calendar and even provide recommendations for streamlining processes.”

Obviously, how AI is utilized will be different in various economic sectors. According to tech journalist James Connolly (@JimCon), the secret to getting the most out of a cognitive technology is to understand the problem needing attention and then leverage the right technology solution to address it. He explains, “As companies seek ways to use artificial intelligence, they will find AI is best applied to tasks that humans can’t do as well or don’t want to do at all. … In reality, advances in AI applications are more likely to happen when individual line managers or workers look at a single problem that is chewing up too much worker time or resources.”[13]

Concluding Thoughts

Özçekiç concludes, “Every organization should consider the potential impact of AI on its strategy and investigate how this technology can be applied to the organization’s business problems.” At the same time, Bender cautions, “It behooves us all to remember that computers are simply tools. They can be beneficial if we set them to right-sized tasks that match their capabilities well and maintain human judgment about what to do with the output.”

Footnotes
[1] Emily M. Bender, “Look behind the curtain: Don’t be dazzled by claims of ‘artificial intelligence’,” The Seattle Times, 11 May 2022.
[2] Dev Kundaliya, “Much of what’s being sold as ‘AI’ today is snake oil, says Princeton professor,” Computing, 20 November 2019.
[3] Eric Siegel, “Why A.I. is a big fat lie,” Big Think, 23 January 2019.
[4] Greg Nichols, “Why business leaders are short sighted on AI,” ZDNet, 15 November 2019.
[5] Jonathan Vanian, “Most Executives Fear Their Companies Will Fail If They Don’t Adopt A.I.,” Fortune, 14 November 2019.
[6] Aydın Fevzi Özçekiç, “AI as a Myth,” Data Driven Investor, 21 May 2022.
[7] Charles Simon, “Artificial intelligence really isn’t all that intelligent,” InfoWorld, 29 March 2022.
[8] Jennifer Zaino, “Cognitive Computing, Artificial Intelligence Apps Have Big Future in the Enterprise,” Dataversity, 17 September 2015.
[9] “From Digitally Disrupted to Digital Disrupter,” Accenture, 2014.
[10] Michael C. Mankins and Lori Sherer, “Creating value through advanced analytics,” Bain Brief, 11 February 2015.
[11] Adam Uzialko, “How Artificial Intelligence Will Transform Businesses,” Business News Daily, 18 February 2022.
[12] Thomas “Ai Nerd” Helfrich, “5 Ways Artificial Intelligence Is Radically Transforming Creativity in Business,” Entrepreneur, 27 January 2022.
[13] James Connolly, “AI: Find the Right Use for Artificial Intelligence,” RT Insights, 22 November 2021.