In 2022 artificial intelligence (AI) will create a whopping $3.9 trillion in value for businesses, plus 6.2 billion hours of worker productivity, according to Gartner. The value and capabilities of AI have evolved rapidly over the past two decades. No longer is AI a purely academic experiment or the plot of a sci-fi movie. Instead, AI is fast becoming a standard component in everything from stock trading applications to smart cars.
IDC predicts global spending on AI will more than double over the next four years, from $50.1 billion in 2020 to more than $110 billion in 2024. Software and cloud services vendors are implementing AI in a wide range of products. According to International Data Corp. (IDC) the leading use cases for AI are:
- Automated customer service agents
- Sales process automation
- Automated threat intelligence
- General IT automation
Other common uses for AI include healthcare diagnostics, fraud detection in financial services, natural language processing for human interaction, personalization in marketing and ecommerce, robotics, pharmaceutical research, agriculture, oil and gas exploration, predictive maintenance for equipment, and many, many others.
How experts see artificial intelligence’s impact on business
The current and future value of AI in business was the topic of a panel discussion at TierPoint’s September BraveIT 2020 virtual conference. IT executives and AI experts shared insights in the session AI applications have arrived for your business. The participants included moderator Jonathon Beckham, an attorney with GT law who specializes in technology and intellectual property, and panelists Ankur Dinish Garg, Chief of AI at Sonasoft, Bob Schukai, SVP Identity Solutions for Mastercard and Darius Withers, senior in-house counsel for technology at Accenture.
According to the panelists, AI with machine learning provides the most value in situations that require real-time decision-making based on large volumes of data and multiple or complex variables. While the human brain is good at dealing with complex questions, it’s not always able to do so quickly. AI, however, can make real-time decisions that involve gigabytes or terabytes of data and multiple variables. That capability is highly useful in all sorts of industries and business applications.
The panelists highlighted three major industries that are getting big benefits from AI, both now and in the near future.
Applications of AI in Financial services
Research company Omdia predicts that financial services organizations will spend more than $9 million of AI software in 2025. Banks, insurers, mortgage lenders, and other financial services firms use AI technology to optimize their often complex processes, detect anomalies quickly to prevent errors, and even do predictive analytics for such things as identifying factors that might affect the outcome of future claims or reducing losses from fraud.
Stock trading is a prime example of using AI to work through multiple dynamic, and often conflicting variables. Financial Services professionals in charge of stock portfolios can leverage AI software to evaluate an array of information, including market reports, analyst notes, stock trends, and corporate research, to make investment decisions based on each customer’s goals.
AI is also helpful in fighting financial fraud. An AI engine can learn to detect patterns, spot anomalies, and determine whether a transaction might be fraudulent.
“Fraud detection is a matter of authenticating the person and looking at the variables in the transaction—where is it coming from, has the person bought things like this before, has the card been popping up on a bunch of different IP addresses—and deciding whether to accept or reject the transaction,” explained Schukai.
Applications of AI in IT operations
Network and data center management is another major market for AI. The telecom industry alone will spend $36.7 billion annual in AI products and services by 2025, according to Tractica. Large data center companies as well as cloud services providers and cybersecurity companies all use AI extensively.
“AI is very important in networking and the data center space and in any other place where data is flowing and you can’t rely on human response time,” explained Garg. “AI can interface on the fly,” said Garg.
Cybersecurity applications and services need AI to sort through complex data and transactions to identify possible hacks, suspicious end user behavior, or incoming cyberattacks. Cybersecurity requires learning the behaviors of applications, end users, and machines, accessing databases of known threats, and making near instantaneous decisions. Humans can’t operate that quickly, but AI can.
Also read: New Cybersecurity Challenges: 5G, IoT and AI
Applications of AI in Education and Human Resources
AI is useful in human resources, worker training, and professional development. One new AI-powered application, called Avenues, trains social workers through virtual reality scenarios using an Oculus VR headset, natural language processor, and a database of past child welfare cases. The social worker is confronted with various domestic situations and asked to decide on the best course of action, such as remove a child from the house or offer parents different support services. Created by Accenture, the Avenues application takes social workers through an immersive training experience that includes much of ambiguity and stress of real-life situations but allows them to practice making the tough decisions without real-life consequences.
“As technology improves, we’ll see this used in other learning environments—pilots, truck drivers, you name it,” said Withers.
Challenges ahead: transparency and consumer trust
Businesses will soon need to provide greater transparency into how their AI engines make decisions. Most new technologies over the years – the Internet, WiFi, online banking, even search engines—have been easier for consumers to comprehend. At the same time, AI is increasingly controlling people’s stock portfolios, mortgage approvals, healthcare coverage, and even the operation of their smart cars. Consumers will demand a greater amount of transparency into how these AI engines are making their decisions, said panelists.
“This is one of the biggest challenges,” said Schukai. “It will require our industry to open up and lay bare how things work.”
That demand for transparency will push government agencies to become involved and force AI vendors to develop ways of auditing their technologies.
“Auditing is a very important requirement,” said Garg. “Regulatory agencies need to be able to handle AI. They need to look at why did the AI take a specific action, whether there’s a bias or not, and how do we ensure there isn’t bias.”
Blockchain may offer a solution to how to audit AI. Blockchain is a digital ledger that can enable auditing of transactions and data, as well as ensure security. With blockchain, auditors could determine why certain decisions were made and what information was used to make them.
“Blockchain may be the missing link between AI and trust,” said Garg.
Despite the challenges, Garg and the other panelists were upbeat about the future of AI and the industry’s willingness to implement auditing and other methods for improving transparency and consumer trust.