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54 R o y al R o a d s U n i v e r s i t y B C B U S I N E S S . C A M A R C H 2 0 2 5 "We are basically building models to predict any type of financial crime," he explains. "So I use them to predict money laundering transactions, mobile fraud trans- actions, securities fraud transactions and accounting fraud transactions. We're also using these same models to predict turnover in HR for companies, credit defaults, loan defaults and various other domains." Lokanan, an up-close observer of AI's growing power, offers a bigger-picture prediction for the future: these machines won't replace people in their jobs. "You cannot replace the human investiga- tive skills in a fraud case," he stresses. "You cannot replace the HR expertise you need. More and more, we are seeing that we need more domain expertise. And when I say domain expertise, I mean real qualifications." Why? "Remember, AI can't operationalize itself," Lokanan elaborates. "AI can pro- duce for you the insights that you need to make decisions. But for a fraud case, you need the accountants or the internal audi- tors to look at these insights." Lokanan's view sheds some light on a paradox in Statistics Canada's 2024 report on AI adoption by Canadian businesses. Nearly 40 percent of companies surveyed that used AI reported that AI reduced tasks previously employed by employees by a "moderate or large extent." Yet 84.9 percent of those AI-adopting companies reported no change in their head counts after adoption, and only 6.3 percent reported a reduction in the total number of employees. Lokanan argues that technology—like, for example, spreadsheet programs or accounting software—has historically freed people from tedious tasks to focus on work that requires decision-making and judgment. "AI is not going to take your job," Lokanan says. "It's probably going to auto- mate about 20 to 30 percent of your job, but you have to adapt." the videos it created of some of them, as the centrepiece of its award-winning 50th anniversary advertising campaign. ChatGPT's public release shortly after- ward marked a jump in the power of deep learning models, and a tipping point where they exploded into mainstream usage. Mod- els that can write and speak, like ChatGPT, and models that can produce fantastic photo-realistic images, like Stable Diffusion, are collectively known as generative AI. Companies in all manner of sectors are employing generative AI for an ever- expanding range of tasks. Expedia Group, for example, incorporates ChatGPT into its app to help travellers plan trips. Luana Carcano, academic director of undergraduate programs at SFU's Beedie School of Business, describes how genera- tive AI is starting to transform the fashion industry—a keystone of business and cul- ture in her native Italy. "Creativity is really the heart and soul of fashion, and AI can help, because it could be a brainstorming tool for creative people," she points out. Designers can tell computers to turn verbal descriptions or images into designs or illus- trations. They can experiment with design variations quickly and cheaply. In the fast-fashion side of the industry, where brands like H&M produce about 20,000 different styles annually, computing power will accelerate design and produc- tion, Carcano predicts: "It will help them to automatize some processes, but also to ana- lyze the big data that they have and create patterns faster than humans can do." Deep learning is already helping busi- nesses gain better insights and create new services and products. So what about the future? Royal Roads professor Mark Lokanan is creating AI models to predict it. Specifically, he's working to create models that comb through data to detect warning signs of financial crimes like fraud. But he can use the same methods to look at many other areas. "We are basically building models to predict any type of financial crime. So I use them to predict money laundering transactions, mobile fraud transactions, securities fraud transactions and accounting fraud transactions. We're also using these same models to predict turnover in HR for companies, credit defaults, loan defaults and various other domains." Mark Lokanan professor, Royal Roads

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