Long thought of as a tool for improving operations, AI is beginning to play a role earlier in the enterprise process, closer to product design.
Harnessing the analytics capabilities of AI to design new products and services is a promising frontier in enterprise IT, according to Boston University Questrom School of Business professor Marshall Van Alstein speaking at the MIT Sloan CIO Symposium on Monday.
By integrating internal data silos and drawing on external data sources, companies can create dynamic AI ecosystems, drive innovation, improve efficiency, and create new business opportunities.
Most organizations moving AI closer to product design are digitally native, but some legacy companies are still following this model, said Thomas Davenport, professor of information technology and management, Babson College.
Targeted advertising, customer service automation, quality control and logistics are all areas where AI has proven its commercial usefulness. When combined effectively with big data, AI can reshape the way companies develop products.
To keep up with Uber, eBay and Facebook, which are already using AI extensively, legacy companies such as Airbus, Anthem and DBS Bank are working AI into their systems.
“It’s like the Disneyland of data in this environment,” Davenport said. “It can improve your AI model, which allows you to improve your services, which reduces customer friction, which helps you get more customers, which gives you more data.”
This noble circle has created entirely new marketplaces, primarily through ML-powered search functions that enable e-commerce, using data to match buyers with sellers on sites like Amazon and eBay. . While AI recommendation systems remain a powerful business tool, new ways of thinking about AI technologies are gaining ground.
In design, beyond recommendations
Netflix is an example of a business built around an ML recommendation algorithm. The company began combining AI with growing data assets to create streaming content to help guide the development process, most notably in the production of the critically acclaimed show “House of Cards.”
Amazon similarly relied on AI for “The Marvelous Mrs. Maisel,” Van Alstein said.
“A recommendation system takes existing products and tells you what will be successful. But you can also use a recommendation system to create products that don’t exist yet. So, you can turn it upside down and vice versa. ,” Van Alstein said.
For companies committed to combining AI with cloud-based APIs, gains in revenue and market cap could be significant. A 2021 study co-authored by van Elstein, which analyzed 200 firms adopting APIs, found that allowing AI to learn from third-party interactions led to a 4% increase in market cap over two years and 38% over 16 years. increase was observed.
But there is a cyber risk catch. “When you externalize the API, there is a 1.2% chance of getting hacked every month. You’re going to get a huge profit, but it’s something you have to manage,” Van Alstein said.
According to Vipin Gopal, chief data and analysis officer at Eli Lilly & Company, companies that can’t afford that level of risk can still profit. Gopal sees opportunities for large organizations within the pharmaceutical industry to make major profits by sharing currently muted data.
“It’s something we see across the industry,” Gopal said. “Different parts of the organization grew up in silos – the research side, the clinical development side, the packaging and the commercial side. There exists a vast amount of data in different parts of the organization that are largely disconnected.”