Artificial intelligence is the future of business — that much is clear. In the next year, more than 31 percent intend to adopt some form of AI, according to Adobe, and a whopping 72 percent of company leaders believe that AI is going to be “fundamental” in the future. But as enterprise barrels toward an AI future, how is it changing product development and business models?
A panel of experts attempted to answer those questions at VentureBeat’s Transform 2018 summit. Among them was Faizan Buzdar, senior director and platform manager at cloud storage provider Box; Wilco van Duinkerken, head of product at Trivago; Jon Fasoli, director of product management at Intuit, and Jana Eggers, CEO of Nara Logics.
For Buzdar, AI’s effects on the business stack are “already palpable.” He’s in a position to know: Box recently acquired Butter.ai, a contextual search service powered by machine learning, to improve its real-time filing filters. (Butter.ai’s technology is designed to help businesses search across multiple enterprise services, such as Google Drive, Trello, Evernote, Confluence, and Dropbox.) And in June the company formally launched Box Skills, a suite of apps that add new features and functionality to cloud-hosted files — including an image-processing Skill that uses Google’s Cloud Image API, an image and document analysis school powered by IBM’s Watson, and an audio-based Box Skill that leverages Azure for speech.
“It’s about enabling companies to experience machine learning faster,” Buzdar said. “Think about data entry. When you replace it with machine learning, the validation process looks [the same] — you [as a business] saved a lot of money.”
From Trivago’s perspective, data is the valuable fuel that drives the AI machine. As Van Duinkerken explained, its travel platform improves with more interactions. The more it knows about travelers’ propensities and preferences, the better it can tailor results to them. It recently made key acquisitions on that front. In May it bought TripHappy, a U.S.-based startup that analyzes more than 25,000 neighborhoods in more than 10,000 cities to secure personalized bookings for travelers. And it acquired Tripl, a technology firm that generates travel recommendations from users’ social media accounts, in September 2017.
Van Duinkerken noted that AI systems have to be implemented carefully, though. Without an appropriate degree of vetting and transparency, biases can creep into datasets and algorithms.
Fasoli agreed: Algorithms have the potential to “automate monotonous tasks” and “boost profitability,” he said, but if business leaders aren’t educated about the potential pitfalls, the results could become effectively useless.
Eggers took a slightly more optimistic view. She cautioned against uninformed enthusiasm for “buzzy” trends like deep learning and neural networks but said that despite the challenges ahead, AI stands to be transformative — particularly in retail and finance.
Nara Logics, a Boston-based company specializing in content matching, uses AI to power its product recommendation platform. It managed to double the conversion rate of beauty company Olay, and with Skin Advisor it increased average customer basket size by 40 percent in China alone and cut the bounce rate of visitors to a third of what it was previously.
“My recommendation [to businesses]: Hire some great software engineers who will be excited about using AI,” she said.