How eBay uses generative AI to make employees and online sellers more productive (2024)

Messaging matters to eBay chief technology officer Mazen Rawashdeh when he talks about the predicted productivity gains from artificial intelligence. Instead of being enthusiastic about AI, some of his colleagues are apprehensive.

“A lot of people get nervous around AI,” says Rawashdeh. “We shift how we talk about gen AI: This is a tool that is going to help you enjoy the job you do.”

It’s the balancing act that executives at many companies are performing these days as they adopt AI. How do you get everyone on board with a technology that many fear will replace them?

When talking to his software development team about eBay’s generative AI tools, for example, Rawashdeh says he focuses less on those efficiency gains and more on their career development opportunities. Gen AI can elevate the programming skills of junior and mid-level engineers more quickly than was possible before.

A few times during our conversation, Rawashdeh predicted that eBay’s software developers will be 15% to 20% more productive within the next two years thanks to AI. To achieve those gains, eBay has relied partly on GitHub Copilot, an AI-enabled developer tool that can autocomplete code for programmers so they can do their jobs faster.

But the code the technology produces can be a bit generic, says Rawashdeh. The AI doesn’t necessarily understand how eBay does things.

That led Rawashdeh to create eBay Coder, which relies on an open-source large language model that’s trained on over 250 million lines of eBay code. This generative AI tool is better at helping with tasks like code migration or transferring software code between different operating systems or frameworks.

Beyond boosting productivity for developers, Rawashdeh says there are three other generative AI priorities he’s focusing on: improving customer service, scaling the company’s tech infrastructure, and gleaning better insights from customer data to improve the online shopping experience for them.

With nearly three decades worth of customer data in the vault, eBay has a lot of data to sort through. At any given time, there are more than 2 billion product listings on the company’s site and more than 130 million active buyers and sellers. EBay has been using AI to improve search, create more personalized ads, and much more recently, make it easier for sellers to list items on the platform.

Among those newer tools is its “magical listing” feature, which was introduced last year and lets sellers upload a photo and then rely on AI to generate the description to go along with the product listing. Generative AI also recommends listing prices and shipping costs, though the seller has the final say on everything that appears in the posting’s final form. And in June, eBay unveiled a new feature that lets sellers replace image backgrounds with an AI-generated backdrop. An image of soccer cleats sitting on a drab living room floor, for example, can be altered to appear in a more visually appealing grass field.

Rawashdeh says that before generative AI, eBay had billions of signals about what consumers bought and sold, and the feedback that they’d share with eBay about their experience on the site. But it was impossible for his teams to look at that data in its entirety and make good decisions, he said. Generative AI, he believes, will increasingly help eBay sort through that massive data trove and find useful insights.

EBay is agnostic about who it will work with for generative AI. It partners with Microsoft for GitHub and buys AI data center infrastructure from Nvidia, for example. Rawashdeh says he decides based on what will create the greatest value for customers. From there, he sorts out whether to buy or build software and, if necessary, then decide what vendor to work with.

“My bias is always towards build,” says Rawashdeh, who says eBay relies on a mix of commercial and public large language models and builds its own LLMs.

Rawashdeh is a “boomerang” employee at eBay. He first joined the retailer in 2003 but left in 2011 to work for Twitter, now known as X. He was lured from eBay by the social media company’s fast growth and assorted challenges related to tech and workplace culture that he wanted to help untangle.

After nearly five years at Twitter, Rawashdeh says he left to put more effort into investing in startups and serve as a board member. His intention was to retire, but he quickly returned to eBay in 2016 for his second stint. That also led him to fulfill a dream he had when he first joined eBay.

“I wanted to be a CTO,” says Rawashdeh, who finally became one at eBay in 2019. “That was one of my goals.”

John Kell

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NEWS PACKETS

Smaller, cheaper AI models getting more attention. Chief information officers have expressed greater interest in smaller language models, citing new technological improvements, lower costs, and lower barrier for adoption as they pivot away from large language models. This shift explains why investors are pouring more into startups that embrace small language models, while major AI vendors like Alphabet, OpenAI, and Anthropic are unveiling software that's more nimble than their flagship large language models, reports Bloomberg. “You can be more narrow and focused with your model when it’s a smaller model and really zone in on the task and use case,” Arcee.AI startup founder Mark McQuade told Bloomberg.

CrowdStrike’s 'Most Epic Fail' award. CrowdStrike president Michael Sentonas earned some praise after he personally accepted a “Most Epic Fail” award at the annual Las Vegas Def Con hacking conference. Sentonas said it was “super important to own it when you do things horribly wrong, which we did in this case.” However, the cybersecurity company's dispute with Delta continues to heat up, after the global IT outage reportedly led to $500 million in damages that are still being sorted out. Delta wants to recoup the losses incurred from thousands of flights that were canceled, while CrowdStrike asserts its own liability should be less than $10 million, saying Delta struggled more than most with the outage because of the airline’s own IT decisions.

Why Lenovo's laptop remains an enterprise darling. Lenovo’s ThinkPad laptop hasn’t changed much over the decades, and that may be precisely why it remains so enduringly popular, theWall Street Journal reports. Corporate tech leaders tell theJournal that they love the ThinkPad for pretty mundane reasons: The design hasn't changed much, the device is resilient to falls and extreme temperatures, and it is just really reliable. “It operates without most of our users having to think about it,” says Ace Hardware CIO Rick Williams. “People assign a lot of weight to having technology that’s reliable.” Lenovo currently commands the top market share among PC makers, and much of the credit is attributed to the company's focus on the enterprise space.

ADOPTION CURVE

The C-suite wants a security strategy overhaul. A survey of 2,800 C-suite executives conducted by professional services firm Accenture found that nearly two-thirds believe their security strategy will require “significant adjustments” to mitigate the risks associated with generative AI. Another 26% believe that a total transformation is needed.

Cyber experts have warned that Gen AI has given bad actors new tools to create more sophisticated phishing campaigns, as well as deepfakes, which are video, sound, or images of a real person that have been manipulated for fraud. The Accenture survey found that over the next two years, 50% believe generative AI will benefit both cybersecurity attackers and defenders, while 42% believe it will give the defenders an edge in the AI cyber arms race.

JOBS RADAR

Hiring:

- The San Diego Metropolitan Transit System is seeking a chief information officer, based in San Diego. Posted salary range: $201.6K-$286.3K/year.

- PitchBook is seeking a senior director of enterprise technology, based in Seattle. Posted salary range: $200K-$300K/year.

- AlphaSense is seeking a VP of IT and security, based in New York City. Posted salary range: $250K-$299K/year.

Hired:

- Truist Financial Corporation announced that Steve Hagerman will be the bank’s new CIO, joining on Oct. 28 and reporting to chairman and CEO Bill Rogers. Most of Hagerman’s career has been in the financial industry and most recently, he served as CIO for consumer technology, CTO, and head of consumer lending technology at Wells Fargo.

- Capital City Bank has promoted Lynne Jensen to CTO, overseeing product development, cybersecurity, application architecture, and AI platforms. Jensen joined the Florida-based financial firm in 2004 and most recently managed the company’s IT network.

- Avangrid appointed Nelly Jefferson as CIO, overseeing the sustainable energy company’s IT strategies, applications, infrastructure, and business operations. Jefferson, who will start Sept. 16, previously led technology for RWE Clean Energy and ConEdison.

- Hallmark Health Care Solutions named Dimitry Plotko as chief product and technology officer, taking on the role from cofounder Neeraj Isaac, who was CTO for the past 15 years and will move to a strategic advisor role. Plotko joined Hallmark from ADP, where he was SVP of product development.

- Cauldron Ferm appointed David Weiner as CTO, where he will run technology research and development for the biomanufacturing company. Prior to joining Cauldron, Weiner was a VP and head of R&D at specialty chemicals company Solugen.

- Velia Therapeutics announced that Alan Saghatelian has been named CTO, where he will oversee the development of the company’s microprotein-based platform and advance its pipeline of novel therapeutics. Saghatelian has more than 25 years of research experience, including at The Salk Institute for Biological Studies and Harvard University.

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How eBay uses generative AI to make employees and online sellers more productive (2024)
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