Is your neighborhood market using ChatGPT this holiday season?

A new report from American Express found that a quarter of small businesses surveyed planned to use AI to expedite tasks like social media posts, marketing campaigns, seasonal hiring, and customer emails amid the year-end shopping rush. The survey also clocked a 7% bump in the number of business owners who said they were “generally prioritizing AI” from a similar midyear report.

Small businesses see these tools as a way to stretch limited resources and compensate for smaller staffs amid what’s often their busiest time of year, according to Brett Sussman, VP and head of marketing and sales at AmEx’s Business Blueprint and Banking.

“One of the things they consistently tell us is they always feel like they’re potentially a little bit short-staffed,” Sussman told Tech Brew. “And they’re always thinking about, ‘How can I hire and how can I retain my employees?’ And so I think they’ve really taken AI as a tool for them to become more productive with their existing staff.”

But Sussman said there’s also a sizable contingent of small business owners who are wary about tapping into AI because of risks involved.

Keep reading here.—PK

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Data is often cited as the No. 1 wrinkle for companies looking to get into AI. Data scientists can spend nearly half their time wrangling it into shape, and three in five CEOs say a lack of clarity around data provenance is a barrier to implementing generative AI tools.

Many major corporations are hoping to ease some of those headaches with a new set of standards designed to clarify where and how the data they use was collected. Nike, IBM, UPS, Mastercard, and Walmart are among the more than 25 companies that contributed to developing the guidelines as part of a nonprofit consortium called the Data & Trust Alliance.

Companies have been grappling with big tracts of data for years, but the situation has turned perhaps more urgent in the past year as many businesses have tried to build internal tools around large language models. Fine-tuning those models to perform specialized tasks can take a huge amount of internal information, raising new concerns around data privacy and responsibility.

The alliance claims it will be the first to create standards around data provenance that apply to multiple industries.

“The creators of AI platforms are not the only players in this inflection point,” Ken Finnerty, president of IT and data analytics at UPS, said in a statement accompanying the announcement. “Enterprises in every industry are deploying data and intelligent systems that are core to their business…Data provenance is critical to those efforts.”

Keep reading here.—PK

AI is having a moment. From writing wedding toasts and even news articles to generating (often unsettling) images of hands, individuals and companies have increasingly embraced the new technology since ChatGPT became a household name.

The healthcare industry also wants in, particularly to improve the clinical trials process.

New AI-enabled software like eClinical Solutions’s Elluminate cloud platform help clients better manage clinical data, monitor trial participants, and analyze results. Some companies, including cancer health tech firm Flatiron Health, have taken it a step further by using AI-enabled software to review electronic medical records and streamline clinical research.

Those capabilities offer a preview of how AI-enabled technologies could shape the future of clinical trials, health tech executives told Healthcare Brew at a November conference in Boston.

“The generative AI movement now—it’s epic technology. It’s unprecedented in terms of what we are seeing. It’s going to transform industries,” eClinical CEO Raj Indupuri said. “Three, four years from now, we’ll look back and will think this moment [is] almost equivalent to how we see the internet in the early 2000s, how we see the mobile revolution—or the iPhone revolution—after the financial crisis, how we see the cloud [in the] last decade.”

Keep reading here.—SY