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While generative AI has been the talk of the town since OpenAI publicly released ChatGPT in late 2022, employers still face an uphill battle to get their workforce on board with the new technology.
Just 12% of white-collar workers are already using generative AI, and 11% have active plans to use it. The remainder are still considering it, or have no intention to use it, according to a survey of more than 1,100 respondents in professional services industries, including legal, tax and accounting, risk and fraud, and government professions, conducted by Thomson Reuters earlier this year. While 81% of respondents say generative AI could be applied to their work, only 54% believe it should be used. Respondents' most common concerns include AI’s potential for making inaccurate responses, data security risks, privacy and confidentiality surrounding the data it uses, compliance with laws and regulations, and ethical and responsible usage.
For Mary-Alice Vuicic, Thomson Reuters’s chief people officer, the findings show that HR teams still have a lot of work to do to convince employees about integrating AI into their workflow.
“It's a call to action that firms and leaders need to be much more proactive in making this a firm priority, and an organizational priority, helping people understand it, [and] giving them secure space ways to experiment and use it,” she tells Fortune.
While Thomson Reuters has used AI in some capacity for nearly three decades, ChatGPT’s launch in late 2022 prompted the company’s leadership to reimagine how its workforce should use the fast-evolving technology. But first, they had to figure out how to get workers on board. After the launch of ChatGPT, the company updated its internal policies, including its AI code of conduct, ethics, and guidance for how employees would use the technology securely.
Vuicic, who co-leads the company’s internal AI adoption strategy along with the head of technology, says her team focused heavily on communication efforts, an area she believes HR teams sometimes overlook with AI adoption. Thomson Reuters launched an enterprise-wide learning day in April 2023, focusing on teaching employees about AI and machine learning basics. More than 6,000 employees participated in the sessions on AI and machine learning on the day, and more than 10,000 have watched the recording of the company’s AI 101 session since. Soon after, questions about AI quickly replaced hybrid work as the number one topic for employee questions in town halls or info sessions.
The company held another global learning day this year, during which it shared internal adoption use cases. Some of those include using AI for engineering, customer service support, and case management for internal HR inquiries, allowing HR personnel to focus on more high-level issues.
“I think that people underestimate the importance of this,” Vuicic says. “Everybody's reading the headlines, and people are nervous…they're wondering, ‘Am I going to have a job? What does this mean for me? For my children, as they choose their education?’ They're looking for places to talk about this, so we went very transparently, very open.”
Along with its global learning day, Reuters provided AI training for all employees, along with a secure platform where workers could experiment with different AI tools, including ChatGPT. Trainings for non-technical employees include an introduction to AI and machine learning concepts, examples of how the company is using AI internally, and guidelines for responsible use of AI. For technical employees, training includes machine learning principles, how to use large language models, prompt engineering, and in-depth information on the company’s AI platform and services.
Vuicic’s team found that after that training, the company saw increased worker productivity, accuracy, quality of output from employees, time freed up from automation, and money saved from these improvements.
“Training and hands-on use to demystify [AI], it's something that we've put a big focus on here,” she says. “The opportunity for firms, corporations, and individuals to make training a priority, make exposure a priority, and get that hands-on use of experimentation—I think that will remove quite a bit of the hesitation.”
Paige McGlauflin
paige.mcglauflin@fortune.com
@paidion
Today's edition was curated by Emma Burleigh.
