Meta has appointed Clara Shih, the former CEO of Salesforce artificial intelligence (AI) division, to lead a new unit focused on developing AI tools for businesses.
Meanwhile, Salesforce, has confirmed that Adam Evans, previously the company’s vice president of AI Engineering, will succeed Shih, reported TechCrunch.
Evans has been promoted to executive vice president and general manager of Salesforce AI.
Shih, who will lead a new Business AI group, said in a Linkedin post: “Our vision for this new product group is to make cutting-edge AI accessible to every business, empowering all to find success and own their future in the AI era.”
Meta vice-president and monetisation head John Hegeman was quoted by the media outlet as saying: “We believe these latest advancements in AI represent a significant opportunity for businesses to drive more efficiencies and significantly improve the experiences they offer their customers.
“This new product group under Clara’s leadership will help us bring that vision to life.”
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By GlobalDataMeta’s Llama AI models have more than 600 million downloads, and Meta AI now has 500 million monthly active users.
Millions of businesses connect with consumers utilising Meta’s apps, Facebook, WhatsApp and Instagram.
Meta’s new group will focus on providing AI products built with Llama to the millions of businesses advertising and creating content on Facebook, WhatsApp and Instagram.
While the exact tools they plan to offer are still unclear, it’s likely they will include options for creating AI-generated ads, reported the news agency.
Shih added: “Meta’s global reach and leadership in AI represent a generational opportunity for businesses, and I couldn’t be more excited and grateful to help take this from zero to one to scale.”
In October 2024, Meta released a new AI model known as the “Self-Taught Evaluator,” to reduce human involvement in AI development.
First introduced in an August 2024 paper, the tool employs the “chain of thought” technique, mirroring the approach of OpenAI’s o1 models, to improve the reliability of AI judgments.