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Meta reentered the enterprise arena with a new Business AI unit, led by Clara Shih, in late November 2024. The strategic move aims to leverage Meta's existing AI capabilities and vast user base to create AI tools for businesses using its platforms.
Meta's Enterprise AI Move
Meta’s ambitions in the enterprise AI market are underpinned by a strong foundation. The company already has deep ties to the business world, connecting with 200 million businesses globally through platforms like Facebook, Instagram and WhatsApp, as Shih noted in a recent tweet. This vast existing user base offers a natural advantage in deploying and scaling enterprise-focused AI solutions.
Adding to its strengths, Meta's Llama models have achieved considerable traction with over 600 million downloads to date, while the Meta AI assistant, another cornerstone of its AI ecosystem, engages with more than 500 million active users every month.
Shih’s track record includes pivotal roles at Salesforce and as the founder of Hearsay Systems, a company specializing in AI-driven sales and social tools. Her insights and expertise promise to effectively shape Meta’s enterprise AI strategy.
Despite these strengths, Meta’s path into the enterprise AI market has its hurdles. The space is already highly competitive, dominated by well-established players like Microsoft, OpenAI and Anthropic. These companies have carved out strong positions making it difficult for newcomers to gain a foothold.
Meta also grapples with lingering trust and privacy concerns. Its past controversies surrounding data privacy may give some businesses pause, potentially hindering the adoption of its AI tools. For companies prioritizing security and transparency, these concerns could be a significant barrier.
Another uncertainty lies in Meta’s monetization strategy. It remains unclear whether the company will directly sell its AI tools or offer them free as a way to drive ad spending. This ambiguity could affect how businesses perceive the value and sustainability of Meta’s AI offerings.
Also of note is Meta's sunsetting of its Workplace tool, which could cause former customers to think twice before signing on.
Plenty of Opportunities in the Enterprise AI Market
Meta's AI strategy in the digital workplace holds significant potential, according to Dennis Perpetua, global CTO for digital workplace services at Kyndryl. Despite the rapid evolution of generative AI, he believes Meta has many opportunities to carve out a space in the enterprise AI market.
"Meta’s entry into this space might seem late due to the speed at which generative AI is advancing," Perpetua told Reworked. "But the reality is, regardless of how fast the capabilities are evolving, adoption within enterprises suggests there is still room for them. Llama has been around for a long time now, relatively, so they are already a known entity and are well-positioned to move quickly with unique capabilities that will continue to make them attractive."
Far from being at a disadvantage, Perpetua believes Meta is entering the digital workplace from a position of strength, albeit with a different approach than it took with Workplace from Meta. He believes Meta has an opportunity to leverage its successes in the productivity space to integrate seamlessly into existing ecosystems, adding value without displacing major players.
"While the footprint might be small, the insights they have from approaching productivity suites and business tools differently give them an advantage," he said. “They can integrate without needing to displace, finding their own space in the market.”
Perpetua also highlighted Meta’s potential to humanize AI through its experience with platforms like Facebook, Instagram and WhatsApp. “How this is done will take a very carefully laid-out approach, but they possess the experience of building a scalable messaging backbone and hive that can be extended into the business world to capitalize on their starting point,” he said.
Meta’s path into the workplace will likely come through the small and medium-sized businesses that rely heavily on Meta for marketing, according to Perpetua. He sees this as a natural base from which the company can expand its enterprise presence.
"They have the potential to drive propensity scoring for contact centers and personalize the employee experience by integrating with existing business tools," Perpetua noted. "I believe they would accelerate their recognition in the business AI space if they partner with some of the mainstays of software that CIOs rely on. There are plenty of tools managed and depended upon by CIOs that lack a strong AI play today, and these partnerships could rapidly expand Meta’s adoption and footprint."
Related Article: The Workplace From Meta Clock Is Ticking. Factors to Consider Before Migration
The Flexibility of the Llama Model
For many observers, one of the game-changers here is the Llama model itself. Varyence co-founder Jason Hishmeh sees the open-source nature of Meta’s Llama model as a major addition.
Most enterprise AI tools stay tightly controlled behind proprietary walls. "By opening things up, Meta’s essentially saying, ‘Take this model, experiment, customize, and shape it to your own needs,’” he said.
Any organization that's struggled to tailor a generic AI tool to its specific needs will likely appreciate this approach. Meta’s openness could accelerate the adoption of its tools, as organizations increasingly seek flexible, adaptable solutions rather than one-size-fits-all platforms.
He echoed Shih's message around Meta's advantage via its vast user data from platforms like Facebook, Instagram and WhatsApp. If used ethically and securely, he said, this data could offer businesses unmatched insights into customer behavior, potentially predicting needs before they are expressed. However, to serve enterprise clients, Meta must demonstrate its ability to provide real business value while upholding data privacy and meeting regulatory standards.
A final plus for Meta is the Shih hire. Shih's Salesforce background offers a clue of where the unit will focus, Hishmeh added. Meta is likely going to lean into usability and seamless integration and she could be key here.
Clara Shih was appointed CEO of Salesforce AI in May 2023, where she oversaw the company's artificial intelligence initiatives, including the development and deployment of Einstein GPT. Under her leadership, Einstein GPT delivered over one trillion predictions and generative automations weekly across multiple Salesforce clouds.
Her experience leading Salesforce Service Cloud, where she was instrumental in enhancing customer service technologies and integrating AI to improve user experiences, is a plus from the integration perspective.
“I’ve seen businesses waste time wrestling with complicated AI interfaces that never quite fit into their workflow," Hishmeh said. "If Meta’s tools can simply slot into familiar systems, marketers, sales teams, and customer support reps might actually enjoy using them — and that’s half the battle."
Related Article: OpenAI's $200 Gamble: Who Is the Audience for ChatGPT Pro?
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Late to the Party? So What.
Saying Meta is late is like saying businesses that started after the dot-com era had no chance, Eli Goodman, CEO and co-founder of Datos, a Semrush Company, added. He too sees Meta’s user data as an advantage over its competitors.
The level of detail Meta could provide about its customers is something many businesses would find valuable. Success isn't about being first to market, it's about how well Meta can use its strengths to meet business needs, Goodman continued. "If done right, timing won’t matter as much as the quality of what Meta brings to the table,” he said.
There is a caveat, however. Conrad Wang, managing director at EnableU, said success requires Meta to first prove its ability and earn people's trust. Its competitors have had a longer head start, which means Meta will need to make a compelling case for why the Llama model is worth considering, said Wang.
All of the major players in the AI space have their strengths, said Kyndryl's Perpetua. Microsoft has tremendous insights from its productivity and enterprise footprints, Amazon has tremendous insights from its consumer and cloud business, and Google obviously taps into search knowledge.
Regardless of any specific model's performance, the unique vantage points at the root of these models could ultimately differentiate them in the market. There is space and opportunity for each and it improves the overall approach to AI by having these multiple points of view.