A world teeming with self-aware brands would be quite hectic. According to Gartner, by 2025, generative A.I. will be a workforce partner within 90 percent of companies worldwide. This doesn’t mean that all of these companies will be surging toward organizational AGI, however. Generative A.I., and LLMs in particular, can’t meet an organization’s automation needs on its own. Giving an entire workforce access to GPTs or Copilot won’t move the needle much in terms of efficiency. It might help people write better emails faster, but it takes a great deal of work to make LLMs reliable resources for user queries.
Their hallucinations have been well documented and training them to provide trustworthy information is a herculean effort. Jeff McMillan, chief analytics and data officer at Morgan Stanley (MS), told me it took his team nine months to train GPT-4 on more than 100,000 internal documents. This work began before the launch of ChatGPT, and Morgan Stanley had the advantage of working directly with people at OpenAI. They were able to create a personal assistant that the investment bank’s advisors can chat with, tapping into a large portion of its collective knowledge. “Now you’re talking about wiring it up to every system,” he said, with regards to creating the kinds of ecosystems required for organizational A.I. “I don’t know if that’s five years or three years or 20 years, but what I’m confident of is that that is where this is going.”
Companies like Morgan Stanley that are already laying the groundwork for so-called organizational AGI have a massive advantage over competitors that are still trying to decide how to integrate LLMs and adjacent technologies into their operations. So rather than a world awash in self-aware organizations, there will likely be a few market leaders in each industry.
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