🤖 😳 For all the breathless hype, it appears business leaders are on their heels when it comes to #AI, and methinks it has more to do with technological understanding than MBA-level acumen. Here's why:
🔦 Much of the spotlight has been on #genAI, specifically LLMs and chatbots, which, despite the ballyhoo, are NOT general purpose technologies. And yet, #AI and #machinelearning in application, are actually very horizontal.
📉 "Executives who reported the most investment and knowledge in #generativeAI capabilities are the ones most worried about the technology's impact on their business."
So: Lots of noise, very little signal. For many enterprises, it may make more sense to invest in building smaller proprietary models and initially experimenting with precise use cases, such as expediting R&D (drug development, materials engineering, etc.) or even understanding operational workflows (logistics, assembly line efficiencies, etc).
Racing to bolt on chatbots for copywriting or whatever is not a strategic growth driver.
💥 And the stand out note from this survey? "Just 1 in 4 believe their organizations are well-prepared to address #AI governance and risks."
Because of its horizontal potential, leaders need to get in the trenches and understand the point of view of employees. Where would they rather spend energy than say, summarizing Zoom meetings. Where are you bleeding time? How much time is spent translating specialized outputs into a reports?
You can't build effective models or design innovative applications, without truly understanding the workload you're trying to address. Educate yourself, Mr. and Ms. Business Leader, but also, start talking to your people. And listening.
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