It likely isn’t a surprise to many of you that executives like AI. A survey shows that 74% of executives surveyed have greater confidence in AI-generated insights than advice from colleagues or friends. At the board level, even more (85%) favor AI-driven advice.
That’s amazing to me, and while I might think this is a bit too much trust being placed in these GenAI LLMs, perhaps it’s also partially because they work with too many people who aren’t great at their jobs. Plenty of people skim through data or focus on certain things and might miss the details. While an AI can read and summarize a lot, it might not have the context we expect. I tend to be a bit skeptical of AI summaries, often because they don’t necessarily weigh the different parts of an article the same way that I do. However, they can be helpful.
Even more interesting, 44% of executives say they would trust a GenAI to override their decisions based on insights, and 38% would trust AI to make decisions on their behalf. Business decisions based on data, or conclusions from a lot of inputs are different than producing working code, so I don’t know how accurate these models might be in this context. I do know that I want experienced people reviewing and judging GenAI outputs, and I would not allow an AI to override me without my input.
However, I wouldn’t just discount a GenAI recommendation. I tend to have strong opinions, but loosely held. I’ll change if there is evidence or a good argument to do so. It’s possible a GenAI might see things I miss and produce an insight that gets me to change a decision.
What’s a bit scary about the stats from this survey is that many executives see a skills gap in their staff, and their trust in GenAI might lead them to replace or augment existing staff with more GenAI tools. They might expect hiring can be delayed or slowed (or eliminated) with GenAI filling gaps. This might be especially true as many tech companies talk about how GenAI tools are making them more efficient.
That means that tech professionals should consider a few things. First, learn to work with GenAI tools and use them to prove your value to an organization. This includes learning when not to use them. Second, continue to improve your skills to ensure you can judge Gen AI results and emphasize that you are still the expert. Lastly, as the technology improves, consider adding some skills in how to train an AI to be a better assistant for you. The more efficient you are, especially with a GenAI helper, the more likely you are to impress executives and managers that are choosing which staff to keep.
Steve Jones
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