Why Adopting GenAI Is So Difficult – HBR.org Daily

More than a year after the launch of ChatGPT, companies are still facing the same question when they first considered the technology: How do they actually go about putting it into business use? Many companies have simply discovered that generative AI tools like LLMs, while impressive, aren’t plug and play. Companies should consider a few suggestions when thinking of whether and how to onboard these tools: 1) choose performance over novelty, 2) combine GenAI with tools like vector databases, 3) never forget the human-in-the-loop, 4) trace your data, and 5) have realistic expectations.
In the nearly year and a half since the release of ChatGPT 3.5, both businesses and individuals alike rushed to explore generative AI (GenAI) technologies. For many, there was a palpable fear of missing out on the next big thing, of being overtaken by competitors who were able to crack the code of using it to revolutionize their businesses, or being caught flat-footed by sweeping, industry-wide change. Report after report has touted the transformative power of GenAI across industries and its implications on the future of work. Adding more heat to the fire, media articles continuously reminded us that jobs would likely be lost at scale and speedily.


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