Too much of the content, however, is preachy and vacuous—e.g., ”AI is going to be disruptive” or “AI is a game changer.”
The impact of Generative AI on business isn’t staff replacement—it’s the acceleration of human productivity and creativity. According to Charles Morris, Microsoft’s Chief Data Scientist for Financial Services: “Don’t think about Gen AI as an automation tool, but as a co-pilot—humans do it, and the co-pilot helps them do it faster.”Generative AI Unleashed: Charting The Enterprise Future
“There are certain standards that companies should apply to each model. Risk groups need to track these models and rate them on their accuracy, potential for bias, security, transparency, data privacy, audit approach/frequency, and ethical considerations .”Remember the spreadsheet Lotus 1-2-3? Although it wasn’t the first PC-based spreadsheet on the market, when it was introduced in early 1983 it sparked a boom in the adoption of personal computers, and was considered the “killer app” for PCs.
These same issues companies wrestled with 40 years ago with Lotus 1-2-3 are present today with the use of ChatGPT and other Generative AI tools: There’s a reliance on ChatGPT’s often, there’s no documentation on the use of the tool, and there’s no consistency in the use of the tool across employees in the same department, let alone same company.
Companies have wrestled—for decades, now— with giving their employees access to the data they need to make decisions and do their job. Part of the challenge is having tools that access the data, and getting employees trained and up to speed on them.
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