Generative AI has a lot of potential and a lot of caveats. Oliver Silva of Casepoint proposes a cautious approach to embracing generative AI.
His article (How to Take a Cautious Approach to Embracing Generative AI and available here) discusses why it pays to be careful when it comes to innovative solutions such as generative AI, and how your organization can implement a cautious approach to generative AI that balances the potential for innovation and growth with the need to remain flexible and effectively manage risks.
History is replete with examples of innovations that ultimately became highly successful, but only after they matured significantly. Here’s one example:
Mobile Phones
Mobile phones go at least as far back as 1984, when the Motorola DynaTAC 8000X (known by many as the “brick phone”) came onto the market with a hefty price tag of $3,995! Mobile phones evolved considerably for more than 20 years until the first iPhone was released in 2007 (followed by the Android operating system in 2008), which reinvented the mobile phone into the current generation of smartphones popular today that are indispensable to our lives.
So, what are two other examples of innovations that became highly successful, but took a while to get there? And what are considerations you need to know for a cautious approach to embracing generative AI? Check out Oliver’s article here to find out. No need to be cautious about reading it! 😉
So, what do you think? How is your organization approaching the use of generative AI? Please share any comments you might have or if you’d like to know more about a particular topic.
Image created using GPT-4’s Image Creator Powered by DALL-E, using the term “robot conducting a web search on a smartphone”.
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