Across all sectors, we are seeing companies start to use generative AI to write code, check for bugs and streamline their software development processes. This is really an ideal use case for generative AI because many aspects of code-writing involve tedious, time-consuming and repetitive tasks that can be addressed much more efficiently with AI.
While all of these implementations of generative AI are still in relatively early phases of development, the increases in productivity, accuracy and speed to insights they are delivering are proving impossible to ignore. We expect adoption to accelerate rapidly. As is the case with any new, fast-moving technology, though, we also expect to see lots of lessons learned and course corrections made along the way. In the area of generative AI-enabled code creation, for example, which is arguably one of the most thoroughly developed use cases introduced in business thus far, one unintentional side effect has been an exponential surge in new code.
Working through these challenges and finding new opportunities along the way will make for some exciting times for business leaders in every sector over the next several months. The process will also spotlight areas where we need to start thinking about best practices, standards and governance for how this technology is implemented in a reliable, responsible manner.
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