It seems like Google's recent focus on generative AI at its Cloud event in Las Vegas has raised some eyebrows, particularly regarding its emphasis on AI over its core cloud infrastructure and platform services. While showcasing the potential of generative AI, Google may have downplayed the challenges associated with implementing such advanced technologies within large organizations.
The demonstrations presented by Google primarily highlighted AI capabilities within the Google ecosystem, potentially overlooking the fact that many companies store their data in repositories outside of Google's infrastructure. Some of the showcased examples, such as the e-commerce demo, seemed to overemphasize the role of AI, with tasks that could have been accomplished without it.
Despite the promising applications of generative AI, there's a recognition that its implementation poses significant challenges, especially within large enterprises. Past technological shifts, like mobile, cloud, and marketing automation, have come with their own complexities and often led to disillusionment among companies that struggled to fully adopt them.
The success of adopting generative AI could depend on factors such as organizational readiness, technological infrastructure, and internal resistance to change. Companies that have already made significant shifts to the cloud might find it easier to adopt generative AI compared to those that have been slower to embrace technological innovations.
Vineet Jain from Egnyte suggests that companies fall into two categories: those that have already transitioned to the cloud and may find it easier to adopt generative AI, and those that have been slow movers and might encounter more challenges in doing so.