Takeaways from my July 2024 interview with cloud architect and author David Linthicum David Linthicum Wall Street now agrees that generative AI is past the Peak of Inflated Expectations and heading down into the Trough of Disillusionment,  Analysts are starting to paint a clearer picture of how far expectations have fallen, “expecting Big Tech companies… Read More »A generative AI reality check for enterprises

Implications and Future Developments of Generative AI

In a recent interview with renowned cloud architect and author David Linthicum, we delved into the current state and future implications of generative AI. Wall Street analysts suggest that the generative AI has passed the phase of inflated expectations and is now at the stage of disillusionment. As a result, this technology is now under close scrutiny to understand its long-term outlook and potential impact on Big Tech companies.

Long-term Implications of Generative AI

Despite the disillusionment, it is important to remember that this phase is part of the typical cycle for emerging technologies. As acknowledged by Gartner’s Hype Cycle, disillusionment often follows inflated expectations, leading to a more realistic outlook on the potential of the technology. This stage is where the real value and functionality of the concept of generative AI start to materialize.

Long-term use of generative AI holds the promise of automating and improving a variety of tasks, from design, content creation, to drug discovery. And while initial expectations may have been overambitious, they do not negate the potential advantages inherent in generative AI technology.

Future Developments for Generative AI

Going forward, several developments seem likely on the horizon for generative AI. First, we will undoubtedly witness more extensive deployment by tech icons, as they harness the power of generative models to drive innovation and create market differentiators. Further, advancements in computing power and capabilities are expected to amplify the impact of existing models.

Actionable Advice for Enterprises

1. Remain Open to Generative AI: While disillusionment is part of the process, businesses need not be discouraged. The reevaluation phase is critical to gaining a clearer understanding of what precisely generative AI can and cannot do, leading to more effective incorporation into business strategy.
2. Innovate with Generative AI: Companies should consider the ways in which they can harness this technology within their organizations. The automation of design processes and content creation can drive operational efficiency and offer opportunities for new products, services, and even business models.
3. Invest in Training and Education: If businesses are serious about leveraging generative AI, investment in employee training and education in the field is crucial. This will ensure teams possess the required knowledge and skills to effectively utilize this technology.

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