Summary:
Generative AI is everyone’s answer to business transformation and solving business problems. It allows users to lower digital complexity and use technology most naturally: via natural language. The technology also has wide applications across industries, so the adoption of Generative AI is going to be in industry-specific processes, such as predicting weather patterns and improving assembly line efficiencies, as well as more generic processes, such as customer support and creating marketing content. But Generative AI technology is not perfect. Domain and technological expertise are required to accomplish AI integration with existing systems. And while it is closely intertwined with digital transformation, the relationship between digital and AI must be thoroughly understood.
What’s in it for you:
It is becoming amply evident that Generative AI will increase digital complexity as it attempts to connect with heterogeneous systems. CloudOps and SecOps will have to be re-examined, and tools and platforms will have to be revisited to reduce technological risk. To do this effectively, an enterprise must apply five simple rules for optimal returns from its Generative AI investments.
This paper describes how Generative AI will change the technology landscape, how things could go wrong (with examples), how to avoid the dangers of “too much innovation,” and the five sound and sensible rules of investing in technology.
