AI revolution is coming but not soon enough. It is seen as an exciting new wave of technology. There are issues of the use of data, the accuracy of AI-generated answers and the leakage of confidential data. AI, no doubt, will boost productivity. Yet, as we know, historically all inventions take time to have full adoption. Steam power and internet illustrate this. In 1990s, internet took the world by storm. It was predicted it would disrupt advertising, retailing and media. Though these predictions proved true, it almost took a decade. Over a period of time, the tech was refined and costs dropped. Broadband internet connections became commonplace. The payment gateways developed. Audio and video streaming developed. The internet adoption was funded by many investors who believed the startups, and things moved on.

AI could lead to a similar gold rush. There is an investment frenzy. Billions of dollars are pouring into generative AI. Corporates are sampling the technologies. It is to be seen how the industry gets affected. The advent of ChatGPT in Nov.2022 was a ‘netscape moment’ ( reference to the introduction of browser in 1994). ChatGPT has poured soul into internet. However, it is just a start. It has opened door for new opportunities. The widespread use of generative AI apps will take time. There is already improvement in currently known technology. However, future breakthroughs are yet awaited. Mainstream adoption could take 8 to 27 years. It is a broad range. It is going to be governed by economic cycles, government regulation, organisation culture (OC), and management decisions.

Here people are involved. We are not dealing with laws of natural sciences. There are human choices involved. Tech diffuses through people AI forecasts see a productivity surge and addition of trillions of dollars to the global economy.

Specialised AI refers to AI systems that are designed and trained for a specific task or a set of tasks. These AI systems are tailored to excel in domain and have limited capabilities beyond that domain. To illustrate, language translation systems, image recognition algorithms and recommendation engines.

Though generative AI is booming, it can be very costly. There is significant expense in training and executing LLMs. To begin with, early adopters of specialised AI solutions are companies in retail, healthcare, BFSI, and manufacturing. As the potential of specialised AI continues to unfold, its applicability holds promise for other industries.