Deprioritising 3G skills in a 5G AI world: Future of data, AI, and enterprise transformation

Artificial intelligence is rapidly transitioning from a support function to a central force shaping how enterprises operate, compete, and innovate. As AI evolves from predictive and generative capabilities to more advanced, autonomous systems, organisations are being pushed to rethink not just what to invest in, but also what to consciously deprioritise. For years, businesses have built robust data ecosystems centered around structured data, dashboards, and human-led decision-making. Roles such as data analysts, BI developers, and business analysts were critical in translating data into insights. However, with machines now capable of interpreting, reasoning, and even acting on data, many of these long-standing models are being fundamentally challenged.

At the same time, enterprises are grappling with legacy systems that were never designed for this new AI-first reality. These systems are often rigid, filled with hard-coded logic, and disconnected in ways that make modernisation complex. The challenge extends beyond technology to governance, scalability, and even business models, particularly as organisations struggle to move AI initiatives from pilot stages to full-scale deployment. In this conversation, Uday Hegde, Co-founder & CEO of USEReady, shares his perspective on navigating this shift, from redefining skill priorities and modernising data architecture to building scalable AI systems and preparing for a future where AI becomes as essential, and as ubiquitous, as a utility.

Which data or AI skills should tech leaders deprioritise today?

There are several skills that were extremely relevant not too long ago but are now losing their importance, especially when viewed in the context of what AI can do today. I often explain this using an analogy from telecom, how we moved from 3G to 4G and now to 5G. AI is evolving in a similar way, and what we are experiencing today is essentially the 5G phase of AI.

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