Bhavesh Goswami, Founder & CEO, CloudThat explains the value of skilling in AI era.
Until a decade ago, software evolved every two or three years, which was when you paused and upskilled. Today, that approach is obsolete. But you might have noticed that in the past few years, change has compressed dramatically. What once unfolded over years now happens in months.
A striking example came when Anthropic launched enhanced enterprise capabilities within its Claude AI platform, enabling advanced automation across legal research, analytics, and enterprise workflows. According to reporting by Forbes, the announcement triggered a global software stock selloff. In a single trading session, Oracle fell roughly 5%, Adobe declined nearly 7%, and Salesforce dropped around 4%, as investors reassessed the long-term defensibility of traditional software models against rapidly advancing AI automation. Markets were not reacting to hype, they were reacting to the real possibility that AI agents could replace high-value, billable human workflows.
Disruptions that once took decades were now unfolding in weeks.
For entrepreneurs and enterprise leaders, the implication is clear: staying distant from technology is no longer viable. The only sustainable response is continuous skilling. Leaders must dedicate a few hours every week to understanding what is latest and most transformative in AI. That means getting hands-on — experimenting with tools, exploring AI workflows, even trying approaches like vibe coding to understand how AI-assisted development can unlock productivity within their own organizations.
Cloud, Gen AI, and data-driven decision-making are redefining baseline leadership expectations. Tech fluency is no longer confined to CIOs or CTOs. Boards and all CXOs must understand AI workloads, cloud-native infrastructure, automation economics, and data strategy. Enterprises are reshaping hiring and leadership pipelines to prioritize tech-fluent decision-makers who can bridge business strategy and emerging technologies.
This urgency directly aligns with India’s ambition of becoming a Viksit Bharat, a globally competitive, innovation-led economy. Achieving that vision requires leaders across sectors who are comfortable navigating AI-driven transformation. Continuous upskilling is not optional if we intend to meet our national economic aspirations.
However, speed must be balanced with responsibility. AI systems learn from real-world data. If historical decisions reflect bias, models trained on that data can replicate or even amplify those biases. In banking, hiring, or public services, skewed datasets can translate into discriminatory outcomes. A recent opinion piece in The Indian Express highlighted concerns about caste-based bias surfacing in AI outputs, reinforcing the need for ethical oversight. Ethical AI governance, fairness audits, and transparency mechanisms need to be boardroom priorities, especially in a country like ours.
In the AI era, competitive advantage will not belong simply to those who adopt technology first. It will belong to leaders who continuously evolve with it. Continuous skilling will be the defining capability of resilient, future-ready leadership.