By Saurabh Sharma, Founder and CEO at Agile 360-Degree Consulting and Career Mentor
Step onto a railway platform. Some trains are too fast to catch, but others wait just long enough to leave. Careers today are pretty much the same. That express train is now called Artificial Intelligence. Those who know when to get on and how to ride will go ahead. If you wait too long, you might miss out.
The Hard Truth: Jobs Are Changing
In the last few months, big tech companies have been on a job-shedding spree. In July, Tata Consultancy Services (TCS) fired 12,000 people. This year, Microsoft has fired 15,000 people. Oracle has reportedly laid off almost 10 per cent of its Indian workforce. Intel is cutting 15% to 20% of its staff, which will affect almost 10,000 people. As per Layoffs.fyi, 93 companies laid off more than 23,500 tech workers in 2025 alone.
Human intelligence has always evolved with technology. The steam engine defined the industrial age. Computers built the information age. Social platforms rewired the social order. Every shift was disruptive, but AI does not represent just another shift. It is changing the very nature of intelligence.
It started with software quietly automating tasks, but now it’s grown into machines making decisions, coming up with new ideas, and taking over jobs that used to be done by people. This is no longer an enhancement of human capability; it is a challenge to it. For the first time, the problem is not whether we can use technology, but whether we can stay relevant alongside it.
We are no longer in an era of gradual change. We are in the AI age, a transformative break as significant as any industrial or social revolution before it. And this time, no role is safe.
Let’s talk about three levels of the workforce. The new hires entering the workforce, managers overseeing operations, and CXOs influencing the future, to get a fair sense of how profound this is. The disruption is universal, but each faces a unique battle.
For Beginners: Coding in the AI Era
The ground has changed for newcomers. It’s becoming less common to prove yourself by slogging through endless lines of code; instead, people are becoming more intelligent. Although they are still fundamental, languages like Python, Java, and C++ are not the end goal.
What matters now is how you apply them in real projects, how quickly you can turn an idea into something that works. Employers aren’t impressed by syntax anymore; they want outcomes. Tools like Copilot or CursorAI can write and debug in seconds, but they can not tell you why the code should exist in the first place. That’s where you step in.
The fresher’s role has moved from “pure execution” to “efficient-execution.”
Middle Management: Balancing Roles with AI
While new hires focus on learning the coding, middle managers have to drive it and change tracks. They have to deal with project delivery, client expectations, and managing their teams. But managing is not enough anymore.
A project manager who only looks at risk is already at risk of redundancy. People want to see AI being applied in real work. This means finding projects where AI can directly automate workflows, or get customers more involved.
A mid-level supply chain operations professional, for instance, can leverage AI-powered forecasting tools to cut delays by weeks. AI facilitates a marketing manager to divide customers into groups with much more accuracy than older models did. In finance, AI can help controllers and analysts find problems in real time across thousands of transactions. For product managers, AI-driven user insights can accelerate feedback cycles and guide decisions without months of manual research. Even HR managers now turn to AI to improve recruitment, predict attrition, and design more personalised employee engagement strategies.
Depending on the role, the applications differ. But across this wide spectrum, the expectation remains the same, mid-level professionals have to think end to end. It is not about adopting AI in isolation, but about weaving it into the way work is planned, executed, and measured.
While the above may sound obvious, the reality is that middle managers often remain so deeply absorbed in day-to-day project execution that they miss out on meaningful learning in these areas. The cycle of delivery leaves little room for exploration. The practical way forward is structured learning outside office hours. Weekend programs and short-term certifications are no longer add-ons; they have become essential for professional survival.
Senior Leaders: Changing Strategy in a World of AI
The AI train needs a different ticket at the top level of leadership. It’s not about knowing how to get the efficiency via AI; it’s about using AI to create competitive advantage, reduce costs, and drive teams to adopt it with purpose. Senior leaders must understand how AI can directly strengthen their businesses. For example, a CEO/CXO who ignores building an AI-driven RAG (retrieval augmented generation) model for their organisation, risks falling behind competitors.
This is also where strategy and empathy must come together. With thousands of roles being reshaped or lost due to AI-driven restructuring, leaders face the real test of balancing efficiency with humane workforce transitions. Reskilling budgets and internal mobility programs will decide whether companies create long-lasting institutions or fragile workforces built only for the short term.
AI is changing the way work is done across roles and responsibilities. The challenges are not the same for everyone, but each person, whether a leader, a manager, or an individual contributor, has to respond to it in some way.
Careers today are a bit like catching a bus. The route is shifting, and the stops are not always the same. Waiting too long for the “right time” to get on can mean the bus doesn’t stop for you again.
Getting on early doesn’t mean you’ll have all the answers, but it does mean you’re moving with the changes instead of moving along with them.