Career, much like seasons, don’t always move the way we expect them to. Sometimes, they pause. Sometimes, they shift. And sometimes, they force us to rethink everything we believed was stable. A similar pause came in the form of a job loss… I did find another one in three months—but those three months changed the way I look at careers. Sometimes, life doesn’t remove something to punish us—it does so to redirect us. The mental struggles I faced during those three months taught me to find a reality check of the dire situation of the global market around.
At first, I could not accept it. I believed I had the skills—so maybe the market was bad, maybe it was just cost-cutting. I kept justifying it, until it became clear that “A layoff doesn’t just take away income—it questions existence.” And when my identity was at stake, I started searching for all the options to get money and build my identity back in the market.
People around used to first say you need to become irreplaceable, need to create dependency. Then they started saying it is not about that, it is about the AI trend in the market, learn the AI skills and then stand for interviews. Then another thought hit me—AI had suddenly become the new benchmark. And I wasn’t just learning—I was comparing myself with people who seemed to already know it.
How could I adapt so fast, and that too with confidence? Doubts started creeping in—would I become outdated if I didn’t learn AI? It felt like the definition of being ‘relevant’ had changed overnight. Even if I start some coaching will I be able to achieve what these Course advertisements show – high paying jobs, handsome salary appraisals.
What felt like a problem at first slowly started looking like a question. And questions, unlike problems, are not meant to be solved immediately—they are meant to be understood. Despite all the doubts, I started exploring options.
First, I considered AI courses. But I questioned their return on investment—most were expensive, promised too much, and the competition in the market was already high. Then I thought about freelancing. While I had some technical skills and access to AI tools, I lacked real experience. And even though the entry barriers were low, the competition was intense. The last option was trading with AI assistance. But without a strong foundation in finance, it felt like a high-risk path despite its potential. I realized I was not short of options—I was short of clarity. Clarity does not arrive immediately. It takes time, silence, and often discomfort. In a world where everything is moving fast, clarity becomes a slow process. And perhaps that is where many of us struggle—not because we lack options, but because we expect answers too quickly.
With all these options in front of me, I was more confused than ever. And that’s when the reality of it all started becoming clearer. AI didn’t just change the market—it had changed the expectations overnight. It all started sorting in my mind layer by layer. AI was not a skill in itself; it was one of the means/tools of assistance to reach the goal using some skills (prompt engineering, using relevant AI tool as per context, getting repetitive tasks done by AI to use human resources efficiently) that everyone has already, just needs a brush up. Companies, in their urgency to adapt, often struggled to fully understand the shift (panic mode – AI in code generation – 1 skilled developer is enough instead of 5 less skilled in AI). They started expecting more instead of supporting their employees with the help of training, sponsored courses, etc. Lastly, I understood freelancing will not guarantee stable income and trading never meant easy money. They can just become a supporting option not primary solution. The more I explored, the more I realized—the problem was not lack of options, but lack of direction.
And that’s when I stopped asking ‘What should I do next?’ and started asking ‘How should I think about careers in this new reality?
As a common reaction it became clear that, there isn’t just one way to respond to AI. There are multiple pathways, if we are willing to look beyond the obvious.
One direction is the human skill economy—roles like teaching, counselling, and therapy. Even with the rise of agentic AI, there are clear limitations, especially in deeply emotional spaces. While teaching can be supported through recorded courses, true guidance and confidence-building still require human presence. Counselling and Therapy could be done using some bots but when the illness is related to mind, it can’t be done without humans. Mental illness requires social meetings, loving people around, their love, their caring touch to make heal the wounds. A human can understand another human in ways that no tool fully can.
Another path is to work alongside AI as a collaborator. Instead of competing with it, one can learn to use AI tools effectively—whether through prompt engineering, freelancing, or building multiple income streams. In this approach, AI becomes a partner that amplifies effort rather than replaces it. One can take ideas, plan, organize using AI and build on to the same plan to become successful.
A more grounded way of thinking is problem-first, combined with domain expertise. Instead of chasing tools, identifying real-world problems and solving them—using human effort, AI assistance, or both—can create meaningful impact. Fields like agriculture, healthcare, or local businesses can benefit immensely when supported by AI’s organizing and analytical capabilities. A well-qualified farmer/ businessman/ entrepreneur can research onto and experiment new ideas in his field and increase the productivity along with increasing sustainability and earn huge profits.
There is also growing relevance of the real-world or physical economy—spaces where AI can assist but not dominate. As more work becomes digital, roles rooted in the physical world may become even more valuable. For instance, a farmer may use AI for weather predictions or crop planning, but the act of nurturing the land still depends on human understanding and effort. A doctor may use AI for diagnosis support, but patient care and trust remain deeply human. Similarly, electricians, mechanics, or on-ground service providers continue to rely on hands-on skill—where AI can guide, but not replace execution.
And beyond all of this, there is a broader shift towards portfolio careers—not depending on a single path, but combining a job with freelancing, learning, or side ventures. AI, in this sense, becomes an enabler of flexibility rather than a threat. For example, someone working in a full-time tech role may also take up freelance projects using AI tools to speed up delivery. A content writer might use AI to explore ideas while building a personal blog or side business. Even a teacher could use AI to create digital courses while continuing classroom teaching.
The more I explored, the more I realized—AI does not eliminate paths, it multiplies them. But having more options didn’t necessarily bring clarity. It only made one thing clearer—the real challenge was not finding opportunities, but understanding how to navigate them.
The more I observed, the clearer it became that AI is still in its early stages. While it is being rapidly adopted and widely discussed, much of it also feels overhyped. Many companies are attempting to build around AI, yet they still rely heavily on human effort to execute their ideas.
Large organizations have started making decisions based on the assumption that AI can replace multiple roles with fewer, more skilled individuals. But in reality, the transition is far from structured. There is no clear roadmap, limited availability of truly AI-skilled professionals, and growing concerns around data security and usage. I noticed this uncertainty even in my own workplace. During a recent discussion, my manager advised us to use AI for guidance, but not to directly rely on generated code. It made me realize that even organizations are still figuring out where and how to place their trust in AI.
On the other side, employees are navigating their own uncertainty—questioning which skills to learn, which courses to trust, and whether this shift is temporary or something they must fully adapt to. Somewhere in between all this, it becomes clear that the uncertainty is not just external—it is deeply internal which brings me to a simple but important thought—perhaps the need of the moment is not urgency, but clarity.
As individuals, we don’t always need to react immediately to every shift. Sometimes, it is about staying calm, continuing to build our skills, and exploring alternate paths without panic and also understand that “Clarity is the new form of stability”.
A thought I recently came across, heard in a talk by a spiritual leader, His Holiness Sri Sri Ravishankar stayed with me. When calculators were first introduced, there was a fear that people would stop learning mathematics altogether. But that didn’t happen. We still learn tables till 30 in schools, we still think—tools only changed how we apply our knowledge. Maybe AI is something similar. Not a replacement, but a challenge—especially to our creativity, our thinking, and our adaptability.
And perhaps the real response is not fear, but acceptance. To observe, to learn, to adapt—and most importantly, to continue thinking for ourselves. Because in the end, the future may change how we work—but it is still up to us to decide how we think.
By: Aditi Dhale
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