In goal setting workshops all over the world, every facilitator starts at the same place.
Not with goals, or plans, or strategies…
They start with identity – Who am I? That single question determines everything – how you think, what you pursue, how you show up when things get hard.
Now AI is making deep inroads into our work. The way we work is being altered. And with it, something more personal is shifting too.
Our sense of who we are as professionals is changing.
This episode of Monday Muse is to look into this shift – a conversation we are not having loudly enough.
Let’s dive in.
Developer to Manager
It took the Indian IT industry about thirty years to be a $250B+ industry.
The engine behind it has been the global delivery model (initial proposed by Narayan Murthy in 2000) – skilled talent at low cost which can scale.
That combination was unbeatable (it is amusing to listen to Dewang Mehta’s stories and anecdotes that are still available online).
But at the core of IT was – writing code. Millions of engineers wrote software for the MNC’s of the world.
Codex – OpenAI’s code-generating model – launched in 2021. Named after the ancient bound manuscript – humanity’s first structured knowledge format. Codex could write code from plain English instructions.
This writing o code was not perfect, but well enough to matter which led to automation.
What followed were: GitHub Copilot, Claude, Cursor. Coding assistance became coding delegation. And the core of the Indian IT model – human-written code at scale – is suddenly starting to erode.
The new vision of our IT industry is: AI as our assistant. Agents would handle the repetitive work, may be the first to last draft. You review and baseline.
The role that emerges is of a manager — manager of machines. An Orchestrator of tasks, not creator of things.
So if the core melts, what is the new foundation?
What We Were Good At Is Shifting
We built our identity on skills that took years. Not months. Years.
Thinking through algorithms and logic was a foundational craft in designing solutions. Then doing the actual work: development, configuration, deployment. Getting things to run in production.
There were the harder skills.
Analysis and pattern recognition — spotting how system should be designed. Applying design and architecture patterns from a hard-earned mental library:
- Synthesis of complex problems.
- Generating solution ideas.
- Structured thinking.
- Big picture thinking.
These were the things that set us apart.
AI does versions of all of these now – faster, at scale, and without ego. May be with bias 😊
And that is the uncomfortable truth sitting at the centre of this.
The thing we were proud of being excellent at is no longer our differentiator.
This is an identity crisis.
The Imposter Syndrome underneath
The term – “Imposter Syndrome” – was originally coined by American psychologists in 1970s after observing a pattern of chronic self-doubt and “intellectual phoniness” in more than 150 highly successful professional women and students.
Their view was – high achievers inflict self-doubt when faced with a new situation.
As AI does our work, we don’t just lose our work. We lose self-worth. Fear of being exposed. Perfectionism. Overworking to compensate.
We have always tied intellectual worth to struggle. When AI generates a complex design in minutes – something that used to take us hours – we feel like a fraud for taking credit.
And there is a deeper question: who owns the insight – the person who prompted the tool, or the algorithm that generated it?
That ambiguity creates a validation void. Completing the task feels like nothing.
Here is the irony.
The people feeling this most are not the juniors. It is senior professionals — who had made it work earlier in game the rule of which has changed (or changing).
What Can We Do to Protect Our Territory?
So what do we actually do?
The best military strategies don’t rely on a single line of defence. They layer it.
So should we. What we should do is to activate multiple layers of our career stack by things in different plane —
- Consolidate our knowledge, skills
- Take extra care for the inventory of specialised high-value skills
- Expand our roles across consulting, sales, and thought leadership beyond being a core SME
- Expose to deep industry and domain knowledge
- Create an inventory of track record of delivered outcomes and stories.
Activating means consolidating our knowledge, automating/agentifying work, learning new things and using agents to do delegated things faster. On each of the layers.
Also also, make it prohibitively expensive for any single custom agent to replicate what you bring as a whole at multiple layers of the career stack.
And also double down on what AI simply cannot do on its own – bring in emotional intelligence, inspiration, Motivation. The things that make us human.
And finally – develop AI literacy fiercely. Master the tools. Build AI-powered capabilities in your own field.
Be the AI master before AI becomes your master.
A Successful Career in the AI Era
Career used to mean accumulating capability. More skills, certifications and experience.
That definition is shifting.
Today it means judgment, trust, relationships – the ability to act under uncertainty. The question is not whether AI is taking your job. It is whether you are building the things AI cannot take.
Move from doer to orchestrator. Direct agents to handle the heavy lifting. We focus on creative direction and business outcomes.
AI fluency is no longer a differentiator. It is a baseline – just like email was in the nineties.
And success is no longer about productivity. It is about value creation – where AI generates new revenue and innovation, not just cuts costs.
The most successful professionals will be “Frontier” employees (taking inspiration from “Frontier” models) – people who learn fast and unlearn faster, as AI shifts every few weeks.
In Conclusion
We have covered a lot of ground this week.
AI is not just disrupting our work – it is disrupting who we think we are. The imposter syndrome, the validation void, the shift from doer to orchestrator.
Three questions to reflect upon:
- What part of your identity is tied to a skill AI can now replicate?
- What layers of your career stack are genuinely hard to replicate?
- Are you building the AI-proof version of yourself?
When calculators arrived in the 1970s, engineers believed mental arithmetic was their core value. It defined them professionally.
Gradually, that identity shifted – from the calculation to what they could do with the cauculated result.
Our identity is shifting in nearly the same way.
That is all for this week.
Hope, it has been useful.
Till next episode!
This post originally appeared in the Monday Muse newsletter — weekly insights for enterprise and solution architects navigating digital transformation. Subscribe here.