How AI is Reshaping Organizations — Perspectives from Across the Avataar Portfolio

Over the past few weeks, we set out to understand how companies across the Avataar portfolio are thinking about AI — not just at the strategy level, but also at the ground level.

We wanted to dive into how AI is changing the way teams are built? What are people leaders navigating? Where is it working, and where are the gaps still wide open?

So, we ran a structured survey across the portfolio, with detailed inputs from key leaders.

We complemented this with practitioner conversations — CHRO roundtables, industry events, and one-on-one discussions with people leaders across India and globally.

Contributors from the broader practitioner community include Aru Uppal (Intangles), Sahil Sharma (RateGain), Ritu Agast, Priya Singh, Upashna Agarwal, Salil Chinchore, and Vidit Baxi (Safe Security) —spanning roles across HR leadership, talent strategy, and organisational design.

The report brings together three perspectives: where our portfolio companies are today in terms of AI adoption, what the broader practitioner community is seeing and doing, and where the gaps remain — honestly — for all of us.

Key takeaways

1. AI is a productivity multiplier.
   The org chart has not caught up. In some portfolio companies, the same team
   is delivering significantly more than two years ago. But headcount has not
   dropped. Structures have not been redesigned. Most companies are layering AI
   onto existing ways of working rather than rethinking from the task up.
2. Hiring is breaking in real time.
   Candidates are using AI tools during interviews without disclosure. The CV is becoming a structurally weak signal. What companies are hiring for now is learning velocity — someone who taught themselves a new framework in the last twelve months is consistently more attractive than someone with a decade of static experience.
3. One question that’s reshaping org design.
   Before any new hire is approved: can an agent do this job? Companies making this a mandatory step are finding that teams stop proposing roles that would not survive the question.
4. Compensation benchmarking is becoming obsolete.
   Survey data is typically six months old by publication. Role definitions are shifting faster than benchmarks can track. Skills-based pay remains aspiration, not practice — and the companies that figure it out first will have a meaningful talent advantage.
5. The human cost is real and underinvested.
   Anxiety about role displacement is present across nearly every company that responded, particularly in technology functions. The organisations handling it well are not offering reassurance. They are being honest about what is changing and making experimentation safe.
6. Culture is the unlock, not training.
   The signal that a company is ready for AI adoption is not whether a training programme exists. It is whether the leaders are the first ones using the tools.‍‍

India has a structural advantage nobody is talking about. Two decades of BPO and GCC work built a national muscle for deconstructing work — figuring out which parts of a job can be separated and systematised.

That is exactly the thinking AI-driven redesign requires.

What the full report covers‍

The report goes deeper into how portfolio companies are building internal AI capability — from AI champions programmes to workforce segmentation frameworks. It covers how practitioners globally are rethinking hiring, compensation, and operating models. It includes observations on why the emerging AI leadership roles often fail, who should own the human side of AI adoption inside an organisation, and four questions designed to surface where the most important gaps are.

What comes next‍

We plan to build on this as an ongoing series — going deeper into how AI is being embedded across specific functions like marketing, finance, and HR, combining insights from within the portfolio and the broader ecosystem.