India's AI workforce is the world's most active. The impact should be bigger

By: Avani Prabhakar

Recent research shows that 98% of Indian workers use AI at work – the highest rate of anywhere in the world. And yet, something is not adding up. Projects aren’t being completed faster. More innovation isn’t underway. Collaboration has not become meaningfully easier.

In my role – which deliberately brings together unifies People strategy and AI Enablement – leading our global workforce’s AI transformation journey, I've asked myself the same question every Indian and global enterprise leader is now facing: how do you turn individual AI usage into team-level impact?

The answer is not about the tools. It is about how and where they are being applied. Many AI tools are optimised for the individual and are being layered on top of disconnected workflows – but the most meaningful work happens in teams. That is why leaders aren’t seeing the return on AI.

The real problem – A coordination crisis

The research shows a growing gap between effort and impact in Indian organisations. Knowledge workers juggle an average of eight projects simultaneously – a pace that speaks to the ambition embedded in how work here gets done. 

Workers are spending significant portions of their week chasing context, switching between tools, aligning stakeholders, and updating status. These are activities that sit around the edges of their actual roles, not at the heart of them.

 Only 58% say they are operating at a comfortable pace. AI may be helping individuals move faster on their tasks, but it is not fixing how work flows across teams.

Consider the work that actually matters: a product launch, a quarterly business review, an incident response, and a customer journey. None of these live in one person's inbox. They span teams, disciplines, and decision points. 

In India, the process carries an additional structural dimension. The country's GCC ecosystem means that Indian-based teams are frequently the connective tissue for global organisations, coordinating across time zones and geographies by default.

In my experience, R&D teams that build core products across India – where we have more than 2,000 employees – Australia, the US, and EMEA, this scenario is the daily reality. When coordination breaks down at that level, the costs compound across every timezone it touches.

Without considered, strategic AI enablement, workers move faster individually, but collective clarity does not improve. 

Teams that still rely on meetings or message threads to understand what is happening will likely find that work is duplicated because there is no shared visibility – parallel teams could be working on similar analyses without knowing the other exists. In this environment trust erodes and time is wasted. And AI, rather than solving this, can actually accelerate the fragmentation if it's only applied at the individual level.

Only 13% of companies globally report having what could be called a “thriving AI culture”. That is not a tooling deficit. It is a leadership opportunity. And here, India's people leaders have a distinct advantage that their counterparts in many Western markets do not.

India’s knowledge workers are already the most AI-eager workforce in the world. Some 47% have access to extensive AI learning opportunities, and 19% already view AI as a teammate, compared to 15% globally. 

The cultural resistance that makes AI transformation slow and difficult in many markets is largely absent here. That means the challenge for Indian HR and people leaders is not convincing a reluctant workforce to adopt AI – it is channelling existing enthusiasm into team-level systems that improve coordination, collaboration, and decision-making. 

That is a fundamentally different and far more complex challenge to solve.

Such efforts can begin with shared goals and a live context. Different elements like objectives, roadmaps, and decisions exist where work happens, kept current by AI summaries that update as plans evolve, rather than sitting in static documents that go stale the moment they are shared. 

Transparent workflows, clear working agreements, and treating AI as a team sport are very important, and thus, success can be measured through outcomes like cycle time, rework, and decision latency.

Research shows that the organisations seeing the greatest benefits from AI are not simply rolling out more tools. 

They are integrating AI into team context, culture, and workflows, and the results reflect it – including up to a 9.4x higher likelihood of improved collaboration.

 Their practices share common patterns: they take a context-first approach to planning, centralise project briefs, customer insights and risk registers, and use AI to continuously synthesise signals – such as decisions made, blockers raised and scope changes. 

The outcome is that anyone can join a project midstream and still contribute meaningfully – and AI is an embedded, accurate, impactful part of the workflow.

Why India is positioned to lead

India’s workforce has both the appetite and scale to lead. Extremely high AI usage shows a real willingness to experiment, and dense, cross-functional teams in services, product, and digital operations provide a strong environment for rapid learning. 

The GCC ecosystem adds another dimension: Indian teams already have experience operating across organisational boundaries, geographies, and time zones. 

If AI can solve coordination challenges anywhere, India is uniquely positioned to demonstrate how to scale.

The data confirms what I see on the ground: the problem is not willingness; it is structure. The research shows that 43% of Indian workers say their existing technology does not support collaboration well, despite the country leading the world in AI adoption. Indian workers are ready, but the systems around them are not.

AI transformation is not a start-and-stop motion – it is continuous. The leaders and organisations that treat AI as an ongoing practice of experimentation, measurement, and redesign will pull ahead. At Atlassian, we are committed to sharing what we learn as we go, because no single company has all the answers, and the playbook for this era is still being written.

I am convinced of one thing: India does not need more AI adoption. It needs AI coordination. And the leaders who build for that – who focus on teams, not just tools – will define what comes next.

About the Author: Avani Prabhakar, Chief People and AI Enablement Officer at Atlassian, leads the company's People and Transformations organisation, focusing on unlocking workforce potential in the AI era. She is driving the cultural shift needed alongside AI adoption, building AI-fluent teams and embedding upskilling, innovation and modern ways of working across the business. With more than 20 years of experience across technology, aviation, engineering, professional services and consulting, Prabhakar has played a key role in shaping Atlassian's Team Anywhere model while championing practical, people-first approaches to human and AI collaboration in high-growth organisations.