Aruna Jayanthi on the Gravity of Work Behind India’s Next Technology Era

Before India became a global shorthand for IT and technology services capability, the industry was being shaped through quieter forms of work: client projects, delivery pressure, successful deployments, operational failures, and young professionals learning how software behaved once it entered the real world.

Aruna Jayanthi entered the industry in that formative period.

One of her early assignments was a maintenance project. From the outside, it appeared less exciting than building something new. But the work carried a deeper education. A maintenance analyst could not look only at one module or one clean piece of code. The problem could sit anywhere, and the answer required a wider view of dependencies, users, process, consequence and failure.

That early exposure gave Aruna a lesson that would travel through four decades of leadership: the real gravity of work often lies in learning how the larger system behaves, where it breaks, and what it takes to make it work better.

Across her years at Capgemini, where she led India, global business services, Asia Pacific, Canada and Latin America, and later through board roles and work with founders, the same instinct kept returning. Technology had to be understood through business processes. Scale had to be understood through culture. Services had to be understood through outcomes. Leadership had to be understood through the intelligence sitting closest to customers and teams.

“It was never about career,” she says. “I never woke up and thought about how am I going to become a CEO.”

For Aruna, the challenge in front of her came first. The title came later.

That philosophy gives weight to her reading of India’s technology services moment. The industry has earned global credibility through execution and scale. Its next phase will depend on something more demanding: the ability to redesign the model that made it successful, engineer a structural shift around enterprise AI platforms and services, and create value through the orchestration of people, platforms and intelligent agents.

A reputation to build from

Aruna is careful about the way India’s technology story is framed. The industry’s early advantage is often reduced to cost and labour, but her reading is wider. If price had been the decisive factor, global technology work could have moved to several other geographies. India endured because it learned quickly, handled complexity, delivered reliably and created confidence at scale.

When asked whether India’s association with technology delivery has become restrictive, she pushes back with a useful correction.

“When somebody thinks technology, they think India,” she says. “What’s wrong with that?”

For Aruna, a strong global association is an advantage if the country keeps building on top of it. The next layer has to come from deeper research, stronger entrepreneurship, sharper problem selection, more original innovation and serious intellectual property creation.

She is direct about the R&D gap. Government support has a role, but a deeper innovation culture will also require large companies to invest with longer horizons and greater seriousness. During a recent visit to Bengaluru, she met founders working across AI, energy optimization, testing tools, sustainability, defence, healthcare, deep tech and other emerging spaces. The energy, she says, was almost physical.

The opportunity, in her view, is to use technology to solve harder problems at scale, especially in sectors where India’s complexity can become a testing ground for globally relevant solutions. The next phase will ask whether Indian companies, founders and institutions can become architects of game-changing technologies and solutions, create intellectual property, serve national priorities, reduce dependence on expensive imports and address global markets with greater confidence.

Beyond headcount

One of Aruna’s clearest arguments is about the future of technology services.

For years, the industry measured itself through people, effort, utilization and delivery capacity. Headcount became a visible shorthand for scale. Larger teams meant larger mandates, and larger mandates became a signal of trust. The model begins to weaken when clients expect business outcomes rather than effort, and it will shift even further as digital agents take on more execution.

The future, she argues, has to be measured through value.

One example she gives is outcome-linked pricing. A partner could commit to a business result instead of simply billing for effort.

“I will deliver this business outcome for you, which is to reduce your cost by 10 percent,” she says. “If I manage to do it by 12 percent, we share the profit of that remaining 2 percent.”

The shift is significant because the partner is taking responsibility for value created and sharing in the upside when the outcome improves beyond the baseline. Technology partners have to understand the business consequence of their work, while clients have to evaluate partners through impact rather than activity.

As AI agents become part of enterprise delivery, scale will increasingly include a combination of humans, digital agents, platforms and orchestration capability. In Aruna’s framing, the next technology-services leader will need to understand customer economics, process design, automation, risk, sector context, AI-agent capacity and outcomes with the same seriousness earlier generations brought to delivery discipline.

The process beneath the platform

Aruna’s view of digital transformation is practical and unsentimental. Many companies begin with the technology. They choose a platform, approve a budget, start the implementation and later discover that the business process beneath the system was never properly questioned.

Her point is clear: transformation has to begin with what the business wants to become.

“Your technology is only as effective as your business process is effective,” she says.

A company implementing Salesforce, for instance, has to examine how sales actually happens, how customers are understood, how leads move, how accountability is assigned, how managers intervene and where decisions slow down. An ERP implementation raises similar questions. The system may be modern, while the operating model can remain old.

“The question is not about what technology am I going to implement,” she says. “The question is how am I going to run my business, and in order to run that most efficiently, what technology would be the right one to do.”

Many failures occur because organizations automate inherited confusion. Existing habits enter the new platform. Fragmented responsibilities become digital workflows. Slow approvals acquire better interfaces. People then blame the technology for a problem that began in design, ownership and leadership.

Simplicity, in her reading, is an operating discipline. It requires leaders to understand how work moves across the organization, where customers experience friction, how vendors interact, what employees actually adopt and which decisions must be redesigned before any tool can make a difference.

What makes integration real

Integrating acquisitions gave Aruna a different kind of test. Large integrations are often described through structures, synergies, reporting lines and financial logic. Inside an organization, people read something more personal: whether they are respected, whether their leaders still matter, whether customers remain protected and whether the acquiring company treats them as equal participants in the future.

Aruna’s emphasis is on the human and cultural work beneath the formal integration. Senior people from the acquired organization need meaningful roles. Customers need confidence that value will continue. Employees need signals that the new system will recognize their history and capability. Even small decisions can carry meaning because people are searching for evidence of how they are being seen.

The acquiring organization sets the tone through behavior. If it behaves like a winner absorbing a weaker system, the integration will carry resentment. If it treats the incoming organization as a source of capability, memory and trust, the combined institution has a better chance of becoming stronger than either part alone.

Culture is built through decisions people can observe. Titles, meetings and announcements matter, but people remember whether they experienced fairness in the transition.

Intelligence comes from the edge

One of the most revealing stories Aruna tells is about an innovation council.

She had assembled senior leaders to judge ideas contributed from within the organization. Someone challenged the logic and asked why a 25-year-old could not be part of the jury. Aruna accepted the point and changed the jury.

The story matters because it shows a leadership instinct that becomes more important as industries move faster. Intelligence does not always travel through hierarchy. The employee closest to a customer, a tool, a workflow or a market shift may see change before formal leadership has language for it.

“Customer intelligence always comes from the field,” she says.

A senior leader’s role is also to design systems where useful intelligence can surface without being filtered out by title, age or institutional habit. In AI, customer experience, automation, cybersecurity, product design and organizational change, the people closest to the work often see the future earlier. Leadership has to create enough openness for those signals to reach the center.

AI and the next use of capacity

Aruna’s view of AI is neither fear-led nor casually enthusiastic. She sees the efficiency potential clearly, and she is equally interested in what the released capacity can make possible.

If AI takes over and reduces as much as 90 percent of a certain type of work, the managerial question should not end with productivity gains or cost reduction. The more ambitious question is what the organization can now do with the capacity released, combined with the potential of AI. Can it serve more customers? Can it improve quality? Can it move into harder problems? Can it build new products? Can it make decisions faster and with better evidence? Can it create what she calls a 10x value opportunity?

The framing matters because AI is often discussed through substitution. Aruna brings it back to ambition. Efficiency has value, but leadership is tested by what it chooses to build after efficiency becomes available.

The same idea applies to talent. The future professional cannot survive only on technical skill. Aruna repeatedly returns to the need for business understanding: customer economics, process, regulation, consequence and the ability to see how technology changes work in the real world.

Capability built around a tool can expire quickly. Capability built around judgment compounds.

From executive power to board judgment

Aruna’s board work has given her another vantage point on leadership.

Operating leaders are expected to act. Board leaders have to question, guide and challenge while allowing management to own execution. The power is different because the distance is different.

Her examples are practical. A board member may ask why a factory has a certain cost structure, whether a market expansion is properly understood, whether investment choices are aligned with the strategic vision, whether AI is being treated seriously enough or whether management has examined the right alternatives.

The board’s job is to improve the quality of thinking without becoming the operating team.

That requires restraint. It also requires courage. A board that is too passive becomes ceremonial. A board that starts running the company weakens management accountability. The work lies in asking the question that changes the conversation.

For Aruna, this is another form of judgment: knowing where to intervene, where to listen, where to push and where to let management own the answer.

The next chapter

Aruna’s current chapter brings her closer to founders, smaller companies and social enterprises trying to scale.

Many of them come with ambition, energy and product ideas, but need help with structure, governance, market access, partner channels, leadership teams and the transition from informal founder-led execution to a more scalable enterprise.

That work seems to interest her because it draws on accumulated operating experience. She has led large businesses, integrated organizations, worked across markets, handled customers, built teams and sat in boardrooms. The value now lies in helping others avoid predictable mistakes and build stronger institutions earlier.

There is a quiet continuity here. The young analyst who learned to understand a maintenance system now advises founders on the systems they must build around their own ambition.

What her career leaves for leaders

Eight lessons stand out from Aruna Jayanthi’s career

1. Treat the role in front of you as complete work. A career compounds when each responsibility is taken seriously enough to build credibility, judgment and trust.

2. Measure value by outcomes. Numbers may signal reach, but the real test is whether the work enhances value, quality, experience or resilience for the client.

3. Begin transformation with the business process. Technology adds value when the operating model beneath it has been properly understood.

4. Read the signals people receive. In integrations, culture is shaped through roles, tools, customers, authority and small gestures that people remember.

5. Respect unglamorous work. The assignment that appears quiet may teach the widest view of the system.

6. Let intelligence travel upward. The field often sees change before formal authority recognizes it.

7. Use AI to expand ambition. Efficiency matters, but the bigger question is what new capacity the organization can create.

8. In governance, ask better questions. Board leadership requires restraint, clarity and the ability to challenge without taking over.

Closing Reflections

Aruna Jayanthi’s career keeps returning to one discipline: take the assignment seriously enough to understand the system beneath it. That discipline carried her from early technology delivery to country leadership, global businesses, integrations, boards and now conversations with founders trying to scale.

The judgment she speaks from was built through unglamorous work, hard transitions, customer proximity, institutional patience and the ability to ask better questions as one moves from doing the work to shaping the conditions in which others can do it well.

For India’s technology services industry, execution created credibility. For leaders like Aruna, the next contribution lies in helping that credibility mature into original problem-solving, enterprise AI capability and institutions capable of building what the next era will demand.