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India’s Space Tech Looks to Budget 2026 to Ignite Ambitions

India’s space tech story has come a long way, but Union Budget 2026 may shape the sector’s next decade of growth. The government targets growing the space economy to $44 billion by 2033, with Earth observation, communication, navigation, launch services, and in-orbit services as core segments.

In the Budget last year, the total allocation for the Department of Space increased to ₹13,416.20 crore, an increase of approximately 14% from the previous year’s revised estimates to support missions like Chandrayaan-4 and the Venus Orbiter Mission. However, the Indian Space Research Organisation (ISRO) was only able to execute five launches in 2025.

The buzz is still strong. Last year, ISRO was able to demonstrate space docking. States including Karnataka, Tamil Nadu, Andhra Pradesh, and Gujarat upped the ante with space policies dedicated to fostering private sector growth, manufacturing, and innovation. Private funding returned after a slow patch, with the Indian National Space Promotion and Authorisation Centre (IN-SPACe) and SIDBI Venture Capital also launching a dedicated ₹1,000 crore fund.

For the upcoming Budget, startups now seek clarity on demand, tax reform, procurement, and insurance support.

Launches Continue Despite Setbacks

ISRO’s missions over the past year reflected both ambition and risk. The EOS-N1 mission aboard PSLV-C62, the launch carrying 16 payloads in total, experienced an anomaly during the third stage. Earlier, another PSLV setback (C61 launch in May 2025) raised concerns, but startups signalled resilience across the ecosystem.

As launch cadence rises, some founders want policy to look beyond rockets and satellites. Sakthikumar R, founder and CEO of OrbitAID Aerospace, says India must rethink where value is created.

“To secure long-term leadership in the space economy, India must evolve from a launch-enabled nation to an in-orbit systems nation,” he tells AIM, adding that the Union Budget should introduce a National In-Orbit Infrastructure Mission focused on satellite life-extension, autonomous refuelling, and active debris risk management.

He adds that shared testbeds and mission-risk frameworks would reduce barriers for private firms. “By institutionalising failure-tolerant innovation and open access to ISRO-class facilities, India can set global standards for sustainable, service-driven space operations,” he says.

At the same time, private firms have expanded downstream capabilities. Geographic information systems software provider Esri India partnered with Dhruva Space to widen access to satellite data. AWS expanded its Space Accelerator programme to support 42 Indian startups. Even global startups such as Starcloud drew attention for training large language models in space using NVIDIA H100 chips.

Agendra Kumar, managing director at Esri India, says geospatial technologies are being recognised as critical technologies for national security, governance, and economic development. The National Geospatial Mission, announced in the Union Budget 2025, also strengthened India’s geospatial infrastructure and data ecosystem.

He adds, “As the next step, the government must allocate adequate funds so that the roll-out of this programme can gain speed and provide the data and infrastructure to support numerous other programmes and initiatives of various ministries.”

Funding is Back But Still Uneven

Private capital into Indian space startups came back with a bang after a relative lull in 2024, with startups including Pixxel, TakeMe2Space, Agnikul Cosmos, Skyroot Aerospace, and EtherealX raising private equity. Downstream analytics companies, too, raised early rounds.

However, founders say capital alone does not solve scale challenges. Long development cycles and delayed revenues make space different from other deep tech sectors. Industry bodies argue that access to low-cost capital depends on how the government classifies space assets.

The Indian Space Association (ISpA) and Deloitte India have urged the government to recognise space and satellite infrastructure as critical infrastructure. Such a move could reduce financing costs and unlock long-term lending. The recommendations include including space infrastructure under the Harmonised Master List of Infrastructure Sub-Sectors and enabling access to bonds, viability gap funding, and development finance institutions.

Rashmit Singh Sukhmani, co-founder and CTO at SatSure, says, “As we look to Budget 2026–27, recognising space and satellite infrastructure as critical infrastructure and enabling predictable demand, including government procurement mandates, will be key to unlocking long-term, infrastructure-grade capital for an industry with 5–7 year gestation cycles.”

While funds and policies today strongly support satellite manufacturing and launch, there is also a need to invest in compute infrastructure.

“As satellites generate massive volumes of sensitive data, greater focus is needed on data storage, processing, and GPU nodes for geo AI, along with expanding ground station networks in India, so this data can be securely stored and processed within the country,” adds Gaurav Seth, co-founder and CEO at PierSight.

The Cost Question

Manufacturing remains a pressure point for the sector. Import dependence for space-grade components raises costs and delays schedules. Companies argue that existing tax structures treat space hardware the same as general electronics, creating friction.

Keyur Gandhi, director of space regulatory and commercialisation at Dhruva Space, says, “Introducing dedicated, granular HSN and SAC codes for space-grade components and services—distinct from general aerospace or electronics—would reduce GST burdens, unblock input tax credits, and provide clarity on domestic value addition and import dependence.”

He also notes that extending SEZ-equivalent indirect tax benefits could lower project costs and unlock working capital.

Additionally, operational delays matter. Shravan Bhati, co-founder and CEO of SatLeo Labs, says, “For payload and satellite startups, importing critical tools and components still requires licences that take 4–5 months, even for government-recognised companies, leading to avoidable launch delays.”

“There is a strong case for single-window, fast-track clearances and smoother customs processes for strategic space tech imports,” he adds.

Demand is Still Missing

While supply-side incentives exist, companies stress that demand creation matters more. Government procurement remains limited, and pilots often fail to scale.

Krishanu Acharya, co-founder and CEO of space data analytics firm Suhora Technologies, points out, “We expect targeted measures to accelerate the downstream space economy, particularly in converting satellite data into actionable insights for defence, agriculture, disaster management, and climate resilience.”

“We need the Budget to bridge the gap from pilots to scale,” he asserts.

Industry bodies propose procurement mandates that require a fixed share of government space spending to flow to private firms. Similar models exist in the US and Europe. ISpA proposed a 50% mandate for sourcing space-based services and hardware from Indian private entities.

The procurement debate also extends to how the government evaluates technology. Several founders argue that price-led tendering discourages the development of advanced capabilities, especially in strategic domains. Sanjay Kumar, founder and CEO of EON Space Labs, notes that the current approach limits innovation.

“The L1 system prioritises price over capability, sidelining private firms offering more advanced technologies,” he says. Kumar pointed to recommendations from the Economic Survey and defence procurement reviews, calling for quality-cum-cost based selection (QCBS) for high-technology purchases.

“We recommend a mandatory adoption of QCBS for high-technology procurements in EO-IR systems, optical payloads, and advanced sensors, with technical-to-commercial weightage ratios from 60:40 to 80:20,” he remarks.

He adds that indigenous manufacturing must also go beyond assembly. “We also request an Indigenous Content Premium allowing up to 20% price preference for vendors demonstrating core design and manufacturing capabilities in India.”

While programmes such as iDEX, which aim to create self-reliance in defence and aerospace, have expanded startup participation, founders say structural gaps remain between prototyping and scale.

“The iDEX programme has been transformative, with over 430 contracts signed and ₹449.62 crore allocated for FY 2025–26,” Kumar mentions. “However, defence startups face structural challenges.”

He flags the transition between lab success and commercial deployment as the weakest link, pointing out that there is a need to bridge the technology readiness levels (TRL) 4–5 gap, a critical stage where most innovation falters.

He adds that startups should be guaranteed procurement commitments after successfully completing iDEX challenges. This will help convert prototypes into orders without the need to re-tender under the L1 bidding system.

States are also stepping in.

Karnataka has set an ambitious target to capture 50% of India’s space market by 2033, leveraging its legacy as the nation’s primary space hub. Not far behind, Madhya Pradesh recently launched its SpaceTech Policy-2026, eyeing ₹1,000 crore in investment by positioning itself as a center for satellite manufacturing and geospatial applications.

For India’s space ecosystem, Budget 2026–27 may matter less about the numbers and more about the intent.

The post India’s Space Tech Looks to Budget 2026 to Ignite Ambitions appeared first on Analytics India Magazine.

Why The AI Foundry by Tredence in Chennai is a Working Room for Builders, Not Another Conference

The AI Foundry by Tredence is coming to Chennai next month for the second edition with a format that is deliberately different from most AI meetups. This is not a conference, a talk series, or a demo showcase. It is a four-hour working session built for people who are already designing and deploying generative AI and agentic AI systems in production.

Scheduled for February 7, 2026, at Tredence’s Chennai office, the invite-only workshop brings together a small group of senior engineers, architects and data scientists to work through a real-world problem statement from design to deployment.

Register Now!
Date: February 7, 2026
Time: 10.00 am – 5.00 pm
Location: Tredence Analytics Solutions Pvt, Global Infocity Park, Chennai

The organisers describe the AI Foundry as a solutioning forum for AI builders. Tredence and AIM are giving a platform for developers and engineers working in generative AI and agentic AI to present solutions and gain insights from experts.

The preferred participants include data scientists and principal data scientists, applied AI scientists and AI solutions architect, decision scientists and technical leads, applied machine learning engineers, platform and cloud architects, DevOps and ML platform engineers, generative AI engineers and prompt engineers, LLM application developers, AI product engineers, MLOps specialists, and forward deployed engineers (FDEs)

The organisers describe the AI Foundry as a solutioning forum for AI builders. The focus is on co-creating systems that can move beyond proofs of concept and survive enterprise conditions. Participants will work in groups to map user journeys, design agentic workflows, define system blueprints and think through deployment, monitoring and governance.

The intent is simple. Show what it actually takes to build usable, trusted and scalable AI systems.

During the session, participants will design how users interact with AI-driven workflows, identify human-in-the-loop moments, and structure decision paths. They will outline high-level architectures that combine generative models, agents and orchestration layers. They will also propose deployment designs that address reliability, security and scale.

Trust and adoption are central themes. Teams will explore and explain governance and transparency mechanisms that determine whether AI systems are accepted within real organisations.

The workshop is aimed at people who design systems, run platforms, ship models, and troubleshoot failures.

For those already wrestling with orchestration, scale, monitoring and trust in enterprise AI, the Chennai edition is positioned as a rare working room to think through what production really demands.

Register Now!
Date: February 7, 2026
Time: 10.00 am – 5.00 pm
Location: Tredence Analytics Solutions Pvt, Global Infocity Park, Chennai

The post Why The AI Foundry by Tredence in Chennai is a Working Room for Builders, Not Another Conference appeared first on Analytics India Magazine.

Ex-Google Executive Peeyush Ranjan Launches AI EdTech Startup Fermi.ai in India & USA

Former Google GM and VP Peeyush Ranjan has launched Fermi.ai, an AI-first edtech startup aimed at transforming high-school STEM education across India and the United States.

Headquartered in Singapore, the company is rolling out its learning platform through subsidiaries in both countries, beginning with mathematics, physics and chemistry.

Fermi.ai is built around what the company calls “productive struggle”, a learning philosophy that encourages students to work through mistakes and strengthen conceptual understanding rather than rely on shortcuts. The platform uses AI to analyse how a student arrives at an answer, identifying gaps in reasoning and offering step-by-step guidance instead of direct solutions.

“Students today are getting answers faster than ever, but their understanding is getting weaker,” Ranjan said, who has also served as CTO of Flipkart and held leadership roles at Airbnb. “We built Fermi.ai to support thinking, not replace it, and to give educators visibility into struggles that usually stay hidden.”

The startup has emerged from Meraki Labs, where Ranjan partners with entrepreneur Mukesh Bansal, founder of Myntra. Bansal said Fermi.ai focuses on mapping a student’s thought process rather than solving problems for them. “It’s about showing students how they think, and helping teachers guide them back to mastery,” he noted.

Bansal also launched Nurix, which is another emerging AI startup focused on building AI-native consumer and internet products.

Fermi.ai’s platform is built around four core components: an adaptive real-time tutor that provides pedagogically guided hints, a stylus-first smart canvas designed for handwritten equations and diagrams, a concept-linked question bank aligned with exams such as AP, IB and JEE, and an analytics layer that pinpoints where student reasoning breaks down.

Before its public launch, the company conducted a three-month pilot with 79 students, covering over 15,000 concept tests. According to the startup, students who initially struggled showed an average improvement of 4.68 points by their final attempts, while heavy users demonstrated higher mastery gains and reduced dependence on hints.

The cloud-based platform is currently available for free at fermi.ai, with a dedicated pilot programme for educators launching in 2026.

The post Ex-Google Executive Peeyush Ranjan Launches AI EdTech Startup Fermi.ai in India & USA appeared first on Analytics India Magazine.

CitiusTech Partners with Ventra Health to Build Agentic AI Revenue Intelligence Platform

Healthcare technology services firm CitiusTech has partnered with Ventra Health to develop an agentic AI-powered revenue intelligence platform to improve revenue cycle management for healthcare providers.

The platform, branded vCision, uses AI-driven automation and adaptive models to identify revenue leakage, reduce claim denials, and improve reimbursement outcomes across complex billing workflows.

The companies said early deployments have shown a 19% improvement in first-pass payment rates and a 26% reduction in initial denial rates, along with faster recovery of delayed reimbursements.

Under the partnership, CitiusTech will support the engineering, data, and AI development of the platform, bringing its capabilities in healthcare technology, generative AI, and intelligent automation. Ventra Health is also setting up a new GCC, focused on engineering, data, and platform delivery to scale AI solutions across its operations.

The vCision platform is designed to help revenue cycle teams improve processing accuracy, anticipate changing reimbursement behaviour, and adapt to evolving payer guidelines. It also integrates real-time training and education for operational staff and extends Ventra’s enterprise analytics platform, vSight, launched in late 2023.

Rajan Kohli, CEO of CitiusTech, said the collaboration is focused on embedding AI-driven intelligence into revenue operations to improve financial predictability and reduce revenue loss. Ventra Health CEO Steven Huddleston said the platform will enable faster, more informed decision-making as reimbursement requirements continue to shift.

Ventra Health provides revenue cycle management services to facility-based physician groups across specialties including anaesthesia, emergency medicine, hospital medicine, pathology, and radiology.

The post CitiusTech Partners with Ventra Health to Build Agentic AI Revenue Intelligence Platform appeared first on Analytics India Magazine.

What Leaders Believe is the Next Frontier in India’s GCC Story

India’s GCC story isn’t new, but for years, its true significance remained largely out of sight.

Back in 1985, Texas Instruments (TI) became the first multinational to set up a wholly owned R&D center in India. Located in Bengaluru, this facility was never just a cost-saving move. It signalled the start of something much bigger.

For more than a decade, India’s GCCs were defined by scale. They hired in the thousands, ran global processes at speed, and helped multinational companies operate more efficiently. Cost advantage was the headline. Execution was the mandate.

That era is now decisively behind us.

In 2026, GCCs are redefined beyond headcounts. What matters is what they own, which decisions they influence, and the business outcomes they are accountable for.

Global companies today are operating in an environment shaped by economic uncertainty, tighter regulations, rapid advances in AI, and growing expectations around security and trust. The focus is no longer on cost arbitrage, but on where critical work can be delivered with depth, speed, and reliability.

From Scale to Strategic Weight

India today hosts more than 1,850 GCCs employing nearly 2.2 million professionals. In 2025 alone, over 100 new GCCs were established in the country—a clear sign of sustained global confidence in India as a long-term base for building capability.

But what is fundamentally changing is the nature of these centres.

“The global frontier in 2026 will be shaped by a very different kind of GCC,” Milesh J, head of strategy and operations at SAP Labs India, tells AIM. “India is no longer just executing work. It is becoming the place where products are built, decisions are made, and enterprise priorities are shaped.”

This shift is deliberate. Global firms are pushing more ownership into their India centres, across product development, AI platforms, analytics, cybersecurity, and core R&D. The objective is greater speed, stronger resilience, and tighter alignment between strategy and execution.

In many organisations, India-based GCCs are now expected to operate as true extensions of the global enterprise, rather than downstream delivery arms.

One of the clearest markers of this evolution is product ownership.

“India is becoming the world’s product headquarters,” Milesh notes. “GCCs are mastering entire product lifecycles, from strategy to delivery and continuous innovation.”

This represents a decisive break from the past. Instead of supporting discrete modules or executing pre-defined roadmaps, GCC teams are now responsible for end-to-end product decisions, design, engineering, testing, deployment, and ongoing iteration.

The drivers are practical. Global companies want faster experimentation, shorter release cycles, and greater accountability. When product decisions and engineering teams sit closer together, feedback loops tighten, and execution improves.

This model, Milesh explains, creates a flywheel effect, where integrated applications generate high-quality data, data powers AI-driven decisions, and those decisions continuously refine business processes, generating even more value over time.

Pankaj Sachdeva, VP, data science & analytics and MD, India at Pitney Bowes, tells AIM that the most successful GCCs will be those that combine deep domain knowledge with strong engineering capabilities, while staying closely aligned with broader enterprise strategies and customer needs.

As a result, talent readiness is emerging as a defining priority. GCCs are accelerating investments in specialised skills such as AI, cybersecurity, and full-stack development, while building multi-skilled teams capable of supporting global roles.

AI Moves From Showcase to Backbone

If 2024 and early 2025 were about experimenting with AI, 2026 will be about living with it.

According to the EY GCC Pulse Survey 2025, 58% of India’s GCCs are already investing in agentic AI, while another 29% are planning to scale deployments soon. GenAI adoption is even more widespread, with 83% of GCCs investing in it.

The shift is also visible in execution. Pilots have grown from 37% in 2024 to 43% in 2025, with upskilling initiatives, like GenAI training, now reaching 81% of GCCs.

Across India’s GCC ecosystem, AI is moving beyond pilots and proofs of concept. It is increasingly embedded into everyday workflows, quietly improving speed, quality, and decision-making.

“AI is no longer a showcase technology,” Arvind Chittora, MD at Sonoco Performance Hub, explains. “It has become a workflow enabler. The real test now is whether GCCs can use AI to shape outcomes, not just deliver outputs.”

Chittora added that India-based GCCs are increasingly emerging as global centres of excellence for analytics and AI.

In many multinational firms, these teams now define standards for data architecture, model governance, and responsible AI practices.

However, this shift, as Chittora believes, comes with higher expectations. AI systems deployed at scale must be explainable, auditable, and secure, especially in regulated industries. As a result, governance is no longer an afterthought.

In this regard, Balu Chaturvedula, the SVP and country head at Walmart Global Tech, reveals how the evolution has moved rapidly from traditional models to generative AI, then to multimodal systems, and now toward AI that can operate with increasing autonomy in decision-making. His phrase “AI everywhere” captures this shift towards intelligence being embedded across systems and workflows.

Chaturvedula points to a second trend he calls “autonomous everywhere”, driven by the rise of physical AI. “Physical AI is rampant right now,” he said, pointing to Walmart’s significant investments in automation.

Taking an example, he explains, “Walmart has made humongous investments in physical AI. We have taken a significant leap in automating our entire data centre and certain formats.”

He emphasises that this was not a recent move but a long-term transformation. “This journey is not now; it’s been a journey for five years. It’s a very capital-intensive journey, but we thought that’s the only way we can change the way we serve our customers, and we are much ahead in that journey.”

Trust Becomes a Strategic Advantage

As Indian GCCs take on greater responsibility for decision-making systems, trust has moved to the centre of the conversation.

“Trust has become a strategic edge,” says Milesh. “Cyber resilience, data sovereignty, and responsible AI are now board-mandated priorities.”

Security, compliance, and ethics no longer support functions sitting outside product teams. They are being built directly into development cycles, with close collaboration between technology, legal, and risk teams.

SAP Labs India, for instance, is emerging as a strategic anchor for ethical AI and cybersecurity, guided by SAP’s AI ethics policy aligned with the UNESCO’s Recommendation on the Ethics of AI. This alignment positions India not just as a builder of AI systems, but as a steward of responsible and trustworthy innovation.

Across the ecosystem, leaders agree on one principle: speed cannot come at the cost of integrity.

“Every technology introduces exposure and vulnerability,” Chaturvedula cautions.

Without strong threat detection, secure system design, and properly structured access controls, the risks multiply. “If you don’t do threat detection properly, if you don’t do underlying security properly, if data isn’t structured with the right authentication and authorisation controls, we will be in a very big trouble spot,” he adds.

Talent Density Over Headcount

As GCC mandates deepen, the way they think about talent is also changing.

For years, growth was measured by headcount. That metric is losing relevance.

“Elite GCCs are prioritising depth and speed over headcount,” Milesh adds. “Roles are becoming more fluid, combining engineering, design, and AI ethics.”

This has intensified competition for specialised talent, particularly in AI engineering, data science, cloud, and cybersecurity. Yet, compensation alone is no longer enough to attract or retain top performers.

Engineers today want ownership: the chance to work on complex problems, influence decisions, and see the impact of their work on real products and customers.

Vijai Kishan, India site lead and head of India enterprise technology at Fidelity Investments, tells AIM that this evolution is already visible. “Our teams are not just supporting global work, they are shaping it. That requires deep technical skills, strong business understanding, and a continuous focus on learning.”

To meet these expectations, GCCs are redesigning career paths, enabling cross-functional rotations, and investing heavily in upskilling. Leadership density, rather than sheer team size, is becoming the differentiator.

Lighter Offices, Wider Footprints

The physical footprint of GCCs is changing as well.

Hybrid work is no longer a temporary arrangement; it has become a structural reality. As a result, many GCCs are moving away from large, long-term office leases and towards more flexible spaces with shorter commitments.

This flexibility allows companies to scale teams up or down as business needs change. It also enables hiring across multiple cities while maintaining a core presence in major innovation hubs.

Offices themselves are being redesigned—not for fixed seating, but for collaboration, labs, and secure environments for sensitive work.

At the same time, the rise of nano GCCs and mid-size GCCs is driving demand for flexible and managed workspaces.

“They want to operate asset-light, scale gradually, and focus on speed-to-market,” Gaurav Vasu, founder and CEO of UnearthInsight, a leading GCC intelligence and research firm, mentions. “That’s where flex spaces give them a massive advantage—not just on cost, but on bundled services, compliance, and readiness.”

This shift has accelerated the expansion of GCCs into tier-2 and tier-3 cities.

To reduce risk and tap broader talent pools, companies are setting up smaller satellite centres in cities such as Coimbatore, Ahmedabad, Indore, Lucknow, Mysuru, and Mangaluru.

These locations offer lower operational costs, strong talent availability, and higher employee retention.

Recent reports suggest demand for GCCs in tier-2 cities could grow by 30-40% in the coming years, with some centres achieving up to a 35% reduction in operating costs and a significant boost in profitability.

GCCs as Ecosystem Connectors

Beyond real estate and talent, GCCs are taking on a new role—becoming connectors within the innovation ecosystem.

Partnerships with universities, startups, and local innovation hubs are becoming more common. These collaborations support long-term capability building through joint research programmes, skill development initiatives, and early access to emerging technologies.

“GCCs are increasingly acting as bridges,” Anuj Khurana, co-founder and CEO of Anaptyss, says during an interaction. “They bring together academia, startups, and enterprise teams to create sustained innovation.”

This ecosystem-led approach reflects a more mature view of capability building—one that looks beyond immediate delivery needs to long-term resilience.

Perhaps the most important change underway is how success is measured.

“By 2026, GCCs will be judged by the value they create,” Khurana explains. “Not cost savings, but product quality, speed to market, risk reduction, and customer impact.”

Decision-making authority is gradually moving closer to India-based centres. With that authority comes accountability. GCC leaders are increasingly expected to co-own outcomes alongside global business teams.

Chittora captures this shift succinctly. “The real differentiator will not be capability, but authority. GCCs that can challenge assumptions, surface uncomfortable truths, and co-own outcomes will shape the enterprise. Others will remain service factories.”

The Next Chapter

India’s GCC ecosystem is entering its most consequential phase yet.

The foundations—scale, talent, and operational excellence—are already in place. What will define the next decade is how effectively GCCs convert these strengths into influence, ownership, and trust.

Those centres that invest early in AI at scale, leadership depth, governance, and real product ownership will evolve into global nerve centres—places where enterprise strategy is shaped, not just executed.

The post What Leaders Believe is the Next Frontier in India’s GCC Story appeared first on Analytics India Magazine.

Why Mphasis CEO Believes AI Can No Longer Be ‘Lipstick’ on Legacy IT

After decades of layering new software on top of ageing enterprise systems, companies are running into the limits of legacy technology, believes Mphasis CEO Nitin Rakesh.
In a detailed post-earnings interaction, Rakesh said the IT services firm is positioning its NeoIP platform—enabling agentic AI-led IT operations and observability—to help enterprises rethink how they modernise and operate long-standing core systems, using AI to extract intelligence and drive change, rather than simply automate around legacy constraints.

Rakesh traced the challenge back to the evolution of enterprise computing. Early software automated manual record-keeping in sectors such as banking and insurance. While the digital and cloud era improved reach and experience, core systems, many built in the 1970s and 1980s and still running on mainframes, largely remained untouched.

Enterprises, he added, have continued to add layers without fundamentally transforming systems of record. “We keep putting lipstick on the same thing,” he said in the Q3 earnings call press meet.

That model, Rakesh argued, has increasingly become unsustainable as real-time payments, instant onboarding and always-on digital experiences put pressure on systems never designed for such speed or scale.

Modernising By Shrinking the Core

Rather than advocating wholesale replacement of core systems, Mphasis focuses on extracting business intelligence from legacy platforms using data and AI to drive customer and operational experiences. This approach progressively reduces the complexity of the core until it becomes feasible to modernise.

Enterprises, Rakesh noted, often lack up-to-date documentation of how their systems actually work. Over decades of changes, the most accurate representation of business logic is not on paper anymore; it’s the code itself.
AI, he argued, makes it possible to relearn that logic far faster than traditional manual methods.

Rakesh cited the case of a large modernisation programme involving tens of millions of lines of legacy code. Where conventional approaches would have taken several years just to reverse-engineer business rules, Mphasis’ AI-assisted techniques compressed that phase by roughly 80%, completing it in a matter of months through iterative analysis.

Beyond “Break-Fix”

Rakesh said the same approach is extending into IT operations. Traditional “break-fix” models, where systems are repaired only after failures occur, are increasingly misaligned with AI-era expectations.

“Even your dumb car has a yellow light that tells you something is going wrong,” he said. “But our smart IT operations don’t do that even today.”

The goal, he said, is to move operations toward more predictive and preventive models, where incidents are anticipated and addressed earlier, reducing downtime and manual intervention over time.

Resetting Pricing And Delivery Models

These changes are also reshaping how Mphasis structures commercial engagements.

Rakesh said traditional IT services pricing, based on headcount, effort and long timelines, is gradually giving way to outcome-oriented models, particularly in large modernisation and operations deals. Historically, legacy modernisation programmes were priced over six to seven years based on estimated effort, often costing several dollars per line of code.
By re-engineering delivery using AI-assisted approaches, Mphasis is now committing to outcomes over shorter timeframes and at lower unit economics, Rakesh asserted.

“What the client cares about is the outcome,” Rakesh said, adding that customers are increasingly indifferent to how many people or tools are deployed at different stages, as long as delivery risk, timelines and results are clear.

He described this as “savings-led transformation”, where efficiencies in existing systems free up the budget for reinvestment rather than simply cutting spending.

Talent, Hiring And the Changing Pyramid

The shift toward AI-assisted delivery is also influencing workforce strategy. Rakesh said Mphasis has moved away from traditional campus hiring over the past two years, instead engaging candidates through internal programmes and hackathons focused on live projects and emerging technologies.

The most important attributes the company looks for, he said, are “learnability” and “technical skills”.
Hiring continues across experience levels based on project needs, including a higher intake of junior talent in the US. In the December quarter, the company reported a headcount of 31,272—an increase of 463 over the previous quarter.

Over time, Rakesh said the workforce structure could evolve toward a more fluid, diamond-shaped model rather than a classic pyramid, moving from junior-heavy structures to agile teams dominated by mid-level specialists. However, he emphasised that such changes will take several years and require alignment with customers.

Deal Momentum And AI Infusion

During Q3, Mphasis secured $428 million worth of new deal wins, with 62% of them being AI-led.

Responding to questions on deal wins, Rakesh said most recent engagements include elements of AI-led delivery, spanning modernisation, operations and software lifecycle transformation. Some deals require a three-to-six-month ramp-up before revenues flow, while others convert more quickly.

Responding to a question from AIM on disclosing AI revenue, Rakesh said the more relevant measure for him is how many customer engagements are being impacted by what the company is building, rather than carving out AI as a separate revenue line.

“What’s important to me is, are we bundling services and software together in how many engagements?” he said. “The metric I gave was that clients representing almost 50% of our revenue today are on some form of a NeoIP engagement. That does not mean 50% of revenues are on that engagement alone.”

The CEO, however, emphasised that the company cannot continue to deliver without an AI-led approach. Otherwise, clients, he added, will either figure out how to do it with the same vendor, with another provider, or on their own.

“That’s why the right approach should be whether I’m able to infuse this in every engagement, every customer,” he said.
Giving an AI revenue breakdown, he argued, risks confusion, where strong growth in a reported AI bucket alongside slower overall growth could be misread as revenue deflation.

Partners And Investors

Rakesh said that the NeoIP platform has been built largely through internal development and ecosystem partnerships rather than large acquisitions, with hyperscalers and model providers acting as technology enablers.

He also addressed recent stake sales by Blackstone, which sold around a 9.5% stake in Mphasis through a ₹4,600-plus crore block deal during the quarter. While Blackstone is no longer a majority shareholder, Rakesh said the focus remains on execution and customer relevance rather than changes in the shareholding structure.
“This is not the beginning of the end,” he said. “This is the end of the beginning.”

Looking ahead, Rakesh said Mphasis is entering a new phase, with investments made over the past several years beginning to show tangible opportunity. “Talk is cheap,” he said. “Executing this is really hard.”

Mphasis reported a 2.6% quarter-on-quarter and 12.4% year-on-year increase in revenue in the third quarter of FY26 to ₹4,002.6 crore.
Net profit after the exceptional item related to the labour law change declined 5.7% quarter-on-quarter to ₹442.2 crore.
Its shares declined 2.32% on Friday, ending the day at Rs 2,745 apiece.

The post Why Mphasis CEO Believes AI Can No Longer Be ‘Lipstick’ on Legacy IT appeared first on Analytics India Magazine.