An AI-native attack on the outsourcing machine
Hang Ten Systems is an AI-native enterprise services startup founded by former Infosys CEO Vishal Sikka to use artificial intelligence as the primary engine for building, changing, and running large-company software, replacing the labor-heavy outsourcing model that has dominated IT services for decades.
The headline is blunt: Sikka has launched Hang Ten Systems, an AI-native enterprise services firm that has raised a USD 32 million (approx. RM149 million) seed round led by Mayfield, with a strategic investment from Aramco Ventures and participation from angel investors. This is not another slideware consultancy. Hang Ten already works with customers such as Siemens Gamesa Renewable Energy and Fresenius on AI-native project delivery, where software is built and maintained by AI agents supported by a compact expert team rather than by vast offshore benches.
Sikka is attacking the very labor model that once paid his salary. He led Infosys when it gave a grant to help OpenAI get off the ground, and now he is building a business that treats AI not as a side tool but as the core production line for enterprise automation.
Why Hang Ten’s model is different from legacy IT services
Hang Ten’s bet is that AI can now perform much of the software customisation, integration, and maintenance work that IT services firms have charged enterprises billions to deliver. Instead of scaling by adding more engineers, the company focuses on what it calls agentic code generation, reusable AI skills, and a bench of forward-deployed experts for areas like finance, HR, and product development.
That matters because the traditional industry—roughly a USD 250 billion-plus software services market—is built on labor arbitrage: armies of engineers, layers of project managers, and long implementation cycles. Hang Ten’s model aims to scale through accumulated project leverage rather than headcount growth, turning each deployment into reusable automation rather than another invoice line of human effort.
In plain terms, Hang Ten is pointed straight at the labor model that made Sikka’s old industry rich. The target is the exact software work global enterprises have long handed to firms like Infosys, Tata Consultancy Services, and Wipro, only now reimagined as AI-native IT services where automation, not body count, defines capacity.
Timing, tension, and a $250B industry under AI pressure
Hang Ten’s launch lands in a services sector already nervous about automation. Indian IT services stocks have been under pressure as investors ask how much revenue is exposed to AI tools that automate coding, testing, documentation, and support work. One analysis warned that a severe AI disruption case could drive another 30% to 65% valuation derating for major IT names.
At the same time, industry leaders are publicly arguing that AI will amplify rather than replace traditional firms, pointing to a USD 300–400 billion AI-first services opportunity by 2030. Nasscom expects the broader technology industry to reach about USD 315 billion in FY26, while coverage this year has described the software services industry as a roughly USD 250 billion-plus market already under AI pressure.
Sikka has been vocal about both the risks and the gap between human cognition and today’s AI, and has argued that new foundation models should not be left to a few global players. Hang Ten is his answer: a Hang Ten Systems startup that treats that pressure not as a threat to be managed, but as a wave to surf for advantage.
Can AI-first services win against incumbents?
The question is not whether Hang Ten can raise money or write an impressive launch post; it already has USD 32 million (approx. RM149 million) in the bank, paying customers, and Jerry Yang on its board. The real test is whether its AI-native architecture can dislodge legacy consulting and outsourcing firms that live on long-term contracts and deep client entrenchment.
According to one investor, Hang Ten’s model "scales through accumulated project leverage rather than headcount growth," which is a polite way of saying the old assumption that enterprise software needs endless human labor is now vulnerable. But winning in this space means handling the hard questions: who owns the risk when AI-written code breaks a finance workflow, how procurement compares a young startup to a long-term partner, and how incumbents respond when they bundle similar promises into existing master services agreements.
Hang Ten enters a market under intense scrutiny, with analysts debating whether AI will disrupt traditional IT services or expand them, even as some major firms’ shares have fallen over 35% amid a reassessment of long-term economics. Whether Hang Ten can deliver at the scale its early clients represent is the real test.
Conclusion: Automation over headcount is now a strategic choice
Hang Ten Systems is more than another AI enterprise services pitch; it is a public rejection of the idea that value in IT services equals the number of engineers on a project. Sikka is betting that, in a USD 250 billion-plus industry under AI pressure, the winners will be those who treat automation as the default and human effort as the exception.
For incumbents, the choice is stark: either adopt an AI-native IT services mindset internally or compete with firms born on that model. For enterprises, the emergence of Hang Ten is a signal to rethink procurement around outcomes and automation instead of hourly rates and headcount. The wave Sikka describes is real; the only remaining question is which players will manage to hang ten and which will be pulled under by their own legacy structures.
