India’s enterprise technology sector is undergoing a significant transformation, driven by two key trends: the rapid expansion of AI infrastructure and a heightened focus on AI governance and security. This week, SEMICON India brought attention to the country’s semiconductor ambitions, while enterprises grappled with the evolving challenges of AI integration and data protection.
SEMICON India Highlights Semiconductor and AI Infrastructure Growth
At SEMICON India 2026, India’s semiconductor aspirations took center stage. Applied Materials announced a $5 billion investment over the next decade, while the government revealed $11–12 billion in investment proposals under Semicon 2.0. The event also showed the need for robust infrastructure to support the AI economy. Nabfid, a state-run financier, has sanctioned loans exceeding ₹3,000 crore each to at least four data centers. These developments signal a full build-out of chips, manufacturing capacity, and compute infrastructure essential for scaling AI workloads.
The focus on semiconductors extends beyond manufacturing. Tata Electronics announced 16 partnerships at SEMICON India, covering areas like wafer fabrication, advanced packaging, and talent development. Collaborations with Nexperia, Besi, and Fujifilm highlight the growing depth of India’s semiconductor ecosystem. For enterprises, this expansion is key for building a localized and resilient electronics supply chain.
AI Agents Redefine Enterprise Security
As AI agents transition from content generation to executing actions across systems, they are reshaping the enterprise security perimeter. Cisco India’s security leader, Ninad Katkar, emphasized the need for greater visibility into machine identities, permissions, and agent activity. The challenge lies not only in protecting infrastructure but also in governing what autonomous systems can access and execute. This shift is prompting CIOs to prioritize identity management, least-privilege access, monitoring, and resilience, especially in distributed technology environments.
The integration of AI into workflows necessitates security controls designed from the outset. As companies move beyond generative AI experiments to agents interacting with data and applications, ensuring data protection and governance becomes vital.
Palantir, Nvidia, and Booz Allen Hamilton are reevaluating their use of advanced AI models due to concerns about proprietary data and intellectual property. Palantir has sought a zero-data-retention commitment from Anthropic, while Nvidia is restricting Anthropic models to less-sensitive tasks. These moves highlight a growing emphasis on data handling, security controls, and contractual assurances in AI procurement decisions.
The appeal of isolated or privately controlled AI environments is rising, particularly for organizations handling sensitive information. This shift shows the need for enterprises to balance AI capabilities with robust data protection measures.
Cybersecurity Shifts Focus to Resilience
Deloitte India suggests a strategic shift in cybersecurity for critical infrastructure. The focus is moving from breach prevention to ensuring operational continuity and rapid recovery post-attack.
This shift is driven by the expanding threat environment, with AI, cloud services, and digital payments becoming integral to essential services like healthcare and power. Deloitte recommends stronger controls around AI tools, software testing, access management, and trusted backups.
The emphasis is on designing technology, business continuity, and third-party dependencies together to ensure resilience. For CIOs, the question is no longer if a system can be breached, but if critical operations can continue when part of the system fails.
IT Services Model Under Pressure from AI
A Boston Consulting Group (BCG) report highlights the pressure AI is putting on the traditional headcount-led model of IT services. The cost of AI inference has dropped significantly, and numerous frontier models have been released since 2023.
Buyers are now seeking measurable business outcomes, integration with existing technology, data sovereignty, and accountability. This shift is pushing technology providers towards outcome-based models, emphasizing domain expertise and integration capabilities.
Indian IT services companies are adapting to this new reality, with firms like HCLTech launching dedicated units for mid-market enterprises, focusing on AI-led transformation and cloud services.
Axis Bank’s partnership with Cognizant for application management services under a five-year deal is another example of this shift. The bank aims to standardize IT operations, expand automation, and strengthen governance, reflecting a broader trend in the banking sector towards managing large application estates through standardized processes and automation.
HCLTech’s new business unit, HCLTech Pulse, targets mid-market enterprises with a focus on AI, cloud, and cybersecurity, highlighting the growing competition in this segment as more companies move towards scaled AI deployment.
Salesforce’s Agentforce Expansion and AI’s Impact on IT Services
Salesforce is broadening its Agentforce platform with AI agents tailored for specific business tasks across sales, service, and operations. These agents integrate with Customer 360, enabling them to utilize existing customer data and processes. The technology allows agents to pursue long-term goals, acquire new skills, and collaborate, emphasizing preconfigured solutions for enterprises to avoid starting deployments from scratch.
A BCG analysis shows that technology buyers now prioritize measurable outcomes, integration, and accountability over generic AI features. This trend raises the significance of outcome-based models and domain expertise as Indian IT firms adapt to AI-driven delivery, aligning with the evolving demands of the market.
