Global infrastructure pledges dominated the India AI Impact Summit in New Delhi, where conglomerates and hyperscalers outlined multibillion-dollar investments to expand compute capacity across the country. Yet beneath the capital headlines, enterprise platform vendors clarified how they intend to operationalize AI inside business systems.
The summit’s emphasis on deployment readiness and industrial-scale execution signaled a shift from model experimentation to enterprise integration. Against that backdrop, SAP used the event to articulate a platform-centric view of AI—arguing that long-term value will emerge from intelligence embedded across enterprise workflows.
SAP Makes the Case for Platform AI
SAP CEO Christian Klein did not announce new investment figures at the summit. Instead, he issued a formal statement to India’s Ministry of Electronics and Information Technology outlining how the company views AI’s role in economic development.
Klein described AI as “not just a technological leap” but “a catalyst for inclusive growth and prosperity across communities worldwide.” He said combining trusted data with contextual AI can broaden access to innovation and create opportunities that transcend borders. He added that AI has “immense potential to boost growth, resilience, and competitiveness.”
Calling AI a “once in a generation opportunity” for India’s digital economy, Klein said its real impact will come “not from standalone models, but from platform thinking,” with intelligence embedded into digital foundations and scaled responsibly across ecosystems.
Adoption Momentum and Engineering Depth
Clas Neumann, SVP and Head of the Global SAP Labs Network, attended the summit and pointed to what he described as early enterprise momentum in the country.
“In many studies it shows that AI adoption in India is already higher than many Western countries,” he said, adding that while India faces both opportunity and challenges in AI, “the opportunities will prevail.”
Neumann framed AI as an economic multiplier. He said the technology creates “huge opportunities” across productivity, education, healthcare, and jobs, and that India “will benefit greatly in the long run.”
He also tied that outlook to SAP’s customer base. “SAP has thousands of customers now emerging on the AI roadmap,” he said, describing businesses becoming more sustainable, agile and efficient as AI capabilities move into core processes.
Neumann noted SAP has invested in India for more than three decades and operates its second-largest engineering hub in the country, outside its headquarters in Germany.
With more than 17,000 employees across multiple cities and a recently expanded Bengaluru campus, SAP’s engineering presence forms part of the foundation supporting its Business AI strategy in the region.
Industry Leadership and Policy Signaling
Sindhu Gangadharan, Managing Director of SAP Labs India and Chairperson of NASSCOM, played a visible role across multiple summit sessions. Speaking on panels focused on trustworthy AI, she emphasized that technology must be measured by its societal impact.
In a summit address called “AI for People, AI for Progress,” Gangadharan cited projections of a potential $264 billion productivity boost for India by 2030 and said more than 30% of Indian organizations are implementing AI, above the global average. She argued that AI will not replace people, but that those who use AI will outpace those who do not.
Gangadharan also hosted Germany’s Federal Digital Minister at SAP’s dedicated space inside the venue and participated in the Indo-German Tech Forum, linking SAP’s enterprise messaging with broader industry and bilateral discussions underway during the summit.
Application-Layer Positioning in an Infrastructure Cycle
SAP’s presence unfolded alongside significant capital announcements from infrastructure providers. Microsoft reiterated its $17.5 billion India cloud and AI investment, Amazon reaffirmed multibillion-dollar expansion plans, and Qualcomm announced a $150 million AI venture fund. Indian conglomerates outlined multi-gigawatt data center expansions.
Against that backdrop, SAP’s messaging operated at the enterprise application layer. As compute capacity expands, the company positioned Business AI inside existing enterprise systems, linking infrastructure scale to process-level execution.
The focus remained on embedding intelligence into business processes, rather than announcing new commitments. In doing so, SAP aligned its summit presence with its broader Business AI strategy, centering process integration, trusted data, and operational scale as infrastructure capacity across the country continues to expand.
What This Means for ERP Insiders
Platform thinking elevates enterprise platforms. This emphasis shifts value toward systems that control enterprise data, workflows, and governance. As models commoditize and compute capacity expands, advantage may accrue to platforms that orchestrate context across finance, supply chain, and human capital.
India’s scale is shaping enterprise AI. A large engineering base and thousands of customers advancing AI roadmaps create influence beyond individual deployments. As AI embeds into core workflows, repeated implementation patterns in high-adoption markets can solidify into de facto standards that shape processes, integrations, and controls.
AI advantage follows organizational readiness. If those who use AI outpace those who do not, competitive separation emerges. Enterprises that redesign workflows, incentives, and decision rights around AI will compound gains faster than teams running pilots.
A version of this article was originally published by SAPinsider on February 23, 2026.
