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India's AI Adoption Shows Scaling AI is Hard, Even with Billions Invested

Investment in artificial intelligence surged, with capital flowing into chip development, data centers, and the creation of new AI models. Despite this influx of resources and the continuous release of new models, widespread AI adoption faced significant hurdles across various sectors.

While technological capabilities advanced rapidly, organizations struggled to integrate AI into their existing workflows. The challenge shifted from technological limitations to the preparedness of institutions and organizations to absorb AI effectively. Institutions, defined as the rules, incentives, standards, and accountability structures, play a crucial role in reducing uncertainty and fostering trust in new technologies. Organizations, operating within these institutional frameworks, must adapt their workflows to accommodate AI.

The historical example of the chemical industry's diffusion illustrates this point. Germany initially pioneered the industry, but the United States achieved widespread adoption by integrating chemistry into manufacturing and everyday commerce. Productivity gains only materialized after institutions evolved and organizations redesigned their workflows. Similarly, the United States established the disciplines of business administration and management science, which facilitated the adoption of new technologies, including AI.

The current situation in India, where approximately 20 billion transactions are processed monthly, highlights the complexities of scaling AI adoption. Despite the potential benefits, organizations face challenges in adapting their processes and ensuring that AI systems are effectively integrated. The constraint is no longer technological capability. It is whether institutions and organizations are prepared to absorb AI.

Looking ahead, the successful integration of AI will depend on the ability of institutions to create supportive frameworks and organizations to adapt their workflows. This will require a concerted effort to address the challenges of AI adoption and unlock the full potential of this transformative technology.

Multi-Source Journalism

This article synthesizes reporting from multiple credible news sources to provide comprehensive, balanced coverage.

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