#aipolicy

If AI investments are rising, why is enterprise-wide execution still lagging? This blog uncovers the real gap between AI ambition and implementation, and what organizations must fix in their AI policy to move from pilots to impact.

Union Minister Jitin Prasada has described the India AI Summit as a Mahakumbh for artificial intelligence (AI). The scale of participation reflects a historic phase in India’s digital journey, he said. He addressed the session titled “From AI User to Creator” at the AI Impact Summit 2026. Calling upon innovators and entrepreneurs, the minister urged wider adoption of artificial AI. Developers must create solutions that strengthen technological self-reliance, he added. Global leadership in emerging technologies remains a key objective for India. According to Prasada, India has progressed from an AI user to a creator. This transition reflects sustained digital initiatives in recent years. Continued expansion of AI capabilities remains essential, he emphasised. Technology and trade now act as twin engines of economic expansion. Rapid technological change requires agile governance frameworks. Without adaptation, governments risk losing competitiveness in the global race. India currently stands as a global talent hub. However, this advantage requires continuous skill development. Emerging technologies demand ongoing innovation and workforce adaptation. India AI Summit:  AI's Expanding Role AI must move beyond theoretical discussions. It should function as a practical capacity-building tool for youth. Stakeholders must prioritise sector-specific AI deployment strategies. Regional implementation models also require focused attention. Discussions should not remain confined to large language models alone. Instead, policymakers should emphasise measurable, real-world applications. Countries of the Global South seek tangible AI-driven solutions. AI must improve ease of doing business. It should also enhance ease of living for citizens. Advanced technology should not remain concentrated in limited hands. Broader access will ensure inclusive digital transformation. Data serves as the fuel of the AI ecosystem, the minister noted. Steps are underway to ensure availability of quality datasets. Reliable data infrastructure will enable meaningful transformation. Organisers expect over 2.5 lakh visitors at the expo. International delegates will participate in large numbers. The summit aims to foster global partnerships and business opportunities. Industry participants view the event as a strategic innovation platform. India now stands at a critical inflection point in AI development. Artificial intelligence will shape the country’s economic trajectory. Stakeholders must act decisively and responsibly, Prasada said.

Choosing which LLM handles a request might seem like a technical detail, but at scale, routing decisions directly impact cost, performance, and risk. Different models have unique behaviors, data handling policies, and compliance requirements. If routing logic lives inside individual applications, governance becomes fragmented, making it impossible for enterprises to enforce consistent standards across AI usage. At AgentsFlow, we solve this problem by providing a centralized, policy-driven and auditable LLM routing solution. Our platform ensures enterprises can manage AI model selection, compliance, and performance optimization in a unified way—turning routing from an infrastructure concern into a strategic governance advantage.

Static AI policies may seem fine at first, but as AI adoption grows, they quickly break. New use cases emerge, more teams deploy AI agents and models and tools constantly evolve. Static policies either slow teams down or create new risks. At AgentsFlow, we solve this problem by creating adaptive AI guardrails that evolve with your usage, intent, and business context. Our solutions help enterprises maintain control, reduce risk, and scale AI safely.

Most AI guardrails work well in testing but often fail in production. Models change, prompts evolve, and usage shifts—what was safe yesterday can be risky today. Agents Flow provides policy-driven, adaptive guardrails to keep AI safe, compliant, and under control in real time.