By Viswanath Ramaswamy
India is rapidly accelerating towards its goal of becoming a global leader in AI use and innovation, driven by efforts from the private sector and government initiatives like the IndiaAI mission.
A recent IBM ROI of AI study found that 87% of IT decision-makers (ITDM) at Indian businesses said that they have made significant progress with their AI initiatives last year, with 76% already seeing positive return on investments (ROI) from their AI projects.
However, the time for AI experimentation is over and it’s critical that we move beyond pilots to scaling AI that will span the enterprise enhancing productivity, efficiency and customer experience.
To do this, business leaders need to carefully assess the ROI of AI, which is not necessarily limited to monetary gains but covers other dimensions as well. Our study found aspects like faster software development, rapid innovation, and time saved through enhanced productivity ranked as the three most important metrics Indian ITDMs use to calculate ROI from AI investments. Having this nuanced understanding will allow business leaders to fine tune and strategically align their AI deployments that generate the most return.
The most impactful of these are the use of open-source ecosystems, using AI responsibly and the growing significance of AI agents and assistants.
Open source taking center stage
To accelerate ROI from AI investments, Indian organizations are increasingly turning to open-source solutions as a key IT strategy. In fact, we found 70% of ITDMs said that at least half of their AI solutions will be based on open source in 2025, compared to just 48% who said the same for 2024.
An open AI ecosystem recognizes the value of community-built technology and the open exchange of information, ideas, and skills it cultivates. This shift is natural, given these ecosystems provide the collaborative foundation, cost efficiency, and technological flexibility needed to unlock the full potential of AI, which is critical in India’s fast-evolving and competitive digital landscape.
Governance isn’t an afterthought but the foundation of AI adoption
Scaling AI within enterprises isn’t just about speed or efficiency, it’s also about trust, transparency, and responsibility – because AI that people trust is AI that people will use. More than half the businesses we surveyed said that lack of AI governance is a key challenge to overcome, emphasizing the need for a robust responsible AI framework integrating principles such as fairness, transparency, and accountability. By embedding responsible AI practices, businesses can confidently progress on their AI journey while engendering trust from their stakeholders and minimising risks.
Being the responsible AI agents in business
The future of work is being rewritten with AI agents and assistants. Unlike traditional AI models that require human guidance and operate within predetermined boundaries, agentic AI can adapt to dynamic situations and taking purposeful action.
This type of AI builds upon generative AI techniques, which involve creating content based on learned patterns, but takes it a step further by using these generated outputs to achieve specific objectives.
A study by the IBM Institute for Business Value found 9 in 10 executives expect their organization’s workflows to be digitized with intelligent automation and AI assistants by 2026. As organizations start to pair employees with domain-specific AI agents, workers need to completely rethink how they do their jobs. They will need to manage entire teams of autonomous task completing agents and learn to work with chat-based supervisory AI agents.
As with other forms of AI systems, agents can also hallucinate and confidently choose the wrong tool or take an impractical or unwise action. The effort needed to manage and governing agents would be tremendous and not possible to do in an ad hoc or manual way. Hence, even in this instance responsible AI practices with designing and deploying agentic workflows becomes critical.
The author is Vice President, Technology, IBM India & South Asia.
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