Enterprises Embrace AI in a Cost-Conscious Era to Maximize Returns
NEW DELHI: The enterprise AI landscape is shifting towards a more disciplined approach as companies reassess their investments. After two years of rapid deployment and increased computing demands, businesses are now focused on whether their AI expenditures are yielding measurable returns. Uber has reported that its internal AI budgets were depleted faster than anticipated due to rising employee adoption, leading to stricter governance measures.
Meta has prioritized reducing inference costs, while major players like Amazon, Walmart, Cisco, and Uber have implemented usage caps or directed employees to more cost-effective AI models. This trend is also evident in India, where a recent EY-CII survey revealed that 47% of enterprises have multiple generative AI applications in production. However, over 95% of these companies maintain AI and machine learning budgets below 20% of their overall IT spending.
The push for accountability in AI investments is gaining traction. A study by SAP indicates that Indian organizations expect a 45% increase in AI investment over the next two years, with a shift in focus towards improving returns rather than merely increasing deployments. Sambhav Jain, managing director and partner at BCG India, noted that diminishing returns are becoming more apparent, as larger context windows and multiple AI agents often yield only marginal improvements in output quality without significant gains in productivity or customer experience.
Deepak Dhanak, co-founder and COO of Rocket, emphasized that the issue lies not in AI spending itself but in the lack of accountability in measuring outcomes. He stated, “The overspend is not an AI problem, it is a measurement problem.” Dhanak criticized the previous focus on token consumption as a vanity metric and stressed the need for businesses to align the right AI models with specific tasks and to measure actual outcomes.
Despite the acceleration in AI investments, with Microsoft, Amazon, Alphabet, and Meta projected to spend around $320 billion on AI infrastructure by 2025, many Indian startups are also adjusting their strategies. A Z47-OpenAI-Zinnov study found that nearly 90% of mature AI adopters have reduced some form of BPO spending, with over one-third cutting outsourced work by more than 25%. Furthermore, 86% of Indian startup founders plan to increase their AI budgets this year, yet only 9% have reported a measurable increase in sales or conversions linked to AI.
Executives are increasingly questioning whether cheaper AI models can deliver substantial value at a fraction of the cost. Milesh J, head of strategy and operations at SAP Labs India, remarked, “We’re not experimenting with AI anymore — we’re operationalising it. That shift changes the entire cost conversation.” He cautioned that the real risk lies not in overspending on tokens but in confusing expenditure with strategy, highlighting the need for rigorous measurement to determine which AI investments are truly effective.
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