Freshworks has released The Global Cost of Complexity Report: The Mid-Market AI Complexity Trap, featuring a detailed examination of how AI complexity is affecting mid-market companies in India. The research, based on responses from over 9,000 mid-market IT decision-makers across six countries, finds that in India, 27% of the average mid-market AI budget is lost to complexity overhead, contributing to an estimated ₹33,000 crore in wasted AI spend every year.
Despite this “complexity tax,” Indian mid-market companies remain bullish on AI. Ninety-four per cent report a growth outlook for the next 12 months, and 94% plan to increase AI investment over the next 12–24 months. At the same time, IT leaders are under intense pressure to deliver: 74% of Indian executives expect AI investments to show ROI within eight months, yet 51% say AI deployments alone take 6–12 months just to go live, creating a sharp gap between expectations and execution timelines.
“Mid-market IT leaders don’t have time for AI that takes months to deliver value. They need AI that works inside the business they already run and shows value fast,” said Srinivasan Raghavan, chief product officer at Freshworks. “The companies that move from purchase to performance fastest will turn AI from a complexity tax into a competitive advantage.”
The ROI Reality Gap: IT is Being Judged on Timelines Shorter Than Deployment
Mid‑market AI programmes are stalling in the gap between executive expectation and deployment reality. Globally, 72% of mid-market executives expect AI investments to show ROI within eight months, and in India that figure is 74%. At the same time, 55% of organisations say deployment alone takes between 6 and 12 months before meaningful ROI can even begin, with just over half (51%) of Indian organisations reporting similar deployment timelines.
The barriers are structural. System integration complexity (27%), skilled talent shortages (26%), and excessive configuration requirements (26%) are the top reasons pilots fail to become full programmes worldwide. Indian mid‑market organisations report the same pattern, with system integration complexity (34%), skilled talent shortages (30%), and excessive configuration requirements (31%) all cited as leading barriers. With deployment timelines running longer than the windows executives are watching, programmes risk being cut before they can deliver value.
The Productivity Paradox: AI Was Supposed to Create Headroom, But For Most Mid‑Market Teams, It Has Done the Opposite
Managing AI is now adding to the workload it was meant to reduce, with teams fixing flawed outputs and governing tool sprawl across a growing stack of AI products.
More than 8 in 10 (86%) of mid‑market IT leaders globally say managing AI complexity has increased their team’s workload; in India, this rises to 88%. Overall, 80% report that AI outputs are introducing noise, errors, or rework—a phenomenon the report terms “AI slop”—and that share climbs to 85% among Indian respondents. AI is generating work faster than it is eliminating it, and IT teams are absorbing the difference.
Sprawl is compounding the problem. Mid‑market organisations use an average of 4.2 AI tools globally, with 10% running seven or more. Indian mid‑market organisations are managing an even broader stack, using an average of 4.6 AI tools, with 16% running seven or more, even as teams spend over a quarter (27%) of their AI‑related time on complexity rather than value delivery. Yet only 33% of mid‑market organisations worldwide have a formal, consistently applied AI governance framework, compared with 50% in India.
Separate Freshworks research found 71% of US mid‑market IT leaders say unapproved “shadow AI” use is common inside their organisation.
The Execution Pivot: Mid‑Market IT Leaders Are Buying Differently
Mid-market organizations are responding to the AI complexity trap by changing how they buy. The new priority is AI that delivers value early, plugs into existing systems, and does not require a major build-out to work.
“Middle-market businesses tend not to be early innovators and often lag in realizing full-scale implementation benefits until they are confident of ROI. Until then, smaller pilots and tests are often used to prove feasibility,” said Doug Farren, executive director, National Center for the Middle Market.
Mid‑market buying behaviour is shifting decisively toward AI that works out of the box. Globally, a third (34%) of mid‑market IT leaders name workflow integration as their top priority for the next two to three years, and 90% favour built‑in workflows over heavy configuration. In India, 44% name integrating AI into current workflows as their top priority, and 93% favour AI solutions with built‑in workflows over heavy configuration. More than half (54%) of mid‑market organisations globally are buying AI capabilities rather than building in-house, while in India the market is evenly split: 42% are buying and 42% are building in-house, reflecting both strong vendor appetite and in-house innovation.
