Despite rapid AI integration, Indian enterprises lose 27% of budgets to complexity as rising workloads, tool sprawl, and ROI pressures challenge scale
India’s mid-market enterprises are emerging as global leaders in AI adoption, but this rapid progress comes at a significant cost. According to Freshworks’ latest Cost of Complexity Report 2026, Indian companies are losing a substantial portion of their AI investments to operational inefficiencies, integration challenges, and growing system complexity.
The report reveals that 27% of the average mid-market AI budget in India is lost to what it terms “complexity overhead.” This translates into an estimated ₹33,000 crore in wasted AI spend annually highlighting a critical gap between investment and realized value. While the global average complexity cost stands at 25%, India’s higher figure reflects the unique pressures faced by organizations scaling AI quickly across diverse and often fragmented technology environments.
Despite these challenges, India continues to lead in AI adoption among mid-market companies. Around 36% of Indian organizations have already embedded AI across multiple core business functions more than double the global average of 15%. This demonstrates a strong appetite for innovation and digital transformation, with companies leveraging AI to enhance customer experience, operations, and decision-making.
“Mid-market IT leaders don’t have time for AI that takes months to deliver value they need solutions that work within existing systems and show impact quickly.”
— Srinivasan Raghavan, Chief Product Officer, Freshworks
However, this ambition has created a growing operational burden on IT teams. The report notes that 88% of Indian mid-market IT leaders say managing AI complexity has increased their team’s workload. Rather than reducing effort, AI is, in many cases, adding to it—through tasks such as managing multiple tools, fixing flawed outputs, and ensuring governance across systems.
This challenge is further compounded by what the report calls the “ROI reality gap.” While 74% of Indian executives expect AI investments to deliver returns within eight months, the reality is that deployment itself often takes between six and twelve months. As a result, AI programs risk being evaluated or even discontinued before they have had sufficient time to generate measurable outcomes.
Several structural barriers are contributing to this gap. System integration complexity is cited by 34% of Indian respondents as a key obstacle, followed by talent shortages (30%) and excessive configuration requirements (31%). These issues slow down deployment timelines and make it difficult for organizations to move from pilot projects to large-scale implementations.
Adding to the problem is the growing sprawl of AI tools. Indian mid-market organizations use an average of 4.6 AI tools, with 16% using seven or more. Managing this expanding ecosystem not only increases complexity but also diverts time away from value creation. In fact, companies are spending more than a quarter (27%) of their AI-related time dealing with complexity rather than driving outcomes.
The report also highlights the phenomenon of “AI slop” where 85% of Indian IT leaders report that AI-generated outputs introduce noise, errors, or rework. This forces teams to spend additional time validating and correcting results, offsetting the intended productivity gains of AI adoption.
In response, mid-market companies are beginning to shift their approach. Rather than investing in heavily customized or complex AI solutions, organizations are increasingly prioritizing tools that integrate seamlessly into existing workflows and deliver faster time-to-value. In India, 44% of IT leaders now rank workflow integration as their top priority, while 93% prefer AI solutions with built-in workflows over those requiring extensive configuration.
Buying behavior is also evolving. While globally 54% of mid-market organizations prefer to buy AI capabilities rather than build them in-house, India presents a balanced picture, with 42% buying and 42% building internally. This reflects both a strong innovation culture and a growing ecosystem of AI vendors catering to enterprise needs.
Ultimately, the report underscores a critical insight: while India’s mid-market is ahead in AI adoption, success will depend on how effectively organizations manage complexity. The ability to move from experimentation to execution while controlling costs and reducing operational overhead will determine whether AI becomes a competitive advantage or a costly burden.
As enterprises continue to scale AI initiatives, simplifying implementation, improving integration, and focusing on faster outcomes will be key to unlocking the full value of AI investments in the years ahead.