Freshworks has released The Global Cost of Complexity Report: The Mid-Market AI Complexity Trap, a survey of 12,021 IT professionals, including more than 9,000 in mid-market organisations.
The research puts a dollar figure on how complexity is consuming mid-market AI budgets before real business outcomes are delivered, finding an average 25% of mid-market AI spend is lost to complexity overhead. In Singapore, this figure stands at 23%.
With tighter margins than larger enterprises, mid-market companies feel this “complexity tax” harder and faster. Singapore mid-market IT leaders are no exception, with nearly 92% planning to increase AI investment over the next 12 to 24 months, yet only 20% have AI integrated across core business operations and 28% remain stuck in pilots.
” As Singapore pushes for AI adoption through its national AI strategy mandate, Singapore 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 Simon Ma, Managing Director, APJ.
The ROI reality gap: IT is being judged on timelines shorter than deployment
Mid-market AI programs are stalling in the gap between executive expectation and deployment reality. While 73% of mid-market executives in Singapore expect AI investments to show ROI within 8 months, 48% of organisations say deployment alone takes between 6 and 12 months before meaningful ROI can even begin.
The barriers are structural. System integration complexity (27%) and excessive configuration requirements (25%) are the top reasons pilots fail to become full programs in the country. With deployment timelines running longer than the windows executives are watching, programs 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 (85%) of mid-market IT leaders in Singapore say managing AI complexity has actually increased their team’s workload, and 73% report that AI outputs are introducing noise, errors, or rework, a phenomenon the report terms “AI slop.” As AI adoption accelerates across Singapore businesses, AI is generating work faster than it is eliminating it, and IT teams are absorbing the differences.
Sprawl is compounding the problem. Global mid-market organisations use an average of 4.2 AI tools, with 9% running seven or more, yet only 42% of those surveyed in Singapore have a formal, consistently applied AI governance framework. This highlights a growing need for stronger AI governance in Singapore as adoption scales.
The Execution Pivot: mid-market IT leaders are buying differently
Mid-market organisations in Singapore 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 as businesses across the country accelerate AI adoption to drive productivity and innovation.
“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. 36% of mid-market IT leaders name workflow integration as their top priority for the next two to three years, 93% favour built-in workflows over heavy configuration, and 58% are buying AI capabilities rather than building in-house, aligning with Singapore’s focus on practical and scalable AI deployment.
