New research from Cognizant reveals that companies are increasingly favouring ‘AI-builder’ IT firms that provide custom, full-stack AI solutions to unlock real enterprise value and drive successful AI adoption.
Key Points
- Companies adopting AI prefer IT services firms that offer custom, full-stack AI solutions designed to deliver enterprise value.
- Organisations prioritise custom AI solutions and flexible engagement models when selecting an AI partner, valuing them more than pricing and time to value.
- Generic, off-the-shelf AI solutions are a major reason for rejecting AI providers, highlighting the need for industry-specific expertise.
- Key challenges in enterprise AI adoption include regulatory compliance, demonstrating ROI, and a lack of clear AI strategy.
- AI investment is viewed as a long-term commitment, focused on augmenting human workforces and redesigning workflows for human-AI collaboration.
Companies keen on AI adoption prefer IT services players that are ‘AI-builder’ firms offering a new services model defined by designing and building custom, full-stack solutions to deliver enterprise value from Artificial Intelligence, Nasdaq-listed Cognizant said citing its new research on Wednesday.
Based on a study of 600 AI decision makers and interviews with 38 senior executives, the research found that organisations rank custom solutions and flexible engagement models as “the most important factor” when selecting an AI partner, ahead of pricing and time to value, according to Cognizant.
“Cognizant released new research showing that companies pursuing AI adoption overwhelmingly prefer IT services firms – such as ‘AI Builder’ firms, a new services model defined by designing and building custom, full stack AI solutions – to deliver real enterprise value from AI,” Cognizant said in a release.
Challenges in AI Adoption
Enterprises cite generic, off-the-shelf AI solutions as a prime reason to reject an AI provider, along with lack of industry-specific expertise, inability to integrate into existing technology stacks, and inadequate support and maintenance.
As per the research, the top three challenges organisations face in enterprise AI adoption are regulatory and compliance concerns, difficulty demonstrating return on investment and lack of clear AI strategy and vision.
The Role of ‘AI Builders’
Ravi Kumar S, CEO of Cognizant noted that AI success is not about deploying isolated models, but about engineering intelligence into the enterprise with purpose-built solutions.
“The most trusted path to an AI future is working with an AI Builder – one that brings deep industry context, systems engineering expertise, and operational accountability. At Cognizant, we focus on building the bridge from AI experimentation to measurable enterprise value,” Kumar said.
Enterprises face a “messy middle” in scaling AI, and in this context AI builders can create the bridge to enterprise value solving complex, real-world problems, it claimed.
Further, it observed that AI investment is long-term, not experimental. Enterprises are committing sustained capital to AI, signaling long-term infrastructure building rather than speculative investment.
AI, it said, is augmenting human workforces, not replacing them. Enterprise leaders are not forecasting workforce collapse, they’re forecasting redesign of workflows for human-AI collaboration, as per Cognizant.
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