New zeb research suggests enterprise AI adoption is advancing faster than many organizations’ ability to integrate the technology into existing systems and workflows, creating a growing opportunity for channel partners with integration and orchestration expertise.
The enterprise transformation firm found that 52.1% of respondents have integrated AI across multiple business functions, while another 18% said AI is already core to their operating model. More than half (55.8%) reported measurable results from their AI investments.
But integration complexity remains the biggest barrier to adopting more advanced AI, cited by more than 40% of respondents. For MSPs, systems integrators and other technology partners, that gap between adoption and operational maturity could translate into demand for services around data architecture, workflow integration and measurable business outcomes.
Integration emerges as the top enterprise AI barrier
The biggest obstacle identified by respondents was neither access to AI models nor access to skilled workers.
More than 40% cited integration complexity as the largest barrier to achieving more advanced AI capabilities, compared with 24.2% citing trust in vendors and just 4.3% citing a lack of talent.
Integration and execution also narrowly outranked model or technology capability as the most commonly reported cause of AI projects underdelivering.
That finding puts systems integration, data architecture and workflow orchestration squarely in the channel’s path as enterprises move AI deeper into existing technology environments.
AI buyers push partners toward outcome-based services
zeb’s research also points to a potential change in how customers want those services delivered and priced.
Nearly three-quarters of respondents said a contractual outcomes guarantee would either strongly differentiate a provider or cause them to switch partners. Outcome-based pricing backed by a guarantee was the most popular delivery model, selected by 44.1%, ahead of fixed-price projects at 26.1% and time-and-materials engagements at 13.3%.
That preference follows a broader shift already emerging around AI economics. Channel Insider recently reported that vendors and partners are experimenting with consumption-, action- and outcome-based models as customers increasingly question traditional per-seat software pricing and time-and-materials consulting engagements.
For partners, however, taking responsibility for outcomes also means assuming more risk when projects run over schedule or fail to deliver the agreed result.
Vendor neutrality becomes a differentiator for AI providers
The research suggests customers are also scrutinizing the incentives behind AI recommendations.
According to zeb, 87% of respondents said it was important or critical for an AI services provider to remain vendor-neutral, without a commercial stake in the selected model or platform.
“Vendor neutrality is an engineering requirement,” said Sid Vivek, chief technology officer of zeb. “ When an integration partner is incentivized to push a specific cloud or model, you end up with square-peg architecture forced into round-hole enterprise systems. Integration is hard enough without your systems integrator complicating it. Staying agnostic lets our engineering team at zeb pick whatever combination of tech is actually best for the problem.”
For channel partners building AI practices, the findings point toward a services market increasingly defined less by access to any single AI platform and more by the ability to connect multiple technologies, eliminate manual workarounds and demonstrate measurable customer outcomes.