Dive Brief:
- There are sizable opportunities for the channel as worldwide end-user spending on AI models and platforms booms, according to Gartner. In 2026, total model and platform spending is projected to reach $64 billion, up from $39 billion in 2025, per a report published by the analyst firm on Monday.
- The surge in China-based open-source AI models, such as Moonshot AI’s Kimi K2.5, will further strengthen demand for AI platforms across enterprises, said Gartner Senior Principal Arunasree Cheparthi.
- “Partners have a pivotal role to play in the AI and platforms landscape,” she said. “Those who position themselves as the economic control plane, deciding which AI capabilities to deploy, monitoring performance, ensuring policies and optimizing costs are set to capture the most long-term value.”
Dive Insight:
Gartner expects spending on GenAI models to grow 117%, while AI platform spending rises 36.9% in 2026. The uptick in tech expenditure gives partners the chance to specialize and profit through verticalized or domain-specific solutions, according to Cheparthi.
“We’re seeing immediate revenue gains for partners who tailor their AI offerings to specific industries, whether it’s healthcare, defense, manufacturing, or telecom,” she said. “The partner ecosystem is evolving through multi-layered channel strategies. Successful partners are adopting their models to fit different layers of the AI tech stack.”
Cheparthi cites Databricks' integration with SAP and Deutsche Telekom's partnership with Google Cloud as examples of how targeted, industry-specific solutions can drive rapid growth in the AI platforms market.
While AI adoption is in full swing across enterprises, AI budgets are coming under greater scrutiny as companies demand measurable outcomes and token costs rise.
Cheparthi said that this budget squeeze offers unique opportunities for the channel.
“Partners can specialize in preparing, cleansing and labeling data to help organizations unlock the full potential of their AI investments,” she said. “Also, as regulations around AI tighten, responsible AI and compliance are coming to the forefront. Partners who guide organizations through ethical practices and regulatory requirements are increasingly sought after.”
As partners navigate growth in AI platform spending, China’s latest open-source models are adding fuel to the fire.
“Open-source models at this scale lower the cost of entry for enterprises and developers,” Cheparthi said. “They can leverage cutting-edge capabilities without paying for expensive proprietary licenses, and that will increase spending on platform and integration services as organizations invest more in customizing, fine-tuning and operationalizing open-source models for their specific needs.”
The availability of these advanced models will drive increased adoption of AI platforms, potentially leading to a rise in spending on platform infrastructure, orchestration tools and managed services that help enterprises deploy, monitor and govern these models at scale, Cheparthi added.
