Guinea Pigs of Innovation: Why Partners Piloting Agentic AI Internally First Pays Off – Executive Summary

Where are channel partners and their customers on their agentic AI adoption journeys?

• The global partner opportunity for AI services is forecast to reach $267 billion by 2030.
• 49% of partners are at least actively piloting or testing agentic AI, compared with 42% of their customers.
• Data security or compliance concerns (47%), and a lack of internal expertise or training (36%) are partners’ biggest agentic AI adoption inhibitors.
• Use case examples and ROI models (53%), and technical integrations and APIs (48%) are the top resources partners need to increase internal agentic AI adoption.

Introduction: Agentic AI’s internal and external effect

Agentic AI is transforming the global technology landscape, with channel partners playing a pivotal role in its adoption. The global partner opportunity for AI services is projected to reach $267 billion by 2030, with agentic AI delivering autonomous, continuously learning agents embedded across the business stack. A recent survey by Channel Futures and Omdia highlights the importance of channel partners adopting agentic AI internally to build expertise, refine use cases, and better serve their customers. The internal-first approach positions partners as credible advisors, enabling them to address customer challenges effectively and drive successful deployments.

Internal adoption trends and benefits

The survey reveals that 49% of partners are actively piloting or testing agentic AI internally, while another 44% are in the “considering or evaluating” phase. Larger partners, generating over $10 million in annual revenue, are leading the charge, with 65% or more piloting agentic AI internally, compared with 51% or fewer of smaller firms, making less than $10 million annually. This disparity underscores the advantages of greater financial resources, established expertise, and stronger vendor relationships enjoyed by larger firms.

This internal-first strategy not only enhances partners’ credibility but also equips them to guide customers through similar adoption journeys, ensuring successful implementations.

Challenges in internal adoption

Despite the enthusiasm for agentic AI, partners face several barriers to internal adoption:

• Data security or compliance concerns (47%): The autonomous nature of agentic AI raises questions about governance and regulatory compliance.
• Lack of internal expertise or training (36%): Many partners lack the skills needed to implement and manage agentic AI solutions effectively.
• Unclear ROI or business value (35%): Difficulty in quantifying benefits makes it challenging to justify investments.
• Budget constraints (35%): Smaller firms, in particular, struggle with financial limitations.

To overcome these challenges, partners have identified key resources they need from vendors, including use case examples and ROI models (53%), technical integrations and APIs (48%), and hands-on training or certifications (44%).

Customer adoption trends

Customer adoption of agentic AI mirrors the internal trends observed among partners. While 50% of partners report that their customers are in the “considering or evaluating” phase, only 42% are actively piloting or testing solutions. Larger partners report higher customer adoption rates, with 57% or more of their customers piloting agentic AI, compared with 45% or fewer for smaller partners.

Customers face similar challenges, including governance and compliance concerns (51%), data and security management (14%), value realization and adoption (14%), and technical expertise gaps (13%). Partners that have successfully adopted agentic AI internally are better positioned to help customers navigate these obstacles, leveraging their expertise to ensure smooth deployments.

Conclusion

Channel partners adopting agentic AI internally are better equipped to understand its capabilities, refine use cases, and deliver value to their customers. By addressing adoption challenges and leveraging vendor support, partners can unlock the transformative potential of agentic AI, driving growth and innovation in the global technology ecosystem.