Opportunity Watch: Industry research to supercharge your AI strategy

AI continues to grow with no end in sight. Organizations are moving from proof of concept to proving value and return. Innovation is within arm’s reach, with open source AI available in the cloud. While enterprises continue betting big on AI investments, being able to demonstrate a return — showcasing measurable outcomes — remains a challenge. There’s even a name for it: “Tokenomics,” (i.e., token economics). Most easily understood as FinOps applied to AI, “tokenomics is the discipline through which AI consumption is metered, attributed and connected to business outcomes,” where every unit of AI is broken down into input and output “tokens.”¹ It’s where AI investment connects to measurable outcomes. 

Channel partners have tremendous opportunity to offer AI practices and competencies to support end customers’ AI endeavors — helping them implement and scale AI, how to manage AI costs and measure the value of those investments. 

AI spending continues to accelerate
  

About two-thirds (65%) of all technology spending globally will be delivered through or with a channel partner in 2026, according to Omdia.² That represents a whopping $4.05 trillion of the $6.21 trillion global IT market.³  

Unsurprisingly, AI represents a big part of that, with spending continuing to accelerate globally. In fact, IDC projects worldwide AI spending from 2026 to 2029 to grow at a 4-year compound annual growth rate (CAGR) of 30.8%.⁴ And the value of the global AI economy is forecasted to reach $22.5 trillion by 2031.⁵  

End customers are actively seeking AI capabilities to help them continue trying to innovate, boost adoption across the enterprise and realize the efficiencies and benefits. While about half of channel partners globally report that they are currently selling AI solutions in some capacity, the opportunity cannot be ignored.⁶ Offering some level of capabilities, specialization or expertise is becoming an expectation.  

GenAI software spend is expected to grow at a CAGR of 32% from 2024 to 2030, according to Forrester.⁷ And IDC forecasts generative AI software services to grow at a compound annual growth rate of 68.9% worldwide from 2024 to 2029.⁸  

While growth in GenAI software services spending continues, organizations are shifting beyond the GenAI priorities of the last few years and into scaling agents to support the business. And Omdia cites agentic AI as the primary technology investment priority for enterprises worldwide in 2026.³ With a compound annual growth rate of 35.3%, the size of the AI services opportunity is forecasted to be $267 billion by 2030.³ Your customers need advisory, deployment, integration and management support to reach their AI goals.

AI readiness starts with data

Data is at the core of AI. Effective data integration, governance and access control is essential to ensuring AI at scale. Organizations may use enterprise data and layer in external sources to augment coverage. Knowledge of the source data is essential to good AI tokenomics because organizations cannot measure AI value without understanding the data feeding models and agents.  

Organizations around the globe are prioritizing data most closely aligned to day-to-day execution, revenue activity, and measurable business outcomes in order to strengthen their AI readiness.

Agentic moves from pilot to production 

As GenAI adoption has become commonplace, agentic is now the new AI goalpost with companies moving from pilot to production. Seventy-seven percent of organizations already have AI agents running in production.⁹ This is when tokenomics becomes even more important; agentic AI introduces fluctuating usage so monitoring consumption and controlling costs will be critical. 

Executing AI agents successfully will depend on governance, platform integration, organizational readiness, and measurable business outcomes.

Planned use of agents is not categorized under a single delivery model, and organizations will need security, governance and platforms to support multiple models. In a survey, IDC found that organizations worldwide intend to use agents almost equally across four areas:¹⁰  

• In-app agents that are embedded directly inside the apps we use (27%) 
• Custom-configured agents we built with low-code/no-code agentic AI platforms (25%) 
• Standalone third-party agents for a specific purpose but outside of a single app (24%) 
• Bespoke agents built and operated by internal developers or external contractors using agentic AI frameworks (24%) 

Standing out by offering AI services 

Notably, research and advisory firm TSIA defines three service categories for making AI profitable for your business.¹¹ These suggest services will not be replaced by AI; rather, services could be a competitive advantage that helps you differentiate your business and provide more value as a strategic advisor to your customers. 

1. AI readiness & governance services: End customers need support becoming AI ready and compliant as global AI standards will continue to evolve. Forrester predicts spending on AI governance software alone will more than quadruple between 2024 and 2030, exceeding $15.8 billion.⁷ You can be an advisor, helping them evaluate data quality, data integration, data governance and data risk.  
2. Value optimization services: AI is constantly changing and value optimization services offer a potential recurring revenue stream for you to support your customers through all the change. These services are focused on monitoring AI use case performance and helping identify new, worthwhile use cases to implement. Arrow shared some desirable AI use cases based on AI use case spending by industry vertical: Explore healthcare, financial services, education and government use cases. 
3. Outcome-oriented AI services: TSIA defines these as outcome-based offers that combine technology, advisory services, engineers and managed services to deliver on specific outcomes, such as reduced costs or revenue uplift in a specific business area.  

Grow your AI practice. The AI phenomenon continues to make major waves across industries. You have an opportunity to build on this momentum — from creating repeatable services and recurring revenue streams to helping demonstrate proven and measurable outcomes to enabling customers to scale their AI. But it’s impossible to be an expert on all of AI.  

As the leading AI and hybrid cloud aggregator, Arrow is here to help.