Agentic AI Adoption Hindered by Commercial Licensing Models

What happened

Dow, the prominent materials science company, has expressed a strong interest in integrating agentic AI systems into its operations to enhance efficiency and innovation. However, the company faces a significant hurdle in adopting these advanced AI solutions due to the current licensing model employed by Workday, specifically its "Flex Credits" system. This model, which charges based on the consumption of AI services, is perceived by Dow as a barrier to widespread deployment and experimentation with agentic AI, which often involves iterative and exploratory use. The core issue stems from the unpredictable nature of agentic AI's resource consumption. Unlike traditional software, where usage can be more easily quantified, agentic systems might run numerous simulations or analyses, making the "pay-per-use" Flex Credits model economically prohibitive for large-scale adoption. Dow is advocating for a licensing structure that better accommodates the exploratory and potentially high-volume demands of agentic AI, suggesting that the current approach stifles innovation rather than enabling it.

Why it matters

This situation highlights a critical emerging challenge in AI governance and business strategy: the misalignment between innovative AI capabilities and existing commercial models. For business leaders, it underscores the necessity of scrutinising vendor licensing agreements for AI tools, particularly as companies move towards more autonomous and agentic systems. If pricing structures penalise experimentation and broad deployment, the transformative potential of AI could be significantly hampered, leading to slower adoption and a competitive disadvantage for organisations constrained by such models. From an ethical and governance perspective, the incident raises questions about equitable access to advanced AI. Restrictive or unpredictable pricing models could inadvertently create a two-tiered system where only the largest or most risk-tolerant enterprises can afford to fully explore agentic AI, potentially exacerbating existing digital divides. Responsible AI implementation requires not only technical safeguards but also commercial frameworks that foster widespread, beneficial use without creating undue financial burdens or stifling innovation.

The Institute take

This scenario at Dow is a clear illustration of how commercial friction, rather than technical limitation, can impede AI adoption and innovation. Many business leaders are focused on the technicalities of AI implementation, but often overlook the underlying commercial models that can make or break a strategic initiative.

The challenge Dow faces with Workday's Flex Credits exposes a fundamental tension: software vendors often monetise AI based on consumption, while enterprises need the freedom to experiment and scale without unpredictable costs. Responsible AI leaders must proactively engage with vendors to advocate for licensing models that support iterative development and broad deployment, rather than penalising exploration. Failing to address these commercial barriers will inevitably slow the pace of beneficial AI integration, regardless of the technology's promise.