What's Happening?
RSM US LLP is highlighting the necessity for organizations to adopt new measurement processes to accurately capture the business value of artificial intelligence (AI), moving beyond traditional software metrics. According to RSM, while 99% of organizations measure ROI
for AI, they often focus on metrics like process efficiency (40%), productivity and time savings (38%), and decision quality or speed (36%). However, these metrics, as identified in the RSM Middle Market AI Survey 2026: U.S. and Canada, do not fully reflect the true business value of AI, which RSM considers 'digital labor.' The firm argues that organizations have overcorrected by intensely focusing on AI costs, particularly token consumption, without adequately defining AI's role in the workforce or measuring its impact on outcomes and business value, similar to how human employees are evaluated.
Why It's Important?
This shift in perspective is crucial for U.S. businesses investing heavily in AI. Misguided measurement can lead to underestimating AI's true contribution, potentially hindering further investment and innovation. By treating AI as 'digital labor,' companies are encouraged to prioritize value creation over mere cost reduction, fostering a more strategic approach to AI adoption. This re-evaluation of metrics can influence how companies allocate resources, develop AI strategies, and integrate AI into their operational frameworks. It also suggests a need for new accounting and financial reporting standards to properly reflect the intangible benefits and long-term value generated by AI, impacting investment decisions and competitive advantage in the rapidly evolving digital economy.
What's Next?
Organizations are advised to review their current AI use cases and assess necessary changes to support a value-based operating model. The immediate next step involves setting aside traditional cost calculations as the primary measure and creating new measurement processes that focus on outcomes and business impact. This will require developing an operating model that allows for effective measurement, governance, and scaling of AI. RSM suggests that while creating entirely new metrics might be tempting, organizations can leverage existing metrics more efficiently to gain a comprehensive understanding of AI's impact on the entire business. This evolution in AI measurement will likely drive further research and development in AI governance and ethical considerations.
Beyond the Headlines
The redefinition of AI as 'digital labor' by RSM US LLP carries profound implications beyond mere financial metrics. It suggests a philosophical shift in how businesses perceive and integrate AI into their workforce, potentially influencing future labor laws, employment structures, and even the concept of productivity. If AI is viewed as labor, questions arise about its 'rights,' accountability, and the ethical considerations of its deployment, particularly concerning job displacement and the future of human work. This perspective could also lead to new models of human-AI collaboration, where the focus is on augmenting human capabilities rather than simply replacing them. The challenge lies in developing a framework that not only measures AI's economic value but also addresses its societal and ethical dimensions, ensuring responsible and sustainable integration into the economy.
