Why AI Adoption Falters in Large Organizations, According to Hung Lee

In a recent LinkedIn post, Hung Lee delves into the challenges large institutions face when trying to harness the full potential of Artificial Intelligence (AI), contrasting their struggles with the agility of individuals and smaller firms. Lee observes a significant gap between individual productivity gains and institutional-level output when implementing new technologies.

Lee highlights the distinct capabilities of different organizational structures in adopting AI, stating:

“it’s clear to me that individuals or small team companies, have a freedom to move with the velocity that the technology now demands. Larger institutions? Not so much.”

This divergence, according to Lee, is not solely due to regulatory hurdles. He posits that a more significant impediment is the lack of coordination within larger entities.

The Coordination Conundrum in AI Implementation

Hung Lee argues that while individual employees might experience a ten-fold increase in productivity due to AI tools, this does not automatically translate to a similar scaling of output for the entire organization. The core issue, as Lee sees it, is coordination.

He elaborates on this point:

“Basically, individual employees becoming x10 more productive do not sum to organisations being x10 more productive, because those capacity increases are often uncoordinated, and even uncontrolled, leading to at best bottlenecks, at worse catastrophic system failure.”

This dynamic suggests that simply providing AI tools is insufficient. Lee’s analysis points to a systemic issue where the integration of enhanced individual capacity into the broader organizational workflow is not effectively managed.

Empowering Individuals While Building Institutional Capacity

Lee proposes a dual strategy for Talent Acquisition (TA) and HR departments navigating this complex landscape. The first part involves identifying and empowering the most capable employees, often referred to as ‘high performers’ or ‘super-users’ of new technology.

However, this empowerment must be coupled with a strategic focus on building the necessary infrastructure. As Lee notes:

“The current and future task of TA / HR is to radically empower your most capable employees, AND build the institutional infrastructure that can channel their accelerated output into value for the organisation…”

This infrastructure, in Lee’s view, is crucial for channeling the increased output from empowered individuals into tangible organizational value, preventing uncoordinated efforts from becoming system-wide disruptions.

The Role of ‘Vibe Coding’ and Community Insights

Lee also acknowledges the contributions of his ‘AI Braintrust’ community on LinkedIn, specifically mentioning members like Nick Rickards, Tony de Graaf, Marcel van der Meer, Joey N. Leandro Gomes da Silva, and Alla Pavlova for their work in developing recruiting artifacts through ‘vibe coding.’ This reference suggests that practical, community-driven innovation is a key factor in demonstrating AI’s potential at an individual or small-team level, further underscoring the gap with larger institutions.

The post concludes with a nod to potential sponsors and a list of other relevant discussions happening in the recruiting and HR tech space, indicating Lee’s engagement with the broader industry ecosystem.