FOMO, or Fear of Missing Out, in the context of AI, refers to the anxiety of lagging behind 
by not adopting AI quickly enough. Research by Conclusion shows that 38% of finance professionals experience FOMO within their organizations. They feel pressured to implement AI  solutions simply because “the competition is already doing it.” 

This often leads to hasty decisions, where the fundamental prerequisites for successful AI deployment are overlooked. Examples include the absence of a clear data strategy, vague governance responsibilities, or insufficient employee training. These oversights can have serious consequences. Without a solid foundation, the risk of data breaches, compliance issues, or internal resistance increases significantly. 

On the other side of the spectrum is FOMM: the Fear of Making Mistakes. This is especially prevalent in finance, where professionals deal with sensitive data, complex regulations, and stringent compliance requirements. The research reveals that 53% of finance professionals consider FOMM to outweigh FOMO. Moreover, 11% report not using AI at all—yet—due to fear of misuse. As a result, valuable opportunities are missed.

What does this mean in practice? Finance professionals fear that AI might: 

• Lead to incorrect conclusions 

• Violate privacy regulations 

• Produce unreliable risk assessments 

These concerns result in caution and restraint. Understandable, but also risky: innovation is delayed or abandoned altogether. 

The solution is not to choose between FOMO or FOMM, but to develop a balanced and well-considered AI strategy that anticipates both. People play a pivotal role in this. Technology can do a lot, but without employee support and skills, successful implementation is impossible. 

Both types of fear stem from human behaviour we can all relate to. By actively guiding, training, and involving employees in AI projects, trust can be built and resistance reduced. Only then can the true potential of AI be realised. The research also shows that employees are explicitly asking for this: 67% express a need for more knowledge and training in AI. This means organisations must invest in education, training, and a safe learning environment where mistakes are allowed. Governance and security are essential, but the real difference lies in how well employees are supported throughout the transformation