AI adoption in financial services is accelerating rapidly, but what’s driving this pace, and why are some firms more willing to adopt AI?
In this short video, our MD, Henry Duncombe and CTO, Dan O’Hara, explore how constant innovation and fear of missing out are shaping AI decisions and how competitor progress is often overestimated.
Video transcript
Companies are adopting AI at breakneck speed. Within financial services, clients are paying close attention to the risks involved. We’re seeing a spectrum of risk appetite, ranging from firms that are highly risk-averse to those operating on the bleeding edge of AI technology.
The risk spectrum
At one end of the spectrum, we see firms that remain very risk-averse, choosing to use AI only in specific ways to reduce their exposure. On the other side, some firms are willing to try the very latest capabilities, even though most of AI is still considered "bleeding edge" because it changes so frequently.
There is a common perception that everyone else is adopting AI faster or using it more in their business than you are. While there is a lot of pressure, firms also recognise that this might not be entirely true. Compared to a couple of years ago, we simply understand the risks in much more detail now. Ultimately, it is up to each company to decide whether they want to take on those risks or take a "sit back and see" approach.
Is it FOMO?
There is certainly a level of FOMO (Fear Of Missing Out). With new capabilities being released constantly by AI vendors, there is a strong desire to jump on the bandwagon. AI promises to solve a lot of problems and make things much more efficient.
We can see a parallel here to the shift toward the Cloud ten years ago. Cloud technology also asked firms to dramatically shift how they used technology, but it took a long time to convince people. While early adopters like large streaming platforms moved quickly, institutional businesses didn’t move to the cloud for a long time.
With AI, we are seeing that same big shift, but people are willing to move much more quickly than they did with the cloud.
Key differences: AI vs. cloud
Adoption speed: The cloud took years to gain institutional trust, whereas AI adoption is happening almost immediately.
Specific capabilities: AI is often sought out to perform very specific tasks that firms have always wanted to automate, creating a more immediate atmosphere of wanting to try it.
Risk maturity: While the technology is new, the industry is entering this phase with a better understanding of risk management than it had during the early days of the cloud.
