By Roman Eloshvili, Founder and CEO, XData Group
For over a year we’ve been seeing tons of news that point towards AI technology having firmly entered our lives. And it is a unanimous decision that the time to adapt is upon us. Banks and fintechs have recognized this – they are actively working to introduce artificial intelligence into their operations, striving to get ahead in the tech race. Just recently Morgan Stanley unveiled plans for an AI assistant called Debrief, and that’s only one example.
But, of course, AI adoption comes with its share of challenges, with the technical details and implementation costs being only a small part of it. In fact, banks and other financial institutions participating in the AI race should, first of all, think about people. Right now, 60% of executives in banking and financial markets acknowledge that they are pushing for the implementation of AI faster than people may be ready for it. And that is wrong.
So, how can financial organizations better prepare their employees for the advent of AI? What can be done to deal with staff and cultural challenges?
The true face of AI adoption challenges
One of the biggest challenges in AI adoption is the rather prominent shortage of skilled AI professionals. Banking is by no means the only sector where this technology is being adopted, and the more it spreads across industries, the bigger the demand for AI talent grows.
At present time, it would be accurate to say that the demand far exceeds the supply. As such, companies often have to resort to “poaching” AI specialists from one another, or invest in internal training so that their existing employees can develop AI skills.
Furthermore, there is also resistance among employees themselves to consider, as many people may worry that artificial intelligence will make them unnecessary, leading to job losses. This anxiety can result in reluctance to engage with AI initiatives, slowing down the adoption process. And even the more positively-thinking workers might be resistant to the idea, and dealing with AI would require them to retrain and acquire new skills.
From a technical viewpoint, it also bears mentioning that many organizations in the banking sector operate on legacy systems that are often not compatible with modern technological developments. Such outdated infrastructure may be unable to support AI services, making integration difficult and costly. And yet, upgrading or overhauling these systems can be a complex and resource-intensive process, which is also a reason for reluctance among many organizations.
Moreover, due to strict data protection rules, companies often cannot use common large language models (LLMs), such as cloud-based services like ChatGPT. In order to stay compliant with regulations, companies must develop their own AI models, which requires significant investment and expertise. Which brings us back to the need for specialized skills and the shortage of AI professionals.
Healthy AI adoption starts with education
As we’ve already covered earlier, cultural and personnel challenges are becoming increasingly prominent where AI adoption is concerned. So what can be done about them?
First of all, the scarcity of specialists in this field means that there is a need for a strategic approach to talent acquisition and development. Rapid technological advancement has outpaced the availability of skilled professionals, and if companies want to gain a competitive edge, they need to start securing expertise in AI as quickly as possible.
While the competitors are still deliberating their AI strategies, you can start proactively developing in-house talent. Recognize that artificial intelligence is not a temporary trend that will pass before long. So, develop a long-term AI adoption strategy that includes continuous investment in AI technologies and personnel development.
Secondly, while many employees worry that their roles could soon be replaced by AI, they often do not take the time to consider how their jobs can actually be made easier through automation. AI will not replace people outright, but their roles will indeed transform. I believe that the future of the financial markets lies in a hybrid approach, where humans take on the function of moderating AI decisions. The technology is far from perfect, which is why it requires human oversight.
In order to overcome employee resistance to AI adoption, company leadership will need to maintain clear communication about the benefits of this technology and how AI can enhance their work. Education has to be at the forefront: ensure that your staff is aware of ongoing AI initiatives and invest in their ongoing training to keep them prepared for the evolving job landscape. Change does not come easily but proper management can alleviate fears and make the transition easier.
Lastly, let’s talk about data. Earlier I mentioned that companies often have to develop their own AI models. Data is the cornerstone of this process, so continuously collecting it is of great importance.
For example, if you have extensive amount of data from customer support communications, it can be used to train specific support AI models that would improve the efficiency and quality of service in this area. In the same vein, compliance-related data can be gathered to develop AI models that can assist with regulatory requirements, ensuring adherence to proper safety standards.
Remember: AI is for people too
When trying to succeed in the technology race, it is important not to forget about people. Communicating to them about why AI adoption can be a good thing is crucial if you want to broaden their horizons as professionals. By starting the AI adoption process now and prioritizing education and training for their workforce, companies can better prepare themselves for the AI-driven future.
