It is impossible to discuss the role of AI in financial services without highlighting that 2020 was hugely disrupted by COVID-19 and the ripple effect is expected to last for years. Financial Institutions digital transformation strategies previously defined for 2020 quickly unravelled, exposing the inefficiencies to react and respond quickly when the pandemic gripped the world at an unprecedented speed. The reality is AI is encountered by most people from morning until night.

There has been debate over the true definition of AI as the expectations on what is deemed as ‘real intelligence’ change so often. At a high-level, AI as a field can be described as any technique that enables machines to solve a task like how humans would. 

Barriers to adoption of AI in financial services

Many companies and sectors lag in AI adoption. Developing an AI strategy with clearly defined benefits, finding talent with the appropriate skill sets, overcoming functional silos that constrain end-to-end deployment, and lacking ownership and commitment to AI on the part of leaders are among the barriers to adoption most often cited by executives.

• Lacking a culture of innovation – stakeholders within organisations hold immense power in the success of AI projects. Many financial organisations have small risk appetites this is filtered through business leaders on the ground responsible for IT transformation activities. When it comes to talent, training and upskilling are key. But this shouldn’t be just focused on the technology teams. Business teams also need to be upskilled in the art of the possible when it comes to AI, along with some of the drawbacks and other considerations.
• Data infrastructure - financial services firms typically suffer as their data is often siloed across multiple technologies and teams, with analytical capabilities often focused on specific use cases. The need to standardise data and ensure data is accessible is critical.
• Data privacy and cyber security - the use of personal information are critical issues to address if AI is to realise its potential. The General Data Protection Regulation (GDPR), which introduced more stringent consent requirements for data collection, gives users the right to be forgotten and the right to object which is a positive step in the right direction. Cybersecurity and scams that could manipulate perpetrate large-scale fraud are also a concern.
• Scrutinised costs - Costs in AI projects are often scrutinised by finance and senior leaders as the initial ROI is low. AI capabilities are long-term strategic investments so higher returns would be expected further down the line.

Conclusion

AI presents technological opportunities like no other. Unleashed from the orbit of science fiction, this is a real-world technology that is ready to be implemented in any business – today.

The capabilities of AI technologies will continue to grow exponentially as vast data sets needed for training AI solutions become more accessible. The time to move on AI is now. Low barriers to entry will bring ever fiercer competition for AI talent, AI patents and AI capabilities.

AI adopted early will transform the way financial institutions organise, run, accelerate and achieve growth. By implementing new innovative technologies, financial organisations will endeavour to reduce costs and create better experiences for customers and employees alike. This requires organisations to completely rethink their overall business operations including their workforce, a cultural shift is required to embrace new ways of working and technologies.

The uses and capabilities of AI continue to grow and change every day. This article highlights essential factors and advantages to be considered and further exploration is encouraged. AI should not be thought of as a business tool or extension of technology but rather as a transformative cultural change that needs to be considered in a very broad, multi-dimensional context.