By Chris George, Vice President Product at CI&T
Generative AI is a revolution offering unprecedented opportunities and developing at a pace unlike anything we’ve witnessed previously. In the City of London, more than a third of financial service leaders use it at work every day. On Wall Street, Morgan Stanley’s recent appointment of a Head of AI signifies one of the latest moves among major banks to embrace the technology.
As generative AI advances, there is huge potential for enhanced personalisation, recommendations, and educational content. Entirely new financial products, personalised investments and micro insurance will be shaped by this acceleration in AI, in addition to improving efficiency and streamlining processes. Already this is a priority for many – our research found that three-quarters of businesses (76%) expect to use generative AI in the next 12-18 months if they haven’t started doing so already. Yet, less than 1 in 10 (8%) organisations describe widescale use across their organisation.
Every department must examine all existing business processes to assess if and how generative AI can assist and evolve an organisation for the better. And, crucially, organisations must ensure solutions can be deployed at an enterprise level of safety, security, regulatory compliance and ethical responsibility.
How businesses can identify and mitigate generative AI’s risks
Assessing the potential use cases of generative AI is crucial. But business leaders across financial services as well as other sectors must also recognise the accelerated pace of the public release of these technologies. Major corporations are now racing for the next breakthrough for commercial gain.
It’s no surprise, then, that governments and regulators are hastening their efforts to develop AI legislation. The European Union’s AI Act ensures “safety and compliance with fundamental rights, while boosting innovation”. In the US, President Biden’s Executive Order enshrines the safe, secure, and trustworthy development of AI.
It’s crucial to take note of this progress in AI regulation. However, the resulting changes will also heavily impact how businesses can use the technology. Along with these incoming regulations, companies must ensure that they are also defining their own governance for the adoption of AI within their businesses.
Protection through good governance
AI governance at an individual business level will involve working out what guardrails a company puts in place regarding privacy, security, compliance and ethics in implementing AI solutions. This is a board-level conversation, in which leaders must fully comprehend the transformational change to their business that AI presents, and consider their AI strategy and roadmap, methodology and processes, risk management measures, and regulatory compliance. Then, they must examine how it all aligns with their business goals, investments and budgeting, and ESG commitments.
Companies using AI in areas like banking and finance must be even more cautious for the sake of protecting customer data. This involves embedding regulation and compliance into any AI initiatives within product development teams right from the start, so that risk factors are considered at every stage of planning and execution. Once governance and team structures have been established, organisations can then begin to look for practical business use cases, both internally for efficiency and externally for improved end-user experiences.
Early focuses should include end-to-end software development, customer services and operations, marketing and sales, and broader automation of business processes. This process will involve calculating which pain points and opportunities present themselves best to be solved by generative AI. Then, working on a proof of concept (POC) to minimum viable product (MVP) scale, as with all digital innovation, to ensure the development of the right use cases.
Fostering the relationship between humans and AI
Despite its advances, generative AI still has no idea whether what it’s producing is ‘good’. There have been tendencies for AI to ‘hallucinate’ and make inaccurate assumptions, which can be a threat to company reputation. The only way it can learn is through (human) feedback. We need to remember that it is our choice to control AI so it augments our tasks and becomes an invaluable, time-saving tool across our working and personal lives. It can become the scaffolding of an organisation, augmenting our lives by fulfilling menial and mundane tasks and allowing more time for humans to concentrate on alternative work.
Reaching this point will require comprehensive preparation from organisational leadership teams. It is equally important for companies to be transparent with customers about where and how they are implementing AI.
A revolution on the horizon
There are still so many unknowns with generative AI because of how quickly the technology is evolving.
However, as regulations and compliance evolve, and with good governance by organisations, generative AI has the potential to revolutionise banking and finance.
With its ability to quickly process vast amounts of data and identify patterns, generative AI can help banks make more informed decisions and improve customer experiences, and is already significantly improving the software development lifecycle.
This will lead to increased customer satisfaction and loyalty, ultimately enhancing the overall profitability of the institution. As such, it is essential for banks to stay informed about developments in generative AI and proactively integrate it into their operations where possible and sensible.