Key takeaways from a roundtable discussion exploring the challenges of proving ROI, and the importance of fostering a culture of innovation while navigating the transition from analogue to digital operating models.
Generative AI (gen AI) holds immense potential to transform industries. However, transitioning from ideation to adoption poses challenges for many organisations. I recently participated in a roundtable hosted by Raconteur, which brought together senior executives in financial services to understand the hurdles leaders encounter when proving the business case for gen AI.
The discussion delved into the adoption, challenges, and long-term value of gen AI in various contexts, from payments to wealth management and universal banks. It became clear that each institution faces unique challenges and use cases, and there is no one-size-fits-all solution for adopting AI.
Instead, gen AI is a continuum, constantly evolving and providing different scenarios across value streams. This is not an end state but rather an ongoing process of co-creation and co-innovation.
One of the most striking takeaways from the roundtable was the challenge of proving the business case for gen AI adoption. Many benefits – such as improved efficiency, productivity, and time savings – are not easily quantifiable within traditional organisational frameworks. This can make it difficult to demonstrate ROI in boardrooms with low risk-appetite.
To cut through the hype and convince the C-suite of gen AI’s value, they need to experience the benefits first-hand. The focus should be increasing the predictability of numbers and delivery systems, which gen AI can significantly improve.
This predictability can lead to tangible outcomes, such as reducing false positives in fraud detection and increasing sales. These concrete results can be powerful in making the case for gen AI adoption, keeping the reader focused on the potential benefits.
Debunking AI fear
Throughout the discussion, it became evident that the success of gen AI in financial services largely depends on an organisation’s willingness and ability to innovate.
Embedding a culture of innovation and experimentation throughout the entire business was emphasised as crucial. This proactive organisational mindset sets pioneers apart from laggards in the sector.
Another vital aspect of successful gen AI implementation is convincing cynics within the workplace. Discussing the importance of debunking the fear, uncertainty, and doubt (FUD) surrounding the technology is key.
By helping clients understand the difference between consumer-grade and enterprise-grade gen AI and aligning the technology with their risk and regulatory frameworks, we can unlock its true potential and expand how people consider incorporating it into their use.
Examples shared during the roundtable further reinforced the importance of leveraging internal data to support business use cases and demonstrate the impact of gen AI adoption.
By combining world-class research, highly skilled multi-discipline teams, and a deep understanding of customer needs and organisational strategy, financial institutions can create value on a global scale. AI literacy pathways and published principles and standards for AI and big data use are excellent models for engaging and informing the workforce while ensuring responsible and ethical AI development.
Digital mindset
As financial institutions transition from analogue to digital operating models, visualising what a more digital operating model might look like with gen AI technologies in play is a critical first step. By doing so, banks can create end-to-end value streams and successfully navigate this generational disruption, ultimately delivering unparalleled value to their customers.
I left the roundtable discussion feeling energised and optimistic about gen AI's transformative potential in the financial services sector.
As we continue to co-create and co-innovate, I am confident that organisations that focus on proving the business case, fostering a culture of innovation, convincing sceptics, leveraging internal data, and visualising digital operating models will be the ones to unlock the long-term value of gen AI.
The journey may be challenging, but the rewards will be well worth it for those who embrace this exciting new frontier.
