It was a real privilege to sit down with ten likeminded technologists at the recent Banking Transformation Summit (BTS) in London and host a roundtable on Practical Applications of AI for Efficiency and Insight.

I began the session by talking broadly about how much Artificial Intelligence (AI) has been a buzz term in the tech industry for many years. In fact, many financial institutions have been using Machine Learning and other AI tools for more than a decade, and yet a majority of those organisations struggle to translate the hype into tangible business value. A recent survey revealed that only 4% of AI projects were adding significant value to companies by getting over the POC start line into something more realistic.

This eye-catching statistic got the attention of several CTOs who are now seeking real-world examples of successful AI implementations.

One CTO expressed a keen interest in utilising Generative AI for software engineering, as he had implemented AI code development tools to support increasing quality (resulting in a 10% uplift in speed and quality) but didn’t have enough industry data to understand if this was a sufficient game changer. He felt they needed to continue with the journey for a longer period to get a more comprehensive view. He was particularly intrigued by Version 1’s Decipher and its potential applications for his company’s clients. This highlights a growing trend of businesses looking to leverage AI not just for internal processes, but also as a value-add for their customers.

Another technology leader shared a more holistic approach to AI adoption. “Our strategy is to enable the entire organisation to use generative AI,” he stated. This democratisation of AI tools across different departments and roles could be key to unlocking its full potential. By putting AI capabilities in the hands of employees at all levels, companies can foster innovation and efficiency improvements across the board.

However, not all CTOs are equally enthusiastic about AI’s promises. One executive admitted to experiencing “AI fatigue” due to the constant hype and inflated expectations. Despite this, they remained passionate about specific applications like Decipher and was eager to implement it as a means of cutting down on the time and effort to document legacy COBOL code. This sentiment underscores the importance of focusing on practical, results-driven AI solutions rather than chasing every new trend.

So, what does it take for an AI project to fall into that coveted 4% that adds real value? Based on these CTO insights, here are some determining factors:

  1. Clear use cases: Focus on specific problems that AI can solve, like improving software engineering processes
  2. Scalability: Look for solutions that can be deployed throughout the organisation, not just in isolated pockets
  3. User-friendly tools: Adopt AI applications that are accessible to employees without extensive technical expertise
  4. Customer-centric approach: Consider how AI can enhance your products or services for clients
  5. Measurable outcomes: Implement AI projects with clear metrics for success to avoid “AI fatigue”

As we move beyond the hype, it’s crucial to approach AI adoption with a pragmatic mindset. By learning from successful implementations and focusing on practical applications, organisations can harness the true potential of AI for improved efficiency and valuable insights.

The journey to effective AI utilisation may be a challenging one, but as these CTOs demonstrate, there are real opportunities for those willing to cut through the noise and focus on tangible results. As the field continues to evolve, we can expect to see more success stories emerge, paving the way for AI to become a truly transformative force in business and technology.

We rounded off the session with some acknowledgments that not everyone was at a point of deploying Gen AI into Financial Services products just yet. However, there was considerable appetite for the productivity gains which were the most meaningful aspect at this point. It was obvious what the most talked about theme was at the BTS and it was great to get some real insights from a broad cohort.