Connor Heaton, VP of Intelligent Automation and AI at Strategic Resource Management, has a wealth of insights to share on the transformative potential of new AI tools, specifically Large Language Models (LLMs).

The top 3 insights from this article:

  • Significance of Chat GPT's launch: While AI was already embedded in many life aspects, such as movie recommendations or social media algorithms, Chat GPT's launch made AI interaction more direct and widespread. 
  • Potential and pitfalls of AI: The rapid growth of AI, especially in the financial services industry, presents significant opportunities, but it also comes with challenges.
  • Continuous learning is imperative: In the financial services realm, leaders need to commit more hours per week to ongoing learning and development. This is not merely about understanding the latest technologies but also about adapting to new mindsets and ways of functioning. AI, especially models like GPT-4, can play a pivotal role in facilitating this learning process.

The Advent of AI in Mass Consciousness

On November 30, 2022, AI made a gigantic leap into the mass consciousness of humanity. The launch of the large language model ChatGPT led the charge, swiftly amassing over 100 million users in a mere two months. Since then, the landscape of apps, tools, and integrations has been expanding at an exponential pace. As financial brand leaders navigate this digital maze, they find themselves caught in a whirlwind of anticipation and caution.

The growth opportunities these AI tools present in the financial services industry are tremendous. However, as established technology vendors rush to integrate these models into their offerings, there are potential pitfalls to be aware of.

When asked about the exciting developments in his world, Connor points to the rapidly evolving AI space. The AI sector has been on a tear, with new tools and solutions popping up at an unprecedented pace. These tools are resolving long-standing issues and challenges, marking the dawn of an exciting new era.

It's not that AI was an entirely new phenomenon; the technology has been in existence since the 1960s, undergoing several cycles of excitement and disillusionment.

What set the launch of Chat GPT apart was its accessibility and immediate usability. It was a tool that was instantly useful, interesting, and delightful, offering capabilities that were impressively refined compared to past iterations.

This marked a significant step in the democratization of AI tools. While AI had been embedded in many aspects of our lives — from Netflix recommendations to our social media feeds — its direct interaction with the masses had been limited.

The advent of Chat GPT kick-started a new era of awareness, investment, and product development in AI.

And the journey has only just begun.

Possible Pitfalls For Banks and Credit Unions

With these fast-paced developments, it is becoming more crucial than ever to navigate this new age of AI wisely. Financial brands have this tremendous opportunity to leverage AI, not just as a bolt-on solution, but as infrastructure for growth.

On the flip side, there are pitfalls that need to be avoided to ensure banks and credit unions are moving forward responsibly as we integrate AI and large language models into their operations.

Connor shares that one of the first major pitfalls that financial leaders need to be aware of is the risk of bias in AI models. These models learn from the data they are trained on, and if that data reflects existing biases, those biases will be reflected in the model's outputs. This can have serious implications, especially in a field like finance where fair and equitable service provision is crucial.

Another potential pitfall Connor says is lack of transparency. This is often referred to as the 'black box' problem of AI, where it's not always clear why a model made a certain decision or prediction. This can make it difficult to troubleshoot problems or understand why a model is behaving a certain way.

And finally, Connor believes there's the risk of over-reliance on AI. As powerful as these tools can be, they shouldn't replace human decision-making completely. Humans need to remain in the loop to provide oversight, ethical considerations, and critical thinking that AI models aren't capable of.

AI in the Financial Realm: A World of Opportunities

With those pitfalls in mind, there are still great opportunities for transformation and growth when it comes to AI tools, especially large language models, in the financial services space.

Connor shares customer service is one area where AI, and large language models in particular, can make a big impact. They can handle routine queries, provide personalized financial advice, and assist with transactional tasks, freeing up human staff for more complex issues.

AI can also significantly enhance risk assessment and fraud detection by analyzing vast amounts of data more accurately and quickly than humans. It can detect patterns and anomalies that might be missed by traditional methods, thereby improving decision making and reducing risk.

Furthermore, AI can improve financial forecasting by leveraging large volumes of data and sophisticated algorithms to make more accurate predictions. This could revolutionize financial planning and strategy.

When implemented correctly, AI holds the potential to streamline operations, enhance customer experiences, and drive growth in the financial services industry.

Investing in Learning: A Non-Negotiable Priority

In this Age of AI and rapid technological advancement, we must constantly upgrade our knowledge and skills, otherwise, we risk becoming obsolete.

In the context of financial services, there's a dire need for financial brand leaders to invest more hours per week in ongoing learning and development. This investment in time should not be seen as a "nice-to-have", but rather as a critical survival strategy. Remember, the goal here is not just to keep up with the pace of change but to stay ahead of it.

Furthermore, learning is not just about acquiring new skills or understanding the latest technologies. It's also about adapting to new mindsets and new ways of doing things. The old ways of doing things may not work in this new era. Therefore, we need to constantly challenge our own assumptions, question our biases, and be open to new ideas and perspectives.

AI in Learning and Development: A Catalyst for Change

The good news is that AI, particularly large language models like GPT-4, can be a valuable tool to facilitate this continuous learning process. It can summarize long articles, extract key insights from a plethora of online content, and even offer personalized learning recommendations. It can provide us with the information we need, when we need it, and in the format we prefer.

Imagine having your own AI-powered learning assistant that can help you stay updated on the latest trends, research, and best practices in your field. Instead of spending hours reading and researching, you can focus more on understanding, assimilating, and applying the knowledge in your work.

But learning in the age of AI is not just about consuming information. It's also about creating new knowledge. With AI, we can explore new ideas, test hypotheses, and even develop innovative solutions to complex problems. AI can augment our thinking process, helping us to see patterns, connections, and insights that we might otherwise miss.

So, as financial brand leaders, we need to rethink our approach to learning. It's no longer enough to just attend a few training sessions or read a few books. We need to be actively engaged in our learning, constantly seeking out new information, questioning our assumptions, and experimenting with new ideas.

Riding the Wave of Change: Cultivating Change Agility

In this context, the concept of AQ or Adaptability Quotient becomes really important. AQ is about our ability to handle change, to be flexible in our approach, and to be resilient in the face of adversity. And as you mentioned, it's something that can be measured and trained.

The idea of taking a cold shower for seven days is a great analogy. It forces us to get out of our comfort zone and adapt to a new environment. And it's the same with change. We need to embrace it, not resist it. We need to see change not as a threat, but as an opportunity for growth and innovation.

But cultivating change agility is not just an individual effort. It requires a collective effort from the entire organization. It's about fostering a culture of learning and innovation, where everyone is encouraged to question the status quo, share ideas, and take risks.

AI is a powerful tool that can help us navigate the complex and rapidly changing world. But the real game-changer is our ability to learn, adapt, and innovate. Whether it's AI or any other technology, the key to success in this age of exponential change is not the technology itself, but how we use it to drive human transformation and create value.

The Common Misconception about AI and Large Language Models

Financial brand leaders often have a rudimentary understanding of artificial intelligence (AI) and large language models, typically based on limited exposure or brief interactions. Commonly, they've dabbled with AI tools like Chat GPT, gaining some insight into their capabilities. However, many fail to comprehend the vast potential these tools have across various domains and industries.

The prevalent misunderstanding is the belief that AI, specifically large language models, are merely advanced chatbots replacing IVRs (Interactive Voice Response systems). This narrow viewpoint overlooks the technology's transformative power in content generation across diverse formats, be it text, audio, or video. The reach of AI extends far beyond customer service into areas like development acceleration, disrupting art and content creation, and even cyber threats and fraud prevention.

For AI to be used to its fullest potential, it is essential to realize its omnipresence in our existing technologies. Whether it's loan processing and origination systems or marketing apps, if they aren't already employing AI or large language models, they will most likely incorporate them in the future. Developing a thorough understanding of these tools, their strengths, weaknesses, and quirks will facilitate better decision-making and usage across multiple domains.

Moreover, the rate at which technology is evolving necessitates a continuous learning and adaptation mindset. Encouraging employees to experiment with large language models in a safe environment, learn their strengths and weaknesses, and gain experience using these tools can only benefit organizations in the long run.

The First Step Towards AI Integration

When it comes to integrating AI into daily operations, one of the simplest and most practical steps one can take is to use a large language model for tasks like drafting an email, a report, or a blog post. By leveraging GPT for such tasks, individuals can gain valuable insights into the technology's potential and its limitations. This approach is not only low-hanging fruit but can also serve as a stepping stone for more extensive applications such as marketing copy, board reports, and internal communications.

Understanding AI and large language models is no longer a luxury but a necessity in our ever-evolving technological landscape. As we navigate through the misconceptions and start harnessing the true potential of AI, we pave the way for a future where technology and humans work in harmony to create value and foster growth.

Take Action Today:

  • Invest in AI Responsibly: Address the 'black box' problem by choosing AI solutions that offer some level of explainability or by setting up systems where decisions made solely by the AI can be reviewed by human counterparts.
  • Revolutionize Learning and Development with AI:  As AI models and technologies evolve rapidly, it is essential to stay updated with the latest advancements. Allow employees to interact with AI tools in a controlled environment to better understand their capabilities and limitations.
  • Integration and Experimentation: Start integrating AI into everyday tasks such as drafting emails, reports, or blog posts. Using GPT models for these activities can be a good starting point.

In essence, financial leaders should see AI not just as a tool but as a partner that, when used responsibly and wisely, can drive immense value and growth for their organizations.

or more about financial transformation, reach out to James Robert Lay at the Digital Growth Institute.