Marco Argenti, CIO at Goldman Sachs, discusses the importance of safe experimentation and caution in adopting AI in financial services. They explore the emerging abilities of AI in reasoning and workflow and highlight the potential of generative AI to solve complex problems in the industry.
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Quick takeaways
Financial services leaders should exercise caution in adopting AI, understanding the potential dangers and pitfalls.
Generative AI technologies offer a new approach to addressing long-term data governance problems for legacy financial institutions, helping individuals understand complex concepts and make effective decisions, regardless of their level of expertise.
Deep dives
Caution in AI Adoption in Financial Services
Financial services leaders should exercise caution in adopting AI, understanding the potential dangers and pitfalls. Safe experimentation is crucial, defining the scope of what they want to achieve precisely. Implementing AI training and inference for use cases like analytics, anti-money laundering, and surveillance requires a safety-first approach. It is important to tightly control access to information and balance accuracy with safety. AI should augment human decision-making rather than replace it, acting as a copilot rather than executing actions directly.
Insulating AI Models from Harm
To protect AI models in development from harm, financial services professionals should consider using open-source models that can be run on-premises or within a controlled environment. Large proprietary models offer emerging abilities but may require additional precautions. Enterprise versions of these models, with data-sharing features turned off, help secure information. A hybrid approach, combining larger models with highly specialized models trained on specific data, offers both emerging capabilities and data protection.
AI's Role in Data Governance and Problem Solving
Generative AI technologies offer a new approach to addressing long-term data governance problems for legacy financial institutions. By processing information and communicating with employees, generative AI assists in handling tech debt and updating legacy systems. It acts as an equalizer, helping individuals understand complex concepts and make effective decisions, regardless of their level of expertise. It can also aid in explaining and translating code, leading to increased efficiency and productivity.
The Future of Generative AI in Workflows
Generative AI has the potential to reshape workflows by providing intelligence, adaptability, and robustness. Intelligent process agents trained by AI can navigate process changes more effectively, resulting in more flexible and robust automation. This ability to reason and adapt to the current state of the world enhances productivity and efficiency. AI can also generate and adapt processes dynamically, resulting in enterprise systems that can be reprogrammed and trained to handle change more effectively.
Today’s guest is Marco Argenti, Chief Information Officer at Goldman Sachs. Before working with Goldman Sachs, Marco served as SVP of Developer Services at Nokia, then Vice President of Technology of Amazon Web Services (AWS) in 2013, where he started and ran several AWS businesses, including mobile, serverless computing, Internet of Things, and augmented and virtual reality. He joins us on today’s program to talk about where banking leaders should be showing the most caution when it comes to emerging AI capabilities and how financial services professionals should think of cultivating their skills for the future. If you’ve enjoyed or benefited from some of the insights of this episode, consider leaving us a five-star review on Apple Podcasts, and let us know what you learned, found helpful, or liked most about this show!
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