Rapid adoption of AI

Asad highlighted the swift adoption of AI across all industries, and the democratization of AI is helping asset management firms adapt quickly to the new technology. Nearly everyone uses and interacts with AI, Asad says, which is why AI adoption will be faster for asset management than the previous waves of technology.

Compliance and legal considerations

Asset management has significant compliance, legal, and regulatory oversight. Asad noted that other regulated industries, such as healthcare, have seen significant benefits from AI. Asad stressed, "Asset management organizations looking to adopt AI will need to focus on data governance, data quality, and data security. The compliance piece is going to be addressed very quickly."

Importance of data governance

Quality, well-formatted data is essential for AI to function properly. Poor data management can increase risk and loss of trust. Asad emphasized the critical role of data governance, security, and quality in leveraging AI effectively, Data governance and security is paramount and is the foundation of any AI initiative.

Establishing a Center of Excellence for AI

Asad recommended establishing a Center of Excellence for AI in organizations, bringing together representatives from different departments to create policies and processes around AI adoption and data governance. "Once you create a center of excellence, you create policies around it, you create processes around it, and then you utilize technology to implement and enforce them."

Leveraging vendor technology for enhanced governance

Vendors like Microsoft are at the forefront, offering enterprise-ready AI solutions tailored to industry-specific needs. Platforms such as Azure OpenAI provide the technological backbone for AI initiatives and ensure adherence to governance and compliance standards.

Practical implementation and experimentation

Asad observed that while experimentation with AI in asset management is high, its adoption into production and practical application is slow. He stressed the importance of focusing on solving specific problems with AI rather than just experimenting with the technology, "What we want to do for these organizations is to lock into a certain problem, not lock into the utilization of technology, and solve a problem using the technology rather than experiment with technology."

Impact on reporting and business intelligence

Generative AI tools facilitate operational reporting and efficiency by making it easy to create reports and visuals through natural language prompts. "The key is how good your data set is and how expanded your data set is to answer the question posed to it. If your data is not right and you ask the GPT or copilot a question, the reporting will be wrong, which is very dangerous."