3 need-to-know AI insights for advisory firms to stay competitive and compliant

At Berkshire Hathaway's May meeting, renowned investor Warren Buffett remarked on the potential of AI, stating, "If I was interested in investing in scamming, it's going to be the growth industry of all time." 

Buffett's comment underscores one of the three big challenges associated with responsibly integrating AI in financial services, namely, safety vetting. Two other key issues for AI in wealth management are staying competitive and increasing productivity. I'll discuss each below.

AI safety vetting

Safety vetting of AI is the process of evaluating systems before they are integrated into a firm's tech stack in order to confirm that they will operate not only securely and reliably but also ethically (removing bias from AI is key). A robustly vetted AI system will produce results that better build user trust — and reduce the likelihood of unintended consequences. 

Generative AI applications are poised to revolutionize financial services, offering enhancements across various sectors, from personalized customer service via chatbots to improve order handling with the introduction of Dynamic MELO, the first AI-powered stock exchange order type. 

READ MORE: Don't fear the robots: The case for deploying AI in wealth management

Traditional AI applications, on the other hand, such as those powering recommendation engines on platforms like Amazon, have long been integrated into financial operations to detect fraudulent activities like money laundering. Many of the risk management, compliance and governance controls used for this technology can be applied to generative AI — and therefore incorporated into firms' AI safety vetting. 

To ensure effective integration of generative AI into financial services, firms can take these steps in their safety vetting process.

Understand priorities. There are many AI tools available that solve different problems. Firms must identify which generative AI applications are essential for their business.

Perform vendor due diligence. Implement governance processes to vet and manage technology usage, ensuring that any third-party AI vendors align with your firm's security, compliance and risk standards. A firm must research whether a vendor has committed to certain standards and whether it has a strategy to keep pace. Questions to ask include: Do you follow responsible AI standards, such as those of the National Institute of Standards and Technology's AI Risk Framework? How do you address risks such as faulty training data and discriminatory practices? Have you incorporated controls for cybertheft, privacy and consumer rights, addressing FTC concerns? Have you addressed concerns about IP rights? What are the organizations you monitor for trends and best practices?

Adhere to compliance and governance programs. Safeguard firm and client assets by monitoring usage disclosures and restrictions, adjusting cybersecurity controls, enhancing data governance and ensuring adherence to privacy regulations.

Staying competitive with compliance

Advisors have a fiduciary obligation to act in the best interests of their clients, which extends to the use of technology — including AI. Ensuring accountability for AI-driven errors in order handling or avoiding AI-washing in marketing materials, to cite just two examples, helps firms not only uphold fiduciary standards but also build trust. This, in turn, enhances client confidence and helps firms stay competitive

READ MORE: Enhancing firm-level advisory compliance in the age of AI

Last year, the SEC proposed a new rule to regulate predictive data analytics, which encompasses AI, highlighting the importance of aligning firm practices with evolving standards. While the proposed rule has not been finalized, the SEC has set the tone for standards through its speeches, press releases and enforcement cases. 

With increased regulatory and legislative efforts (including the EU AI Act and SEC, FTC and state legislative proposals), compliance officers and product leads should create forums for discussion before implementing new AI technologies. These discussions should address ethical concerns, transparency and accountability and promote risk management. For instance, certain states have proposed regulation based on automated decision-making (ADM) systems that would require notice, opt-out and redress for harm from AI mistakes or bias. Creating a new technology or AI forum will allow timely risk discussions about the trade-offs in using AI.

Staying ahead of these developments on AI means that firms can anticipate regulatory changes. That not only ensures compliance, but also gives them a competitive edge. 

Increasing productivity

Understanding evolving AI standards is not just about ensuring compliance with regulations as they evolve. It also presents an opportunity for productivity gains in an increasingly competitive landscape.

READ MORE: Financial advisors: Be the Indiana Jones of your own AI adventure

By aligning with fiduciary standards during AI adoption, advisors can ensure honesty, transparency and prudent management of assets, including data. Yes, this is likely to enhance client trust, but it can also improve decision-making processes for advisors, leading to their increased efficiency and productivity. Effective AI implementation can streamline tasks, reduce errors and free up time for advisors to focus on face time with clients, among other essential tasks. 

These insights on safety vetting, compliance and productivity highlight the importance of balancing innovation with material risks. To stay abreast of AI regulation and trends, attending conferences like Advise AI can provide valuable insights to distinguish between AI hype and its practical applications in wealth management. 

Malina Aagard contributed research for this article.