Embracing AI: Making Informed Technology Choices to Grow Your Business

Artificial intelligence (AI) has undoubtedly been one of the hottest topics of 2023, and will likely continue to dominate headlines in the years ahead. But amidst all the hype, the term “AI” is often overused both inside and outside the tech realm, to describe or market technology that does not truly fall under the AI umbrella. So what is AI, and how can financial advisors effectively implement it to grow their businesses?

AI is a broad domain that encompasses roughly 12 fields of study. True AI is capable of learning from data, evolving, and exhibiting reasoning or problem-solving capacities that would typically demand human-like intelligence. These systems rely heavily on diverse training and auxiliary data to achieve flexibility in their designated tasks, and their efficacy is directly proportional to the quality of their training and depth of accumulated experience. In contrast, programmatic solutions operate based on explicit instructions, defined by set rules. Such solutions, especially when complex, are often mistaken for genuine AI techniques, and it’s important to understand the difference.

Basic AI has been around for decades, with the first AI programs developed as early as the 1950s. Today, AI has surreptitiously seeped into modern life, such as “watch next” recommendations, autonomous vehicles, and “smart” home devices. More specific to the financial landscape, algorithmic trading, fraud detection, risk and data assessment tools, and robo-advisors are all examples of successful AI integration (although some financial advisors may be interested to know that 2022 saw the use of robo-advisors fall for the first time ever, especially among individuals with over $500,000 in assets.)¹

The “AI in Financial Wellness Market” was valued at $10.23 billion in 2022 and is projected to reach $83.17 billion by 2030, signalling that AI is more than a passing trend.² What’s driving this explosive growth in the financial landscape? In part, the demand stems from an increasing expectation of personalization from clients, as well as a desire to do more, with more efficiency, from advisors. Recent trends in AI will likely continue to build upon themselves, enhancing operational efficiencies for advisors. This can be through mechanisms such as handling routine administrative tasks, providing risk management and compliance assistance, cybersecurity, and data analysis; as well as predictive forecasting and scenario modeling.

Of course, appreciating the growing capabilities of AI is only the first step in the long process of successful integration. AI is likely to become a valuable tool for financial advisors who are willing to allocate resources towards emerging technologies, with some of the shift already happening. Advisors who want to be on the cutting edge – or at least not left “in the Dark Ages” – must be proactive in their approach to AI and willing to embrace new technologies and processes, such as:

• Identify current operational weaknesses in both internal processes and client experiences
• Ensure your current tech stack is up-to-date for an easier transition
• Make sure your data sources are reliable and complete; AI is only as good as its data
• Prepare clients by informing them of impending changes and how it benefits them
• Go gradually. It’s prudent to adopt new systems and tools slowly, and it’s crucial to thoroughly test new technology before rolling it out.
• Monitor the performance of new AI-based systems, and be ready to pivot as needed

We must also be mindful of the risks that come with AI integration. Data safety is of the utmost concern when client information is involved, especially given that many publicly-available AI resources now incorporate user input into their datasets, potentially exposing information to other users. It is vital to control sensitive data and remain cognizant about the lack of security offered – although there is now a growing sub-industry racing to offer solutions. Additionally, standing compliance requirements for data encryption and auditable control of Personally Identifiable Information (PII) conflict with current capabilities of many AI technologies. It is also important that financial advisors not become overly-reliant on AI output, as the integrity of outside data is rarely guaranteed, and it can be all too easy to prioritize hard data at the expense of ‘soft data.’ Furthermore, advisors must be proactive in addressing biases that are inherent to many AI technologies, and ensure these biases do not impact service to clients.

While adoption of artificial intelligence into financial services will require planning, preparation, and mindfulness. When done so appropriately, these new technologies can help advisors streamline operations, handle rote administrative tasks, and provide valuable data insights, while improving the client experience by providing enhanced personalization and overall efficiency.

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1. Neal, R. W. (2022, October 5). Robo-Advisers Struggling to Retain Investors in 2022, Research Finds. Investment News. https://www.investmentnews.com/robo-advisers-struggling-retain-investors-in-2022-research-finds-227476

2. Xherald. (2023, September 11). “AI in Financial Wellness Market Size, Share, Growth Analysis, Trends, and Forecast 2023-2030” (2023). Digital Journal. https://www.digitaljournal.com/pr/news/xherald/ai-in-financial-wellness-market-size-share-growth-analysis-trends-and-forecast-2023-2030

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