AI-assisted apps and "robo-advisors" seemingly make it easier than ever for individual investors to identify worthwhile opportunities and craft a strategy without engaging a human advisor. However, the reality is more complicated.
AI is transforming markets and advisory services alike, but nuance and trust continue to be significant success factors in any investment strategy. Experienced professionals will have a leading role in analyzing investment markets for the foreseeable future — and the advisors who thrive in the emerging environment will be those who use modern tools to complement their real-world expertise.
“The proliferation of AI has changed market dynamics in several positive ways, but robots aren’t likely to take over the investment world. AI might be able to utilize the science behind investing, but professional advisors and critical thinking drive the artform. It is the combination of the art and the science where we have the potential to truly benefit the client."- Chad Oviatt, Chief Investment Officer, F.N.B. Wealth Management
While individual investors may find platforms that promise automated trading and customization refreshing and convenient, certain facets of the technologies are old hat for professional advisors. Quantitative (quant) or rules-based funds, which leverage algorithmic processes to optimize and construct portfolios, have existed for years, and advisors have long used statistical analysis to enhance decision-making. In their current iteration, this is largely how newer AI advisory platforms work, as well. Based on a prompt or pre-established rules, an AI agent scours the internet for data, then produces a summary and/or recommendations for an investor.
The newest AI tools further streamline research for advisors, replacing or augmenting existing algorithmic technologies and unlocking insights to an even greater degree than before. In the span of minutes, rather than hours, analysts can dive into relevant business fundamentals of multiple companies or funds, assessing quarterly earnings, historic stock performance, product launches and market news to identify worthwhile investment opportunities. Similarly, rather than manually calculating the complex metrics that determine the best time to buy or sell a security, AI can quickly compute the results and provide an analysis that supports portfolio optimization. The time and resources saved can then be spent on relationship-building and strategy refinements.
Individual investors, meanwhile, can increase the speed with which they access market information and analysis. AI-powered tools may help to improve investor knowledge and transparency in a highly complex industry. While not infallible, if deployed prudently, AI can be used to efficiently diversify and rebalance portfolios, identify risky investments and provide up-to-date information about performance.
Automated trading platforms leverage thousands of data points to provide investment recommendations or simulate trades. The sheer volume of inputs can give investors a level of confidence in their portfolios, but it remains important to apply human experience, critical thinking and judgment to the outputs. For example, index funds or exchange-traded funds (ETFs) are popular with individual investors because of their lower cost, simplicity and innate diversification. However, if an investor asks an AI agent to build a portfolio wholly based on such funds, it will follow the instructions to the letter. As a result, there is a risk of concentrations, overlap and reduced diversification, given different funds may contain the same companies, or a concentration risk may develop in market-weighted indexes. An experienced human advisor can recognize such unintended risks before portfolio decisions are made.
Furthermore, AI modeling can help investors understand what has worked best in particular economic environments but does not necessarily account for new or unexpected economic policy changes. AI tools are also very good at building efficient portfolios given historical performance and correlations, but the timing and execution of portfolio rebalancing still requires human inputs, or the models must be artificially constrained to align with the needs of the average investor.Although some foresee AI to one day be a holistic portfolio manager, capable of administering all of a client’s assets, steering them to intended outcomes and balancing their life changes, estate plans, personal values and tax considerations, that time — if it ever comes to pass — is far off. Where we stand today, AI assistance is a net positive for both amateur investors and professional advisors, and the tools increase efficiency and augment decision-making with data-rich guidance, but clients still should know that investment advice is specific to their needs. Guidance from a trusted advisor, based on expertise and a long-term relationship, can tailor recommendations that are likely to have a more powerful impact on desired outcomes for the investment portfolio.
How a person feels remains an important factor in determining if their investments are suitable, on-plan and meeting their needs, making thoughtful communication vital. Perhaps one day AI will be able to meet a client eye-to-eye in the same way, but for now, the best option is for investor, advisor and AI to work together.
The F.N.B. Wealth Management team utilizes a blend of technology and personal expertise. Learn more about the group’s capabilities by visiting fnb-online.com/wealth.
