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Introduction

Will it rain today in my city—or on my portfolio? Since the 1970s, artificial intelligence (AI) has assisted investors with trading strategies and meteorologists with weather forecasts. Defined as machines that mimic the cognitive functions of the human brain, AI seeks and compiles information, helps sift through data, and analyzes it to improve decision-making used in our day-to-day living. AI powers the sensors that collect data on weather, carbon emissions, traffic patterns and countless other items.

The development and deployment of AI tools continue to embed themselves into nearly all aspects of daily life. AI platforms can allow individual users to use facial recognition on their phones, get new streaming recommendations based on personal viewing patterns, ask Siri for directions while driving, and even allow cars to drive without a human at the helm. The challenge of providing such customiza­tion cost-effectively and at scale requires AI deployment to understand the interests of clients and prospects as well as the context surrounding them. Automating selections of the next “best” offer for a customer requires real-time database connections, machine-learning and orchestration.

AI can boost most investors’ scale, speed and sophistication. Wealth management profiling systems can dynamically monitor clients’ behaviors and those of their family and associates to help inform their portfolio needs using AI’s ongoing flow of information. Portfolio managers can utilize AI to monitor sentiment across analysts’ reports, earnings calls, stock-price movements, news articles and social media activities. With AI tools, a portfolio manager can identify incongruencies that may lead to large price moves or behavioral biases in trade executions, and they can also decipher in real time whether a company’s practices meet targets for pay equity or carbon footprint reduction. The quality of AI results depend on the human to submit quality queries for better usage and outcomes.

With well-designed AI algorithms, investors can produce better outcomes. However, we still need professionals to operate AI tools to both guide and gut-check their recommendations. In this issue, we provide more on the transformative power of AI in investment management, with

“Copilot, not autopilot: How generative AI augments, but doesn’t replace active management,” written by Max Gokhman, Head of MosaiQ Investment Strategy;

“Durable passive thematic strategies—A solution unlocked by artificial intelligence,” by Ralph Corasaniti, Strategic Accounts & Innovation Director, Retirement & Insurance; and

“The ripe opportunity for AI in the workplace,” by Josh Anderson, Strategic Accounts & Innovation Director, Retirement & Insurance.



IMPORTANT LEGAL INFORMATION

This material is intended to be of general interest only and should not be construed as individual investment advice or a recommendation or solicitation to buy, sell or hold any security or to adopt any investment strategy. All investments involve risks, including possible loss of principal. There is no guarantee that a strategy will meet its objective. Performance may also be affected by currency fluctuations. Reduced liquidity may have a negative impact on the price of the assets. Currency fluctuations may affect the value of overseas investments. Where a strategy invests in emerging markets, the risks can be greater than in developed markets. Where a strategy invests in derivative instruments, this entails specific risks that may increase the risk profile of the strategy. Where a strategy invests in a specific sector or geographical area, the returns may be more volatile than a more diversified strategy.

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