That’s what AI is for. It learns to select and subtract topics and prompt advisors about whom to call and when among high-net-worth clientele. “What it does is it profiles every single client, every single portfolio, every single day and intraday and evaluates literally thousands of ideas,” McMillan says of the firm’s new rollout.

These algorithms can look at new data—such as the downgrade of a company or a client’s equity exposure in Japan. The algorithms might also prompt a client to use a client aggregation tool, or send a safe driver manual to a client whose child is turning 16. The technology scores clients on the relevancy of this data to their situation and then looks at what actions they’ve taken before.

“So for example,” McMillan says, “over the last six months I have sent you 31 single security equity ideas, both downgrades and upgrades, and you have opened 94% of them. You have clicked through on the content 83% of the time. And you’ve transacted on 47% of the ideas that I’ve sent you.”

Those ideas get sent to the advisor every day and morph over time based on clients’ behavior, he says.

Next year, the firm wants to launch another program in which it uses natural language processing to understand human questions, the way the Amazon Echo might, from a client conversation. “We have 40,000 something employees. We have knowledge about every single financial aspect of every market in the world. There is somebody somewhere who knows about trusts and estates in the state of Utah. How to dispose of a Monet you find in your attic to where do we think the long bond is going. Traditionally, that knowledge is built into a bunch of static PDFs and very hard to access.”

So the firm is collating that knowledge using artificial intelligence in the form of natural language processing and building bots for financial advisors, serving as intelligent assistants when clients ask advisors those questions. Advisors couldn’t and wouldn’t likely be experts in everything, after all. “If a client called and said my mom was just diagnosed with early-stage dementia, what should I be thinking about? Or my 2-year-old son has been diagnosed with autism.” The AI arms the advisor with the knowledge. “Because the truth is, there is a person at Morgan Stanley who can answer those questions.”

Picking Stocks

The company EquBot was founded to use AI to pick stocks for an ETF.

EquBot’s exchange-traded fund, the AI Powered Equity Fund (AIEQ) uses machine learning as part of its portfolio selection using IBM Watson and Google DeepMind. One of the ways it learns is to read databases full of newspaper articles to see how companies perform in different environments.

“Each day,” says its prospectus, “the EquBot model ranks each company based on the probability of the company benefiting from current economic conditions, trends, and world events and identifies approximately 30 to 70 companies with the greatest potential over the next 12 months for appreciation and weights those companies to seek a level of volatility comparable to that of the broader U.S. equity market.” Humans then rebalance the portfolio.

By picking the best mix of stocks for the current environment, based on performance and risk, it’s not wrong to compare it to the shifting baseball teams in Moneyball, say its managers. The algorithm learns to put words like “steel tariffs” in context to decide whose ox gets gored by them.