With investors fleeing actively-managed hedge funds that charge high fees, BlackRock has plunged into an AI strategy that promises higher returns while reducing costs at the same time. This means installing capabilities to process all manner of alternative data while automating other processes to free human brainpower for the most important tasks.

Meghan Morris described how BlackRock is transforming how a hedge fund works through AI in this article from Business Insider:

The world’s largest asset manager is on a mission to automate and innovate through its growing artificial intelligence team.

BlackRock founded a Palo Alto, California-based group called AI Labs last year, directed by Stanford professor Stephen Boyd. Now, according to job postings reviewed by Business Insider, the 30-member team is tackling projects ranging from next-generation lending platforms to human task automation.

AI Labs is set up to work on new capabilities, from ideas through execution, at the $6.5 trillion asset manager. “There is a rich problem space for data scientists and engineers across all areas of the business including investments, sales, marketing, operations, product, [user experience], etc. and the potential to have large scale impact,” said one recent posting, for a senior data scientist.

Current projects include building a dynamic pricing and auto-bidding engine for the security lending business, a $1.7 trillion business that BlackRock’s been active in since 1981, according to promotional materials.

AI Labs’ staff is also working with alternative data sets to find useful signals. That’s been a conundrum across asset management as experts say the booming space has been difficult to generate incredible returns, despite seemingly new providers popping up daily.

In a blog post last year, Jody Kochansky, BlackRock’s chief engineer, highlighted some of the ways artificial intelligence techniques are already helping to sort through vast amounts of “messy data.” That helps investment professionals glean insights into areas including “the speed of construction in China, foot traffic into major department stores, and sentiment picked up from thousands of online employee reviews.”