Anyone who’s visited the New York Stock Exchange lately knows technology has already taken a toll on Wall Street jobs.

And the decimation is only going to continue as the artificial intelligence industry booms.

By 2025, AI technologies will reduce employees in the capital markets worldwide by 230,000 people, according to a report from Opimas that came out last week. Financial institutions may see a 28% improvement in their cost-to-income ratios.

Additionally, financial firms will spend more than $1.5 billion this year on AI-related technologies and $2.8 billion annually by 2021, not including their investments in AI startups, the Opimas report estimated.

It’s clear that AI will change Wall Street, but it is probably too simple to merely attribute the change to the promises of AI. Instead, it is several technologies that fall under the broader umbrella of artificial intelligence that are attacking the industry from all sides.

Process-oriented jobs are being killed by robotic process automation, a lower-IQ form of AI in which small pieces of software are programmed to do simple tasks, like looking up a document or a piece of information.

More analytical jobs are being replaced with things like machine learning, deep learning and the like that can digest large volumes of real-time data quickly and learn to find telling patterns with a speed the human brain can’t match.

This has implications for jobs all over capital markets, from the front office to risk, fraud and even HR. And it will create some new jobs — though not entry-level ones.

“AI is going to touch every aspect of jobs in the capital markets,” said Ed Donner, co-founder and CEO of untapt, a startup that presented at the last Accenture fintech demo day and that uses deep learning to match tech job candidates to the right positions. “It’s not just support functions, it’s not just operations; it’s also the front office. And retail banking and private wealth management are affected as well.”

Some of this is buzz, for sure, but AI’s boom is due to the convergence of several trends: costs associated with the advanced computing and data-storage hardware behind AI have come down. It’s now possible to feed AI engines the massive amounts of data they need to learn to do the job of people. And major vendors have all come out with products that can work with existing technology, rather than requiring systems to be ripped out.

Quieter front office

Front-office sales and trading jobs have already dropped, partly because so many firms use algorithmic trading. There’s been a 20% to 30% headcount reduction overall in the front office over the past few years, said David Weiss, senior analyst at Aite Group.

“Trade floors are a shadow of their former selves," and "market making and high-touch trading now employ fewer people,” Weiss said.

This trend will accelerate as AI advances.

“Natural language processing is helping to gain a greater understanding of conversations people are having, the intent of conversations in the front office,” said Terry Roche, head of fintech research at the TABB Group. “And mining data to gain greater insight to what’s happening” so it can give sales traders alerts about investment opportunities for their clients.

Analysts and researchers in the front office are being replaced by AI that can monitor vast arrays of data sources in real time, detect signals and put together analyst reports, Donner noted. The startup Kensho, in which Goldman Sachs has invested, is one example. A smaller startup called Agolo is another.

Emptying middle and back offices

Many jobs have been lost in middle and back offices, because those areas tend to be loaded with processes that are connected by human manual intervention, said Axel Pierron, managing director at Opimas.

“What AI brings there is the ability to do handwriting recognition and image recognition, as well as robotic process automation,” he said. “We’re already seeing the huge efficiency gains that AI can provide to the industry.”

AI is also making a dent in compliance staff.

“Compliance went on a huge hiring spree over the past several years in response to global regulatory mandates and regional enforcement actions,” Weiss said. “Artificial intelligence tech is being deployed to get a better holistic view as well as finally reduce false-positives — in ways that more bodies failed to. So that is the next area for attrition and reduced staffing needs.”

That trend on the sell-side could occur over the next two to five years, Weiss added.

IBM has fed the contents of the Dodd-Frank Act into its "Jeopardy!"-winning AI machine, Watson. It bought regulatory compliance firm Promontory and wants Watson to imbibe the firm’s experts’ knowledge. The startup Quarule is also working on AI for financial compliance.

Asset management firms first

Employees at asset management firms are especially vulnerable, Pierron said.

“You have a combined effect of the trend toward exchange-traded funds and self-investment, so it becomes harder to justify the management fee. There is already that tendency toward automating and robo-trading,” he said. “AI will complement that.”

The success of robo-advisers like Wealthfront and Betterment, of course, has been one driver of this change.

But the change is also coming from within, Pierron said.

“If you look at hedge fund ROI over the past 10 years, most of the industry has been below the S&P 500, which means there is already a high level of questioning around the added value provided by a human doing a trade themselves, using their gut feeling,” he said. “Here we already have the right mindset to implement AI and it’s already being implemented.”

The hedge-fund manager Steve Cohen, whose SAC Capital pleaded guilty to insider trading in December, is said to be hoping to replace people with AI machines at his new firm, Point72 Asset Management.

According to Bloomberg, the firm, which manages Cohen’s personal fortune of $11 billion, is parsing data from its portfolio managers and testing models that mimic their trades.

AI is also being used to watch human traders for signs of rogue behavior. Nasdaq has been doing this for some time on its exchanges. Firms are starting to deploy the technology to monitor market data, trader activity and trader communications simultaneously.

“It’s collecting data about the traders within your organization to create a profile of them, and if the trader breaks the profile of typical activity, that’s identified and flagged for greater analysis,” Roche said.

Where will the displaced find new jobs?

Where will all the laid off (or unhired) Wall Streeters go?

“That’s a really good question,” Roche said. “My son is going to be 18 in a month and he’s going off to college in autumn. I’m really thankful he’s going to study for a double major in IT management and supply-chain management.”

The shift away from entry-level jobs is happening everywhere, including in malls and fast-food restaurants, Roche noted.

“CaliBurger just deployed Flippy the robot, which cooks burgers,” he said. “Where are those jobs going to go? It’s a much broader societal question.”

Pierron pointed out that there will be a transition period — these jobs will not evaporate in one day.

“That’s a much broader discussion around the impact of AI in the industry, not just in capital markets but in our economy — we will have to think about what will be that next job creation,” he said. “With any natural evolution, you have the competencies that are becoming less relevant and you have core competencies and complementing competencies around AI.”

Where new jobs will be generated

Vendors that offer robotic process automation and machine and deep learning software will be able to add AI-related jobs, as will the value-added resellers and consulting firms that implement and maintain the technology.

Within Wall Street firms, three categories of new skill sets will become more important, according to Donner: software engineering, data science, and a hybrid of business and digital skills.

This last category “is someone who’s reporting into the business and knows about the business but also wears a digital hat and knows what it takes to make their business increasingly digital,” Donner said. “That kind of skill set is going to be more and more predominant in the coming year.”

He also sees jobs moving out of primary financial hubs like New York and into financial tech centers near tech schools.

“Goldman has a big tech center in Salt Lake City, JPMorgan has one in Houston and other places, Deutsche is in North Carolina,” he noted. “This shift is happening now and it will continue to happen over the next 10 years.”

From the Hathaway Effect to a flash crash

One danger of AI’s takeover of Wall Street is the chance that machine learning engines could misinterpret signals and make disastrous trades off them.

Such lapses already occur. There’s the so-called Hathaway Effect, in which the price of Berkshire Hathaway stock tends to bump up by 2% or so around the same time that Anne Hathaway is in the news, for instance when it was announced she was going to co-host the Academy Awards.

“It’s believed to be because of the number of AI programs finding signals, seeing the word ‘Hathaway’ and making incorrect deductions and trading decisions,” Donner said. “Hopefully they’ll get smarter and the Hathaway Effect will go away.”

Worries about what AI will do under different conditions has held some firms back from using it, Roche noted. So validating the machine thinking by running test and validation scenarios and putting restrictions and stops in place will be critical.

A broader danger is that misinterpreted signals could bring a whole market down.

Firms’ reliance on artificial intelligence systems “without human oversight could lead to multiple simultaneous identical reactions to adverse geopolitical or market conditions and greatly amplify them — think deeper, tech-induced flash crashes," said Weiss of Aite Group.

The Street will have to give careful thought to where it keeps some humans to watch the robots.

Editor at Large Penny Crosman welcomes feedback at penny.crosman@sourcemedia.com.