The finance industry once seemed to be an exclusively human domain. While automation, highly-functional machinery, and robots slowly replaced the roles of people in industries concerned with the production of physical goods, employees in the service industry and the financial sector seemed infallible and irreplaceable.

With the exponential growth of interest and investments in tech firms and startups in recent decades, the pace automation has also risen. As tech firms compete to develop newer and more advanced products, the relentless march of technology encroaches upon even the most sophisticated tasks. Tasks that were once reserved for humans and considered outside the capabilities of machines are now falling under the domain of better software, higher-quality hardware, and smarter artificial intelligence programs.

Financial services are no longer immune to the increasingly pervasive spread of automation. Despite the overwhelming variety of services offered by the financial industry, different aspects of automation — software, algorithms, and artificial intelligence — are slowly but surely making appearances in all areas of finance, from retail banking to institutional trading to wealth management.

Case in point: according to a March 2016 report by Citi GPS: Global Perspectives and Solutions, increasing automation has a reductive effect on the value of physical branches of retail banking. “The return on having a physical network is diminishing,” the report noted. Instead, the role of retail banking in the future will center around advisory and consultation services, instead of transactions or physical storage of assets. This is due primarily to automation: the report states that the retail banking sector has seen an annual 2% reduction in staff. This number could easily rise, however, as staffing comprises the largest portion of retail banking costs. By 2025, the report predicts, “there could be another 30% reduction in staff.”

While employee cuts in retail banking may be the most visible and tangible result of increasing automation, software applications and developments in artificial intelligence impact higher-finance institutions as well, from the corporate structures of hedge funds to specific desks and services in investment banks.

Just last week, Goldman Sachs, a leading bulge bracket investment bank, posted a job listing on its company website for a “Digital Experience Developer” for its Goldman Sachs Asset Management (GSAM) division. According to the job listing, the role of the developer would be to build an “Automated Digital Advice Platform (Robo Advisor)” that would be able to take on advisory roles for GSAM clients. The Robo Advisor would have sufficient software and artificial intelligence capabilities to develop and implement integrated wealth management plans for clients, whether they be institutions or high net-worth individuals. With this move, Goldman Sachs has effectively embraced the growing presence of automation within the financial industry.

The planned development of GSAM’s Robo Advisor has ambiguous implications for various groups of people, most notably those whose employment may be adversely affected by its existence, and also those who would interact with it as clients. Despite the fact that software would be programmed by the most qualified developers and equipped with the most sophisticated trading algorithms and models, how comfortable would institutional representatives and high net-worth individuals be with entrusting their assets and wealth to artificial intelligence? Markets are fickle and easily affected by events that are tinted with human elements. How likely is it that a machine would be able to foresee and react appropriately in a way that is both protective of and advantageous to the wealth that it is supposed to manage?

Moreover, what will happen to the myriad financial advisors, asset managers, and private wealth managers whose services GSAM’s Robo Advisor is intended to emulate and improve upon? It isn’t difficult to envision a world in which asset management is performed entirely by software and artificial intelligence. As lucrative and engaging career options, financial advisory services and asset/private wealth management have long been viewed as desirable post-graduation employment outlets. Many college students, especially those who are serious about entering into financial services, choose to major in economics or other business-related areas of study in order to prepare for their career. With automation making a move on the long-term viability of certain careers in finance, this is likely to change.

With automated programs, software, and artificial intelligence taking on increasingly large roles within the financial sector and all parts of the economy, computer science may become the major of choice for college students, especially those who are considering careers in finance. Indeed, computer science has been one of the three most popular majors at Princeton University for several years now, and it looks as if it will soon overtake economics in the number of concentrators in the department. In the 2015-2016 school year, there were 244 and 245 upperclassmen in Princeton’s computer science and economics departments, respectively. Although not all computer science majors will go into finance, it is becoming an increasingly viable career direction for computer science graduates.

One relatively new area of finance that demands advanced knowledge of coding and programming is algorithmic trading, a system of exceptionally fast-paced, high-volume trading performed by complex algorithms in fast computers. Knowing how to apply computer science to complex mathematical models in order to program effective, high-return algorithms is invaluable to algorithmic trading, or algo-trading, as denizens of Wall Street refer to it.  This thus renders  a background in computer science that much more advantageous. The rise of this method of trading and its associated human roles, algorithmic traders and quants, explains a portion of the shift in popularity from economics to computer science as a college major.

Regardless of the strength of one’s knowledge of accounting, markets, or computer science, the likelihood of one’s career in financial services being affected by automation is increasing exponentially. This is especially true for the 1,700 employees of Bridgewater Associates, one of the world’s largest hedge funds. In December 2016, the $150 billion hedge fund announced that it would be developing and implementing a new artificial intelligence program that would take over the strategic hiring, firing, and day-to-day decisions of the firm. The program is founder Ray Dalio’s vision for the hedge fund in his absence: an artificial intelligence that would run Bridgewater Associates in the same way as Dalio himself would, but without the need for his presence at the firm. Dalio’s goal for the automation of its management is to have three-quarters of management decisions made by the artificial management intelligence within five years, according to The Guardian.

Is the fast-growing role of software and artificial intelligence in financial services a cause for concern for those who are reliant upon the industry for careers? In the case of management, the Harvard Business Review believes managers whose roles may be supplanted by artificial intelligence softwares have little to worry about. Although AI may be cheaper, faster, and more consistent in making management decisions, human managers will always be necessary: “It just means that their jobs will change to focus on things only humans can do.”

In more finance-specific areas of the industry, however, the future is uncertain. The same logic regarding management and AI may be applied to very human-centric financial services, such as sales or traditional investment banking, as jobs requiring face-to-face human interaction and softer skills are more difficult to code into an AI. Other areas of finance, however, may not be so resistant to automation, as in the cases of asset/wealth management or high-volume trading by investment banks. Whether this means that more college students will focus on computer science in an attempt to gain an edge when entering the financial sector or that they will increasingly turn to other career areas altogether remains to be seen. Above all, one thing is undeniable: automation is steadily increasing in pace, and is impacting even the industries that seem least likely to be automated.