“There’s been a lot of layoffs,” said David Foote, principal analyst at IT research firm Foote Partners. “Companies are identifying people who were solid employees in the past but who are not suited to the new, technology-driven world they’re investing in.” Foote believes that between 20% and 25% of tech jobs could eventually be replaced by AI.
According to Foote’s research, AI will increase productivity by reducing or eliminating human intervention in some areas, while retraining experts to adapt to more strategic and creative roles.
In a similar vein, a June survey of CFOs by Duke University and the Federal Reserve Banks of Atlanta and Richmond found that 32% of companies plan to use AI to perform human tasks in the next year. And by the first half of 2024, nearly 60% of companies (84% of large companies) said they had deployed software, equipment or technology to automate tasks previously performed by humans.
According to the survey’s academic director, Duke University finance professor John Graham, companies are using AI to automate a wide range of business processes, including supplier payments, invoicing, procurement, financial reporting, and optimizing facilities utilization. “This is happening in companies that are using ChatGPT to generate creative ideas and draft job descriptions, contracts, marketing plans, and press releases,” Graham wrote in the report.
In particular, Foote said that 11 IT-related jobs will be affected by AI adoption in the coming years, some in a positive way and some in a negative way, although some believe the number could be higher.
IT Jobs Most Affected by AI
Roles that are expected to be heavily impacted by AI, but won’t necessarily disappear, include software development, cybersecurity, DevOps, UI/UX design, data management and governance, testing and quality assurance, data scientists and analysts, testing and quality assurance, cloud engineers, technical writers, IT support and systems administration, including network management. Ironically, Foote added, AI/ML engineering is also becoming more automated, with tools like Google’s AutoML.
Database management is also changing as AI-based systems, such as autonomous databases like Oracle Autonomous Database, self-patch, self-tune, and handle much of the database maintenance that used to require human intervention. Big data expertise will become increasingly important for traditional administrators.
AI is revolutionizing cybersecurity by automating threat detection, anomaly detection, and incident response. “AI-based tools can quickly identify anomalous behavior, analyze security patterns, scan for vulnerabilities, and even predict cyberattacks, reducing the need for manual monitoring,” Foote said. “In particular, as cybercriminals begin to use AI to attack systems, security professionals will increasingly focus on developing AI models that can defend against complex threats. There will also be an increasing demand for AI ethics experts in cybersecurity who can ensure that AI systems used for security are not biased or misused.”
IT support and systems administration jobs, especially Tier 1 and 2 help desk jobs, are expected to be hit particularly hard by job losses. These jobs involve basic IT troubleshooting and service desk provision, as well as technical support such as software updates, which can now be automated with AI. The remaining help desk jobs require more hands-on skills that cannot be handled by phone or electronic message.
On the other hand, while demand for data scientists and analysts will increase due to AI, their work will shift to more strategic areas such as interpreting AI-generated insights, ensuring ethical use of AI, and developing and validating higher-level models, Foote explains. “They will need to focus on building models rather than simply analyzing data. This includes ensuring that models are ethical, fair, and explainable, especially when making decisions in sensitive areas such as healthcare or finance. Data scientists will also need to have expertise in their own industries, such as healthcare or finance, to ensure that AI models meet business objectives and regulatory requirements.”
He added that there will also be an increased demand for data scientists equipped with model selection and optimization tools such as AutoML, DataRobot, and H2O.ai that automate much of the machine learning pipeline, from data preparation, processing, and analysis to model creation and deployment.
Unlike humans, generative AI tools can sift through vast amounts of data much faster than a human technician can, making it much easier for automated tools to identify problems, says Jack Gold, principal analyst at J. Gold Associates.
While layoffs at tech companies have increased over the past year, Foote expects companies to begin rethinking their hiring strategies. There could be a surge in hiring for a while, he explains, as “automation has ultimately led to people being let go, but they’ve decided that soft skills and institutional knowledge are important.”
Technology can’t create new product ideas, services or business strategies; those tasks require critical thinking. “Management thought they could just get rid of people, but it turns out they need key people who understand nuance,” Foote says. “Companies need people who know how to communicate in a collaborative way, using verbal and nonverbal skills, but who don’t necessarily have to have some level of technical ability. They’re the ones who can inspire and motivate others.”
Gold agrees. While AI will replace some software developers who focus primarily on routine or repetitive tasks, humans will still be needed to define programs and set parameters. “As software engineers become more productive and can write more code, there may be some reduction in the need to hire software people,” Gold says. “But I don’t think the need will go away completely.”
Both Gold and Foote believe that quality control will still require human intervention, as was the case with the recent CrowdStrike incident, which admitted to deploying a faulty software update to Windows computers through an automated process, causing a chain reaction of crashes that affected businesses around the world. “Remember, AI is only as good as the data set it is trained on,” Gold advises.
The Job Landscape Is Changing with the Spread of Generative AI
Generative AI will also create new jobs. For example, new tools and machine learning techniques will need to be integrated with existing enterprise systems, requiring technicians who are familiar with both. Integration is something that companies are working hard on.
Investment bank Goldman Sachs estimated last year that 300 million jobs in the US and Europe would be affected by the rise of AI. It predicted that two-thirds of US jobs could be automated, and that one in four current tasks could be fully automated. The Goldman Sachs report also said that AI is expected to increase global GDP by 7%.
The occupations most exposed to automation were management (46%) and legal professionals (44%). The occupations expected to be less affected were, not surprisingly, those that are more physically demanding, such as construction (6%) and maintenance (4%). Automation is expected to change a wide range of occupations, including IT, but not all occupations will be affected equally. According to Goldman Sachs, one reason the legal sector scored so high is because paralegals are more likely to be at risk than lawyers.
As many jobs around the world are being affected by AI and machine learning, hiring managers will be looking for candidates with experience in these areas. For example, one recent study found that programmers can more than double the number of projects they complete each week by using AI-assisted code generation tools.
Such tools are becoming increasingly prevalent in software engineering, and adoption is rapidly increasing, perhaps surprisingly, in most organizations experimenting with generative AI. This is because even if the automation tool only suggests the basic code for a new application, it can save time spent manually creating and updating code. Tools like GitHub Copilot, Tapnine, and OpenAI Codex can suggest lines of code, fix bugs, and automate code reviews, significantly reducing the burden of repetitive coding tasks for developers.
Following this trend, Amazon Web Services CEO Matt Garman recently said, “In 24 months or so, the majority of developers will likely not be coding.”
The effect of augmenting manpower rather than replacing it
While some fear the complete displacement of software developers, others believe generative AI automation will free up developers and other technologists to do more creative work instead of focusing on routine or repetitive tasks.
Thiago Cardoso, senior product manager at AI-powered content management company Hyland Software, believes generative AI tools should be used to accelerate programming and coding skills, not replace them. Cardoso cited estimates from the U.S. Bureau of Labor Statistics that jobs for software developers will grow 25 percent between 2021 and 2031.
“While these numbers confirm the demand and need for programming skills, comfort using AI to assist with coding will be a skill employers are looking for,” says Kadoso. “Developers should keep an eye on upskilling opportunities and identify which AI tools can assist with tasks like debugging and bug fixing, and improve code quality with preemptive refactoring, so they can focus on honing skills that AI systems cannot perform.”
“Employers will also look for developers who are open and able to adapt to the changing technology market. Developers who embrace this change and find ways to enhance their skills to keep pace with AI innovations will be the most valuable talent as the role continues to evolve,” he added.
Despite the widespread adoption of generative AI, the U.S. economy will have created more than 158 million jobs by 2024, and technological unemployment will be at an all-time low. “There are more optimistic assessments that AI will augment the least skilled workers rather than replace them,” says Philip Carlson-Zlzak, Boston Consulting Group’s global chief economist. “On the other hand, there are also arguments that replacing humans is harder than it sounds, because jobs are a collection of tasks, and AI can’t do them all perfectly.”
Gold also thinks estimates of how many jobs generative AI will ultimately eliminate are overstated. A more likely scenario is that employees will be so productive that companies won’t need to hire as many people. “It could give companies the opportunity to shift their workforce to more strategic tasks,” Gold says. “I don’t think we’ll see actual job losses for another two or three years, because there’s still a lot of debugging to make AI programs more responsive, effective, and efficient. It’s not as easy as people think.”
editor@itworld.co.kr
Source: www.itworld.co.kr
