If you've spent any time reading technology news lately, you've probably seen some version of the same question:
Is AI going to replace IT jobs?
It's an understandable concern. Artificial intelligence can write code, troubleshoot problems, analyze data, automate routine tasks, generate documentation, and accomplish in seconds work that once took considerably longer.
But there's a big difference between AI changing the way IT professionals work and AI eliminating the need for IT professionals altogether.
We're already beginning to see that distinction play out.
AI is undoubtedly reshaping technology careers. Some tasks will become automated, some jobs will change, and IT professionals will need to keep learning. But AI also creates new infrastructure, security, networking, governance, troubleshooting, and technical challenges.
In other words, the technology getting smarter doesn't make technical knowledge irrelevant.
It may make that knowledge even more important.
It's worth being realistic about what is happening.
AI is going to automate certain tasks. Some organizations will restructure positions around it. Professionals who learn how to work effectively with AI may be able to accomplish more than they could before.
But businesses still need people who understand the systems AI depends on.
AI applications don't exist in a vacuum. They rely on networks, servers, cloud infrastructure, operating systems, data, access controls, cybersecurity, hardware, and people who know how those technologies work together.
They also create new problems to solve.
Who secures an AI-connected environment? Who determines whether an automated action is safe? Who troubleshoots the network when an AI service can't connect? Who manages permissions? Who investigates suspicious activity? Who configures infrastructure? Who determines whether the AI's answer is actually correct?
AI can be a powerful tool.
Someone still needs to understand the technology behind it.
The numbers are more encouraging than some of the headlines suggest.
In 2026, the U.S. Bureau of Labor Statistics specifically examined artificial intelligence, information technology, and employment. Even as AI adoption increases, BLS projects substantial growth in several technology-related occupations between 2024 and 2034.
Employment for information security analysts is projected to grow 28.5%, while software developer employment is projected to grow 15.8%, representing more than 267,000 additional software developer positions.
The Linux Foundation's 2026 State of Tech Talent Report found something equally interesting: among organizations surveyed, AI was producing a positive net effect on technical hiring, not simply eliminating technical positions.
Nearly half of surveyed organizations reported growing their technical workforce in response to AI-related demand.
That's an important distinction.
AI may reduce the amount of time required for certain tasks while simultaneously increasing the need for professionals who can deploy, secure, integrate, manage, and troubleshoot increasingly sophisticated technology.
The first few years of widespread generative AI adoption produced plenty of ambitious predictions about replacing workers with automation.
Now we're beginning to see what happens when those ideas meet real-world operations.
In 2026, Reuters reported that Meta had explored an ambitious workforce transformation that would use AI to enable much smaller teams and potentially reduce some teams significantly.
The plan didn't unfold as expected.
According to Reuters, internal AI agents and coding tools created reliability and security concerns and didn't improve employee productivity as much as anticipated. Meta ultimately scaled back the initiative and canceled a planned additional round of restructuring.
The lesson isn't that Meta stopped investing in AI. Far from it.
The more interesting lesson is that AI investment and human technical expertise aren't mutually exclusive.
Giving people powerful AI tools doesn't automatically eliminate the need for people who understand complex systems, recognize when something has gone wrong, and know how to fix it.
Klarna provides another useful example outside of traditional IT departments.
The financial technology company gained considerable attention after saying its AI customer-service system could perform work equivalent to hundreds of agents. But the company's approach eventually shifted.
CEO Sebastian Siemiatkowski acknowledged that the company's focus on cost had contributed to lower service quality, and Klarna began putting greater emphasis on human customer service again.
Klarna didn't abandon AI.
Instead, it learned something many organizations are likely to discover: the best answer isn't always humans or AI. Sometimes it's humans working with AI.
And that's an important distinction for anyone thinking about the future of work.
One area where the case for skilled professionals is particularly strong is cybersecurity.
More AI means more technology interacting with sensitive systems and information. Organizations have to think about access controls, vulnerabilities, data protection, identity, cloud security, network security, AI-generated threats, automated attacks, and what happens when an AI system behaves in an unexpected way.
That creates an interesting reality:
The more powerful our technology becomes, the more important it becomes to secure it.
BLS currently projects employment for information security analysts to grow 28.5% from 2024 to 2034, considerably faster than overall employment growth.
For professionals considering cybersecurity, AI isn't necessarily a reason to avoid the field.
It may be one of the reasons to enter it.
The value of IT certifications isn't disappearing either.
In fact, employers appear to be placing significant value on validated skills as technology changes.
Pearson's 2026 Value of IT Certification Employer Report found that 78% of employers identified professional certification as their leading investment for upskilling employees.
Even more telling, nine in ten employers surveyed expect certifications to become more important over the next three to five years.
Why?
Because having access to AI isn't the same thing as understanding IT.
An AI tool can suggest a network configuration. A networking professional still needs enough knowledge to recognize whether that configuration makes sense.
AI can recommend a security response. A cybersecurity professional needs to understand the consequences of implementing it.
AI can generate a troubleshooting procedure. A technician needs enough foundational knowledge to determine whether the recommendation actually fits the problem in front of them.
As AI makes information easier to access, the ability to understand, evaluate, and apply that information becomes increasingly valuable.
That's where technical knowledge—and the certifications that help validate it—still matter.
Not every IT certification serves the same purpose. But several certifications offered by CBT Campus cover skills that become particularly relevant as organizations adopt more AI-enabled technologies.
AI introduces new capabilities, but it also creates new security questions.
CompTIA Security+ builds foundational cybersecurity knowledge across threats, vulnerabilities, security architecture, security operations, identity and access management, risk, and related security concepts.
As AI becomes integrated into more business systems, professionals who understand how to protect users, devices, networks, applications, and data remain essential.
For someone interested in entering cybersecurity, Security+ can provide an important foundation for understanding the security environment surrounding both traditional and emerging technologies.
AI still needs a network.
Whether an organization is using cloud-based AI services, operating its own infrastructure, connecting users to applications, or moving enormous amounts of data, reliable and secure connectivity remains fundamental.
CompTIA Network+ provides a vendor-neutral networking foundation, while Cisco CCNA develops networking knowledge across areas such as network fundamentals, IP connectivity, network access, security fundamentals, automation, and programmability.
AI may increasingly help professionals configure and monitor networks, but understanding how networks actually work gives IT professionals the knowledge needed to evaluate, troubleshoot, secure, and improve those environments.
AI is also changing both sides of cybersecurity.
Attackers can use automation and AI to increase the speed and scale of malicious activity. At the same time, security teams are using increasingly sophisticated tools to identify unusual behavior and analyze enormous amounts of security information.
CompTIA CySA+ focuses on areas including security operations, vulnerability management, threat analysis, and incident response.
As security tools become more automated, professionals still need to interpret what those tools detect, investigate suspicious activity, determine what's actually happening, and decide how an organization should respond.
More technology also means more complexity.
For experienced cybersecurity professionals, CompTIA SecurityX and CISSP address advanced areas of security that require professionals to think beyond individual tools.
Security architecture, engineering, governance, risk, operations, identity, and enterprise security become particularly important when organizations are deciding how new technologies—including AI—should interact with critical systems and sensitive information.
AI can provide recommendations.
Experienced security professionals are still responsible for making informed decisions.
A tremendous amount of modern AI infrastructure depends on cloud computing.
CompTIA Cloud+ builds vendor-neutral knowledge related to cloud architecture, deployment, operations, security, networking, troubleshooting, and related infrastructure concepts.
As businesses continue moving workloads and services into cloud and hybrid environments, professionals who understand the infrastructure supporting those technologies can play an important role in keeping them available, secure, and functioning properly.
Linux quietly powers a significant amount of modern technology infrastructure.
Servers, cloud environments, containers, cybersecurity tools, development environments, and many AI-related systems rely heavily on Linux.
CompTIA Linux+ validates practical Linux administration skills across system management, security, scripting, containers, troubleshooting, and related areas.
AI can help write a command.
Knowing what that command actually does—and whether you should run it—is another skill entirely.
Even foundational IT skills still matter.
CompTIA A+ covers hardware, operating systems, networking, cybersecurity, cloud concepts, mobile devices, troubleshooting, and technical support.
AI may help a technician diagnose a problem faster, but someone still needs to understand the device, operating system, network, user environment, and potential solutions well enough to act on that information.
For people entering IT, building that foundation can make it easier to understand not only traditional technology but also the AI tools they'll increasingly encounter throughout their careers.
Perhaps the better question isn't:
“Will AI replace IT professionals?”
It's:
“What will successful IT professionals know how to do with AI?”
Research is already pointing in that direction.
PwC's 2026 AI Jobs Barometer found that skills are changing significantly faster in AI-exposed jobs. But it also found that companies achieving the greatest productivity gains from AI weren't simply using the technology to eliminate people. Headcount growth at highly AI-exposed companies was actually outpacing growth at less-exposed companies.
The work is changing.
IT professionals will increasingly use AI to help analyze information, automate repetitive tasks, troubleshoot problems, write scripts, monitor environments, identify threats, document systems, and work more efficiently.
That doesn't make technical expertise obsolete.
It changes what professionals can accomplish with that expertise.
It's reasonable to feel uncertain about what AI means for the future of work. Technology careers have always changed alongside the technology itself, and this particular shift is happening quickly.
But avoiding IT because AI exists may mean overlooking something important:
Someone has to build, connect, secure, maintain, troubleshoot, manage, and understand the increasingly complex technology environments AI is becoming part of.
The safest career strategy isn't pretending AI won't change anything.
It's continuing to learn.
Build strong IT fundamentals. Develop specialized skills. Learn how AI tools work within your field. Understand their strengths—and their limitations. And continue building knowledge that helps you recognize when technology isn't working the way it should.
AI is changing IT.
That's exactly why skilled IT professionals still matter.
CBT Campus has been providing professional IT certification training since 1991, helping students prepare for industry-recognized certifications and build skills for an IT industry that has never stopped evolving.
Our training options include certifications such as CompTIA A+, Network+, Security+, Cloud+, Linux+, CySA+, PenTest+, SecurityX, Cisco CCNA, CISSP, and more, with live virtual instructor-led, accelerated bootcamp, e-learning, and on-demand training options available depending on the course.
Whether you're taking your first step into IT or building more advanced cybersecurity, networking, cloud, or infrastructure skills, continuing to learn is one of the best ways to prepare for what's next.
Fill out the form below to connect with a CBT Campus Training Advisor and learn more about available certification courses, training formats, and upcoming schedules.
Prefer to speak with someone directly? Call CBT Campus at 1-877-872-4646.