Cybersecurity vs. AI Careers: A Comparative Analysis

The AI market is expected to grow significantly, reaching $1.3 trillion by 2030, up from an estimated $214 billion in 2024. And with new tools coming out to make AI easier to use, businesses need AI professionals to help them integrate it into their businesses.

This increased use of AI, however, is exposing businesses to new cyberthreats and cyberattacks. Cybersecurity is a crucial function in today's interconnected world, and the need for experts to stay up to date with their cybersecurity skills is greater than ever. As the number and types of cyberthreats increase, cybersecurity jobs are in high demand.

If you're debating cybersecurity or AI as a career, this guide will help you choose. You'll learn more about cybersecurity and AI careers and what you need to do to pursue them as career paths. You'll also discover how businesses use AI and cybersecurity and how you can develop the skills necessary to start your career.

Cybersecurity: protecting digital assets

Cybersecurity is a growing field that offers numerous opportunities because of the changing security landscape. Cybersecurity professionals help safeguard technology, data, and digital assets from cyberthreats—ensuring companies stay safe from data breaches, avoid losing sensitive data and information, and protect their reputations, productivity, and financial stability.

Threats can be anything from bad actors using deepfakes to common scams on social media. The cybersecurity threat landscape is broad, unpredictable, and constantly changing, which is why real-time threat detection, incident response, and continuous risk assessment are essential parts of any modern security strategy. Many skill sets are required for cybersecurity:

• Infrastructure development to guard against cyberthreats, including setting up firewalls, malware protection, cloud security systems, and other tools.
• Penetration testing to find vulnerabilities by staging mock attacks against a system.
• Real-time monitoring to identify attack patterns and adapt to them, often using threat detection systems.
• Planning skills for creating incident response plans for cybersecurity incidents.

Some of the roles you'll see for these different skills include:

• Penetration tester
• Cybersecurity analyst
• Security operations center (SOC) analyst 
• Network security administrator
• Security analyst

Artificial intelligence: innovation through data and automation

AI is a constantly evolving field with many new advancements, including natural language processing and human intelligence simulation, making it an exciting career path to explore. It's being applied across many industries, from patient analysis in health care to campaign development in marketing. 

The field offers various roles you can pursue depending on your interests, background, and abilities:

• Data scientists dive deep into data analytics to extract insights from patterns.
• Machine learning developers build AI algorithms that analyze big data to find patterns.
• Software engineers create applications for end users.
• Business intelligence developers analyze information from AI and make it available to the end user.
• Other common titles and roles include AI engineers, machine learning engineers, and research scientists.

AI engineers should know these key concepts:

• Machine learning trains algorithms to provide a desired output by running inputs through iterative processes until a statistically determined outcome is achieved.
• Deep learning uses artificial neural networks to identify complex patterns in text, sound, and images, much like human intelligence, simulating the iterative processes of human learning.
• Algorithms are the sets of instructions given to computers to complete tasks in areas of data science, data processing, and automated reasoning.

AI engineers need proficiency in key programming languages, with Java and Python being two of the most common. Additionally, AI professionals must understand cloud security and cloud computing, as much of AI uses big data processed on the cloud. Tools like Apache Hadoop help developers build infrastructure on cloud platforms.

AI vs. cybersecurity careers

AI and cybersecurity are both crucial components of the technology sector, touching many industries. However, the two roles have some important differences in their career paths.

Demand

As businesses continue to integrate digital technology and data into their workflows, the demand for both cybersecurity and AI professionals is likely to grow.

According to the Bureau of Labor Statistics (BLS), the demand for cybersecurity professionals is expected to grow by 33% between 2023 and 2033. This growth is much faster than other industries, which means there will be many opportunities for specialists to enter the field and contribute.

AI careers are showing signs of recovery after a recent slowdown. Job postings requiring AI expertise rose by 4% in Q1 2024 compared to the previous quarter, indicating a rebound in demand. Meanwhile, demand for generative AI skills surged by 38% in the first quarter of 2024 alone.

Salary and job growth

Professionals looking for cybersecurity and AI careers can expect good pay for their efforts. These growing fields require experts with deep knowledge to give companies an edge in the market and ensure they stay secure against attackers. Common examples include penetration testers, security operations center (SOC) analysts, AI engineers, machine learning engineers, and data scientists. 

The national average salary for a cybersecurity professional in the United States is $132,962. The low end of salaries starts at $57,000, while more advanced positions can reach $186,000 per year. These numbers may change based on your position and location.

The national average for AI engineers in the United States is $106,386. New AI engineers can see a salary of $44,000, while experienced engineers have salaries as high as $173,500.

Both AI and cybersecurity offer strong earning potential and long-term growth. The table below compares key data points to help professionals evaluate each path:

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*Based on BLS data for computer and information research scientists

Career paths in AI and cybersecurity

AI and cybersecurity professionals follow distinct career paths, with increasing overlap as the two fields converge. Below are some examples of common role progressions in each area:

• Cybersecurity career paths. Many professionals start in entry-level IT roles such as help-desk technician, network administrator, or IT technician, then move into specialized roles like penetration tester, cybersecurity technician, or security auditor. Advanced paths include cybersecurity engineer, vulnerability assessor, cybersecurity architect, and researcher roles.
• AI career paths. Entry-level positions often include data analyst, machine learning intern, or software developer. With experience, professionals can grow into roles like machine learning engineer, deep learning specialist, or DevOps engineer. Specialized roles may include robotics engineer, AI researcher, or solutions architect.
• Hybrid career paths. New roles are emerging at the intersection of AI and cybersecurity, such as AI security engineer, cybersecurity data scientist, and ML threat analyst. These professionals combine AI skills with security expertise to protect intelligent systems and build smarter defenses.

Success in either field requires the ability to break down complex systems, communicate clearly, and collaborate with teams—especially when working with stakeholders, regulators, or clients in high-risk environments.

Job security

For many job seekers deciding between cybersecurity and AI, job security is a key consideration. The good news is that both fields are seeing high demand, which means solid job security in both professions.

Cybersecurity offers strong job security due to the constant need for businesses to protect their data and computer systems from threats. Professionals can join in-house security teams at businesses or work for managed service companies that assist organizations without dedicated IT departments. As cybersecurity threats continue to grow, so does the demand for skilled cybersecurity experts.

AI has been part of the tech landscape for years, but the surge in generative AI and large language models (LLMs) is creating demand for new kinds of roles and skills, particularly in prompt engineering, model fine-tuning, and AI governance. Companies are increasingly collecting data and need AI specialists to analyze trends and improve decision-making and risk management. As AI becomes more integrated into various industries, demand for AI professionals is expected to rise, providing ample job security.

While both fields are evolving, cybersecurity roles are often seen as resistant to automation through AI technology, since they require human judgment, legal interpretation, and strategic planning for security measures. AI roles are likely to change rapidly as AI expands, which could increase the need for meta-skills like MLOps, auditing, and governance.

Education

Cybersecurity professionals typically start with a bachelor's degree in information technology or a related field. Practical experience setting up IT infrastructure is crucial, and specializations like cryptography, digital forensics, and ethical hacking are available at more advanced levels. 

AI professionals usually begin their journey with a bachelor's degree in computer science or a similar discipline. Many choose to deepen their knowledge with a master's degree, specializing in areas such as deep learning, neural networks, or computer vision. 

In addition to this foundational education, AI roles increasingly require knowledge of data privacy, responsible AI, and ethics, especially when AI models are trained on sensitive information like medical or financial records.

Best certifications for AI and cybersecurity

Certifications offer professionals a way to build specialized skills and demonstrate expertise in key areas. Some of the best options for those working in AI and cybersecurity include:

• CompTIA Security+ covers essential cybersecurity skills and is a strong starting point for building foundational knowledge.
• Certified Ethical Hacker (CEH) teaches hands-on hacking techniques to help professionals identify and fix system vulnerabilities.
• Certified Information Systems Auditor (CISA) is ideal for professionals responsible for auditing, control, and assurance of information systems.
• Certified Information Security Manager (CISM) is geared toward professionals in management roles, with a focus on governance and risk management.
• AI for Everyone from Coursera provides non-engineers with an accessible introduction to artificial intelligence concepts and applications.
• IBM AI Developer Professional Certificate offers project-based learning for AI developers looking to deepen their technical skills.
• Microsoft Certified: Azure AI Fundamentals is a strong entry point for DevOps engineers interested in building AI solutions on the Azure platform.

Future trends in AI and cybersecurity roles

AI is transforming cybersecurity careers, opening up new risks and opportunities. Here are some future trends likely to shape roles in this space:

• AI-powered threats will drive demand for defensive innovation. Cybercriminals will continue using AI to craft sophisticated attacks like personalized phishing, voice cloning, and new types of malware.
• Cybersecurity professionals will rely more on AI tools. Specialists will use AI to detect threats faster, analyze large datasets, and predict attacks using pattern recognition.
• Generative AI will expand into industry-specific roles. As generative models improve, new job functions will emerge in health care, logistics, retail, and manufacturing to secure AI-driven systems.
• AI-integrated systems will create more security roles. With AI embedded in business operations, demand will grow for professionals who can protect complex, data-rich environments.
• New vulnerabilities will reshape cybersecurity responsibilities. Threats like adversarial inputs and model bias will require professionals to understand and mitigate AI-specific risks.
• Cross-functional expertise will become essential. Organizations will seek talent with skills in both AI and cybersecurity to manage integrated systems and evolving threats.

AI is also reshaping cybersecurity. From real-time threat detection to automating incident response, machine learning algorithms are helping security teams reduce false positives, analyze network traffic, and respond faster to potential threats. Similarly, cybersecurity professionals are using AI to monitor user behavior, detect anomalies, and predict cyberattacks before they occur.

AI vs. cybersecurity

Both AI and cybersecurity can be rewarding careers that allow professionals to take on interesting and important problem-solving.

Security professionals will protect businesses from attacks, building the infrastructure to detect and stop threats and test networks for potential vulnerabilities. AI professionals are at the forefront of data analysis. They build tools and models to analyze large datasets to provide insights and perform tasks.

Both fields offer good pay, opportunities for growth, job security, an evolving job market, and interesting work.

If you own or operate a business that wants to hire a professional for one of these roles, browse Upwork's Talent Marketplace to search for AI professionals and cybersecurity freelancers.

If you're an independent professional looking for your next client, browse the available job listings for internet security and artificial intelligence.