IT vs Data Science: Which Data Career Has a Better Future?

Introduction

Every year, thousands of students and working professionals face the same crossroads: should I build a career in Information Technology, or is Data Science the smarter long-term bet? The IT vs Data Science careers debate has never been more relevant than it is today, with both fields sitting at the epicentre of global digital transformation. Businesses across every industry from healthcare to finance to retail are rapidly investing in technology infrastructure and data-driven decision-making, creating enormous demand for skilled professionals in both domains.

But here is the key question that most career guides fail to answer directly: which path offers a genuinely better future when it comes to salary, job growth, career progression, and long-term relevance? According to the U.S. Bureau of Labor Statistics (BLS), the median annual wage for computer and information technology occupations as a whole was $105,990 in May 2024, with approximately 317,700 openings projected each year well above the national median of $49,500 for all occupations. At the same time, data science is rising fast, with projections that place it among the fastest-growing occupations in the entire economy. This blog breaks down the IT vs Data Science comparison across salaries, job growth, required skills, career progression, and future outlook so you can make a decision backed by data, not guesswork.

Understanding the Two Paths IT and Data Science

What Is an IT Career?

An Information Technology career covers a broad spectrum of roles focused on managing, maintaining, and securing an organisation’s technology systems. IT professionals keep the digital backbone of businesses running from managing networks and servers to overseeing cybersecurity, implementing software systems, and providing technical support. Common IT roles include network administrator, systems analyst, IT manager, cybersecurity analyst, cloud architect, and database administrator. IT is not a single job it is an entire ecosystem of specialisations that span every industry. Think of IT professionals as the engineers who build and maintain the roads that everyone else drives on.

What Is a Data Science Career?

A Data Science career, on the other hand, is focused on extracting meaningful insights from data. Data scientists use statistical analysis, machine learning, programming, and visualisation tools to turn raw data into actionable intelligence that drives business strategy. The role sits at the intersection of mathematics, computer science, and domain expertise. Common data science roles include data analyst, data scientist, machine learning engineer, business intelligence analyst, and AI researcher. If IT professionals build the roads, data scientists are the ones analysing traffic patterns to decide where new highways should go.

Salary Comparison Which Pays More?

Salary is often the first factor people consider, and the comparison here is revealing. Both fields pay significantly above the national average, but there are meaningful differences depending on the specific role and level of experience.

On the IT side, salaries vary considerably by specialisation. Network and computer systems administrators earned a median annual wage of $96,800 in May 2024. Computer systems analysts earned a median of $103,790 in May 2024. At the senior end, computer and information systems managers, the most senior IT leadership role earned a median annual wage of $171,200 in May 2024.

For data science, the median annual wage for data scientists was $112,590 in May 2024, with the lowest 10 percent earning under $63,650 and the highest 10 percent earning more than $194,410. The high earning ceiling in data science, particularly for senior and specialised roles in AI and machine learning, gives it a notable salary edge at the top of the career ladder.

The verdict on salary: IT offers a wider range depending on specialisation, with senior IT managers commanding extremely high wages. Data science, however, delivers strong earnings even at the mid-level and has an impressive earning ceiling for specialists in AI and machine learning.

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Job Growth Where Is Demand Heading?

This is where the two fields start to diverge noticeably and where the future of data careers becomes clearest.

On the IT side, growth varies significantly by role. Information security analysts are projected to see employment growth of 28.5 percent from 2024 to 2034, making it the fastest-growing computer occupation and fifth-fastest growing occupation overall. However, not all IT roles share this optimism. Employment of network and computer systems administrators is actually projected to decline 4 percent from 2024 to 2034, partly due to automation and cloud computing reducing the need for on-premise network management. 

Data science tells a far more consistent growth story. Data scientists are projected to experience a 33.5 percent increase in employment between 2024 and 2034, making it the fastest-growing mathematical science occupation and the fourth-fastest growing occupation overall in the U.S. economy. The BLS attributes this growth to the increasing demand to build AI models, conduct data analysis, and integrate data-driven applications into business practices across industries. (Source: BLS)

The data is clear: while certain IT specialisations like cybersecurity are booming, the data science career future shows broader, more consistent upward momentum as an entire field.

Skills Required Are You Cut Out for Either?

Core IT Skills

A strong IT career path is built on technical expertise in infrastructure, systems, and security. Core skills include network configuration and management, cloud platforms such as AWS and Azure, operating systems like Linux and Windows Server, cybersecurity frameworks, database administration, and IT project management. Certifications like CompTIA Security+, Cisco CCNA, and Microsoft Azure Administrator carry significant weight in the hiring process and help IT professionals demonstrate verified competence to employers.

Core Data Science Skills

Data science demands a different but equally rigorous skill set. Proficiency in Python and R for data manipulation and statistical analysis is foundational. SQL is essential for working with structured data. Machine learning frameworks like TensorFlow and Scikit-learn are increasingly standard for senior roles. Data visualisation tools such as Tableau and Power BI help communicate findings to non-technical stakeholders. Equally important is statistical thinking, the ability to design experiments, test hypotheses, and interpret results with rigour.

Career Progression: Where Do These Paths Lead?

Both paths offer clear upward mobility, but the trajectories look different. In IT, career progression typically moves from support and administration roles toward systems architecture, IT management, and ultimately to Chief Information Officer (CIO) or Chief Technology Officer (CTO) roles. At the senior level, computer and information systems managers overseeing IT departments earned a median annual wage of $171,200 in May 2024, with projected employment growth of 15 percent through 2034. The IT professional career path is well-established and rewarded handsomely at its peak.

In data science, career progression moves from data analyst through to senior data scientist, analytics manager, and ultimately to roles like Chief Data Officer (CDO) or Head of AI. As organisations continue to integrate AI and machine learning into their core operations, the demand for experienced data leadership is growing faster than the talent supply which works strongly in favour of professionals who invest in this path early. The crossover opportunities between both fields are also significant: IT professionals with data skills can transition into data engineering or analytics roles, making the two paths more complementary than competitive.

Which Career Offers a Better Future?

The honest answer is that both careers offer a strong future but data science is growing faster, with a higher ceiling for specialised earnings, and is more directly aligned with where businesses are heading in the AI era. Computer and mathematical occupations which include data science are projected to grow 10.1 percent, the second fastest of any occupational group, more than three times the overall average growth rate for the economy. 

That said, IT remains indispensable. Every data science operation runs on IT infrastructure. Cybersecurity, cloud computing, and systems management are not going away; they are evolving. The best tech career choice depends not only on market projections but also on your natural strengths, interests, and how you like to work. If you enjoy hands-on system management and keeping technology running reliably, IT is a deeply rewarding and well-paying path. If you are drawn to patterns in data, strategic problem-solving, and working at the frontier of AI and machine learning, data science offers an extraordinary future.

How Career Plan B Helps

Choosing between an IT and a Data Science career path is a decision that deserves more than a Google search. Career Plan B offers personalised career counselling, Psycheintel-powered career assessment tests, and structured career roadmapping to help you evaluate your strengths and align them with the right tech career. Whether you are a student, a working professional, or a recent graduate, Career Plan B gives you the clarity to choose with confidence.

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Frequently Asked Questions (FAQs)

1. Is Data Science better than IT as a career choice?

Both are strong careers, but they serve different strengths and interests. Data science offers a faster projected growth rate and high earnings in AI-related specialisations. IT offers broader stability, diverse specialisations, and very high senior-level salaries particularly in IT management and cybersecurity.

2. Which field pays more IT or Data Science?

At the mid-level, data scientists earn slightly more. Data scientists had a median annual wage of $112,590 in May 2024. However, at the senior level, IT systems managers earned a median of $171,200 in May 2024 among the highest in the tech sector. The earning potential of both fields ultimately depends on specialisation and experience level.

3. Are any IT roles declining in demand?

Yes, some traditional IT roles are being affected by automation and cloud computing. Employment of network and computer systems administrators is projected to decline 4 percent from 2024 to 2034 according to the BLS. However, high-growth IT specialisations like cybersecurity are more than compensating for these declines.

4. Can IT professionals transition into Data Science?

Absolutely. IT professionals have a strong technical foundation particularly in programming, databases, and systems thinking that translates well into data science. Upskilling in Python, statistics, and machine learning is the most common bridge between the two fields.

5. What is the fastest-growing role across both fields?

Data scientists rank as the fourth-fastest growing occupation in the entire U.S. economy, with a projected 33.5 percent employment increase from 2024 to 2034. On the IT side, information security analysts hold the title of the fastest-growing computer occupation, with projected growth of 28.5 percent over the same period. 

Conclusion

The IT vs Data Science careers debate does not have a single winner it has two different paths suited to two different kinds of professionals. Data science is growing faster, pays strongly across experience levels, and is increasingly aligned with the AI-driven future of business. IT remains foundational, lucrative at its senior levels, and critical to every organisation that runs on technology which is every organisation.

The smartest move is not to follow the trend blindly but to understand which path aligns with your strengths and long-term goals. Both careers offer stability, strong earnings, and genuine impact. The one that offers you a better future is the one you are genuinely built for.

Start with clarity. Visit Career Plan B today and book a free session to map out your ideal tech career path with expert guidance and assessment tools that go far deeper than a comparison blog ever can.