In 2025, we’ve passed the point where technology is simply a tool, and tech isn’t just changing the world; it is the world now. From the way we work to how we entertain, learn, communicate, and rest (hello, sleep-tracking apps), everything’s moving to digital. With this, IT professions transform to serve the new reality. What used to be considered “tech” has morphed into fascinating roles.
Now, throw AI into the mix to get to the job market. According to the World Economic Forum’s “Future of Jobs Report“, by 2025, machines and algorithms will handle more than half of workplace tasks. To stay competitive and be better than AI, over 1 billion workers will need reskilling and upskilling. Now extend that logic into 2030, and you’ll see why the IT job market is exploding—with new roles being born just to keep up.
A McKinsey report even estimated that between 400 million and 800 million jobs could be automated by then. But the idea of AI replacing the human workforce doesn’t seem so scary because new technologies rapidly give birth to new jobs and new job categories. We’re not becoming useless—we’re becoming irreplaceable in new, exciting ways.
So, here’s where we’re headed. Let’s talk about the top IT professions that are not just surviving but thriving—and evolving.
AI and Machine Learning Engineers: From Prediction to Perception
In the early 2010s, AI and ML engineers worked on creating basic predictive models for business analytics. Today, AI engineers are building sophisticated neural networks for almost everything, from real-time language translation to autonomous vehicles and human writing. Even this article could have been written by an AI (but wasn’t, I promise).
With the technology, engineers are developing computer vision systems that can detect cancer in medical images and even predict cancer five years before the actual disease.
Next: By 2030, AI and ML engineers will be the top required specialists focused on general artificial intelligence applications that can transfer learning across domains.
Cybersecurity Analysts: From Firewalls to Global Threat Intelligence
In the early 2000s, cybersecurity was primarily reactive—installing antivirus software, configuring basic firewalls, and responding to obvious intrusion attempts. Their work was mostly invisible until something went wrong or until someone screamed in panic when a virus was detected.
Today’s cybersecurity analysts have gone far from their “roots.” They use SIEM tools to monitor networks in real-time, conduct threat-hunting operations, perform penetration testing, and develop incident response playbooks.
Next: By 2030, cybersecurity will become even more specialized, requiring more roles like quantum cryptography defenders, AI security specialists, supply chain security architects, and more.
Cloud Architects: From Physical Servers to Global Infrastructure
Before cloud computing, infrastructure engineers physically managed servers, running cables and managing hardware. Capacity planning or disaster recovery requires time and resources.
Today’s cloud architects design distributed systems and scalable infrastructure where entire environments can be deployed with a few lines of code.
Next: In the future, cloud architects will evolve into more strategic roles, such as multi-cloud orchestration engineers, edge computing architects, and sustainable cloud designers.
Data Scientists: From Excel to Productivity
For a long time, data science was about managing Excel sheets and creating reports.
Today’s data science is behind every business decision. Data scientists wear many hats – software engineers, mathematicians, and storytellers—to process information, ask the right questions, optimize supply chains, and so much more.
Next: In the future, data science will closely work with AI engineers to convert data insights into automated decision systems.
Blockchain Developers: Beyond Bitcoin and DeFi
When blockchain first started with Bitcoin in 2009, only a few cryptography enthusiasts were experimenting with the technology. We all know what happened with Bitcoin, and we also know how blockchain technology emerged.
Today’s blockchain developers are building applications far beyond digital currencies, for example, transparent voting systems or supply chain verification systems.
Next: By 2030, blockchain development will be more focused on DeFi security engineering, enterprise blockchain architecture, and tokenization. The sector still has a talent shortage, so developers are welcome to reskill.
AR and VR Developers: Building the Next Dimension
Early virtual reality was “not quite real” and limited, with high tool prices. Augmented reality was primarily limited to mobile apps, with poor object recognition and limited interaction.
Now, AR/VR developers are creating immersive experiences like surgical training simulators that reduce errors by 40%, architectural visualization tools that let clients walk through buildings before construction starts, and more.
In the future, we will see more VR supported by mixed reality environment architects and haptic feedback specialists.
Human-Machine Interaction Designers: Teaching Machines to ‘Get’ Us
Early human-computer interaction focused on switching a computer on and off. If seriously, designers took care of graphical user interfaces—buttons, menus, and windows. Interaction was limited to mouse clicks, keyboard input, and basic touch interfaces.
Today’s interaction designers work across multiple modalities—voice, gesture, and sight tracking—to create systems that adapt interfaces based on user behavior.
Next: Slowly, product designers may be called cognitive interface architects, emotional response engineers, or AI personality designers (or all of the above).
Robotics Engineers: Building Bodies for Brains
Before our children started learning robotics instead of building castles from sand, robotics engineers were people no one saw, but we knew they existed. Programming was complex, requiring specialized knowledge, and robots had minimal awareness of their surroundings.
Now, robotics engineers can create collaborative robots that work alongside humans, autonomous drones that inspect infrastructure, and robotic surgical assistants that perform precision procedures.
Next: By 2030, robotics engineering will need more soft robotics specialists, human-robot interaction psychologists, and robot ethical behavior programmers to ensure robots don’t take over the planet (just kidding, or not?).
Creative Strategist: Less Suits, More Strategy
Traditional creative directors and marketing strategists worked primarily with print, television, and early digital media. It took months to plan a campaign, and the results were measured mostly with “gut.”
Now, creative strategists live at the intersection of data analytics, cultural trending, and multimedia storytelling. They work with omnichannel experiences, analyze audience data, identify cultural trends, work with AI-powered design tools, and develop brand identity.
Next: By 2030, this role will evolve into and take on additional roles such as synthetic media director and narrative AI curator.
FinTech Engineers: Speed, Scale, Security
Financial technology mostly meant building basic online banking websites or developing trading platforms. Today’s fintech engineers are building secure peer-to-peer payment systems, biometric authentication, fraud detection algorithms, and more.
Next: As fintech is one of the most sensitive and critical sectors globally, it will require more professionals in financial inclusion, regulatory technology, and behavioral financial AI.
Coming Soon: Jobs That Aren’t Here—Yet
And a few more positions that haven’t officially arrived but are already taking shape and will be mainstream by 2030:
AI Ethicist
AI ethicists will be core members of product development teams certified to evaluate algorithmic impact, ensuring the trained model or software corresponds to regulations.
Digital Twin Analyst
A digital twin is a digital copy of a physical object or system used to simulate behavior. This strategy is used to test future products and systems before investing in actual production. Digital twin analysts will work across industries, creating virtual replicas of everything from supply chains to human organs, urban environments to agricultural systems.
Gartner predicts that by 2026, 60% of large enterprises will use digital twins to optimize business processes to reduce costs and environmental impact.
Machine Psychology Expert
A concept discussed in academic circles will soon study the “cognitive” processes of complex AI systems, developing frameworks to predict behavior, diagnose “reasoning” flaws, and map machine perception biases. These specialists will create tests for machine emotional intelligence and develop techniques to align AI cognition with human expectations.
The emergence of AI DO needs such experts to understand their internal “mental” processes for safety and trust.
Neuro-interface Developer
Probably the most futuristic (but as we can see, every crazy idea has become reality), neuro-interface developers will work on consumer-grade brain-computer interfaces for gaming, productivity, and communication. They’ll design “thought-to-text” systems and emotion detection algorithms.