Will Software and Tech Decide the Future of Jobs?

rtificial intelligence (AI), automation, and intelligent agents are transforming industries, raising critical questions about the future of work. Will software and tech decide the future of jobs? Are we taking the implications of AI seriously enough?

And with AI tools increasingly capable of writing code, why should anyone bother studying software engineering? These are urgent concerns, especially as we stand on the brink of a technological revolution.

In this post, we’ll explore the role of AI in shaping the job market, why society needs to prioritize the future of work, and why studying software engineering remains a smart and strategic choice.

How Software and Tech Are Shaping the Future of Jobs

There’s no doubt that software, AI, and automation are reshaping the job market in profound ways.

Here’s how:  

Automation of Repetitive Tasks: AI is taking over routine, rule-based tasks, from data entry and customer service to manufacturing and even basic software development tasks like writing boilerplate code.  

Augmentation of Skilled Work: Rather than replacing skilled professionals, AI is augmenting their work, boosting productivity. Software engineers use tools like GitHub Copilot to code faster, doctors leverage AI for diagnostics, and designers use AI to prototype ideas.  

Creation of New Jobs: While AI eliminates some roles, it also creates new ones. The rise of AI has led to demand for AI ethicists, machine learning engineers, data scientists, and prompt engineers.  

Transformation of Industries: Entire sectors—healthcare, education, transportation, finance—are being reshaped by AI, leading to new workflows, business models, and job categories.

However, the future of work isn’t solely determined by technology. Economic, social, and political factors, such as government policies, education systems, and societal attitudes toward reskilling, will play a crucial role in shaping outcomes.

Why Aren’t We Taking the Future of Work Seriously?

Despite the transformative potential of AI, there’s a perception that society isn’t taking the future of work seriously enough. Here’s why this perception exists—and what’s actually being done:  

Awareness vs. Action: Experts, governments, and organizations are discussing the future of work, but systemic changes are slow. Governments often lag in updating labor laws, education curricula, or social safety nets.

Companies prioritize short-term profits over long-term workforce planning, and traditional education systems emphasize outdated skills.  

Optimism Bias: Some leaders underestimate the speed and scale of AI-driven disruption, assuming humans will always remain essential in ways they currently are. This complacency can delay action.  

Uneven Focus: While tech hubs like Silicon Valley, Singapore, and parts of Europe are investing heavily in AI education and workforce development, other regions lag behind, creating disparities in preparedness.  

Public Awareness: The general public may not fully grasp AI’s implications due to a lack of accessible education or communication.

That said, efforts are underway. The World Economic Forum, OECD, and other organizations are publishing frameworks on the future of work.

Tech giants like Microsoft, Google, and Amazon offer free or low-cost training in AI and cloud computing.

Governments in countries like Finland, Singapore, and Canada are experimenting with policies like universal basic income (UBI) pilots, retraining programs, and education reform. But more needs to be done—and faster.

Will AI Tools Replace Software Engineers?One of the most pressing concerns is whether AI tools will replace software engineers.

After all, tools like GitHub Copilot, Tabnine, and other AI-powered IDEs can write code, suggest fixes, automate testing, and even generate UI designs. Does this mean software engineering is a dying field? Not at all.

Here’s why:  

What AI Can Do: AI excels at automating routine tasks, accelerating development, and handling low-level, repetitive coding. For example, it can write boilerplate code, optimize algorithms, or convert code between languages.  

What AI Cannot Do (Yet): Software engineering is more than just coding. It involves understanding complex business problems, designing scalable systems, making trade-offs, and integrating solutions into real-world contexts. AI struggles with this level of abstraction, creativity, and human-centric design. It also lacks the empathy, ethical judgment, and collaboration skills required for teamwork, stakeholder management, and ensuring software meets human needs.

The future of software engineering is not about replacement but transformation. Engineers who embrace AI tools will become more productive, focusing on higher-value tasks like system architecture, AI model management, and ethical software development. New specializations, such as MLOps (machine learning operations), AI security, and human-AI interaction design, are emerging, creating fresh opportunities.

Why Study Software Engineering Anyway?

Given AI’s impact, is there still value in studying software engineering? Absolutely. Here’s why:  

High Demand: Despite automation, the demand for skilled software engineers continues to grow, driven by digital transformation and AI development. Software engineering remains one of the fastest-growing and highest-paying fields.  

Transferable Skills: Studying software engineering teaches problem-solving, logical thinking, systems design, and collaboration—skills that are valuable across industries, even as specific tools or languages evolve.  

AI as a Tool, Not a Threat: AI is most effective when guided by humans who understand both technology and problem domains. Software engineering equips you to use AI tools effectively, rather than being replaced by them.  

Shaping the Future: By studying software, you gain the ability to influence how technology, including AI, is developed and deployed, addressing critical ethical, social, and economic challenges.  

Entrepreneurship and Innovation: Software engineering skills enable you to create solutions, start companies, or innovate within organizations, making you a driver of change.  

Lifelong Learning: The field inherently requires continuous learning, preparing you for a future where adaptability is key.

How to Prepare for the Future of Work

To thrive in an AI-driven world, both individuals and society must act proactively. Here’s how:  

• For Individuals:  
  Embrace lifelong learning through platforms like Coursera, edX, and Udemy.  Focus on human skills like creativity, critical thinking, and communication, which AI cannot replicate.  Learn to work with AI tools relevant to your field, such as GitHub Copilot for software engineers.  Specialize in high-value areas like system architecture, security, or AI ethics.
• For Society:  
  Reform education to emphasize interdisciplinary skills, AI literacy, and adaptability.  Invest in reskilling programs to help workers transition to new roles.  Explore innovative policies like UBI, reduced workweeks, or tax incentives for human-AI collaboration.  Increase public awareness of AI’s implications through accessible education.

The future of work, shaped by AI and automation, is not something to fear but something to prepare for.

Software engineering remains a valuable field to study because it equips you with the skills to navigate, influence, and thrive in this future.

AI will not replace software engineers wholesale, but it will change the nature of the job, rewarding those who are adaptable, creative, and eager to learn.

At the same time, society must take the future of work seriously by investing in education, reskilling, and policies that ensure technology benefits everyone.

The question isn’t whether to study software engineering, but how to approach it strategically—by focusing on skills that complement AI, not compete with it.