The technology sector has always evolved through disruption, from on-premise servers to cloud-native platforms, change has been the only constant. Today, generative AI (GenAI) marks a profound inflection point-one that is reshaping the fabric of IT professions. As someone who has spent years leading digital transformation initiatives and guiding tech talent through paradigm shifts, I see GenAI not only disruptive but a real breakthrough in Technology eco-system.
Automation and the Transformation of IT Roles
By 2030, analysts estimate that up to 30% of work hours globally could be automated by AI technologies. This shift is no longer speculative; we are already witnessing its effects. Tools like GitHub Copilot, OpenAI Codex, and Google's Gemini are automating significant parts of the software development lifecycle, from code generation and bug fixing to unit testing and documentation. In parallel, AI agents are evolving beyond assistants into autonomous decision-makers capable of managing Tier-1 IT support or running regression testing suits without human intervention.
Redefining careers: Towards new opportunities
This new reality is prompting IT leaders to rethink workforce planning. Routine IT roles, particularly entry-level software engineering, support, and QA positions, are under pressure. Traditional career ladders are being compressed. But rather than retreating in fear, we must look deeper into how GenAI can augment human potential, unlock new capabilities, and create previously unimagined roles.
Skills for tomorrow: Emphasizing AI literacy
There is no denying that GenAI is displacing certain tasks. A junior developer, for example, once spent weeks writing repetitive code and documentation. Today, a few lines of prompts can achieve the same in hours. We see companies redesigning their IT value chains, reducing reliance on human labor for low-value tasks and delegating them to intelligent agents. But this trend is not about "less people"; it's about more productivity, more creativity, and more strategic focus.
Human-AI collaboration: A new Work Model
Tech leaders agree. Bill Gates acknowledges that AI will make specialized knowledge broadly accessible "Doctors, lawyers, teachers …" it will reduce costs across sectors. But he also notes the disruption: "This is completely new territory." Satya Nadella, CEO of Microsoft, sees AI as a shift in knowledge work. "The grunt work will go away," he says, "and humans will focus on higher-order decision-making." Sundar Pichai of Google adds that coding will become more accessible, even for non-experts. He foresees a democratization of software creation, where "the bar for programming is lowered." Elon Musk, more provocatively, suggests that AI will ultimately render most jobs optional, with universal basic income as a potential societal response.
The commitment of tech leaders: Anticipate & Act
While their tones differ, their messages converge: automation is inevitable-but the human role is evolving, not vanishing. Software engineering, the backbone of the IT ecosystem, is undergoing its own metamorphosis. The traditional role of "code producer" is giving way to AI orchestrators-engineers who design, supervise, and refine intelligent systems. Future developers won't write every line of code themselves. Instead, they will collaborate with GenAI tools, shaping prompts, evaluating outputs, and ensuring quality and compliance.
Towards an uncertain future: Reflections on Value in Work
Moreover, new responsibilities are emerging. Engineers must now understand how AI models are trained, how to fine-tune them, how to integrate them securely, and how to evaluate them for bias or hallucination. This calls for an expanded skillset. AI literacy, cloud infrastructure, data ethics, and governance are becoming core competencies.
These shifts will create new job categories, new opportunities. The demand for these roles will grow :
- AI/ML engineers to build and refine models.
- Prompt engineers who master the art of instructing large language models.
- AI product managers who translate business needs into AI capabilities.
- Ethics and compliance officers to govern responsible AI usage.
- Data curators and annotators to ensure model accuracy.
- AI experience designers who align user journeys with AI-driven interactions.
In parallel, cybersecurity, cloud architecture, and platform engineering roles are gaining prominence as AI infrastructure becomes critical. These are not fringe cases-they are the foundation of the next IT era.
What Should Tech Professionals Do Now?
The imperative is clear: adapt, upskill, and lead. GenAI is not a passing trend; it is a foundational shift. For tech professionals and organizations alike, the focus must move toward the following:
- Continuous learning as AI evolves fast. Become a specialist than a generalist.
- Hiring should prioritize skills & capabilities not just credentials.
- Skills development should combine technical acumen with business insight and ethical awareness will define tomorrow's leaders.
- Rely on Human and AI collaboration. Success will lie in designing workflows where AI handles the repeatable and humans focus on judgment, creativity, and empathy.
As McKinsey emphasizes, companies must reimagine their talent strategies. The most agile organizations are already investing in AI literacy for all, from engineers to executives.
As a CEO of a Tech company, I don't just watch these shifts, but I must anticipate and act on them. Technology is a powerful lever, but it is people and purpose that determine its impact. Our responsibility is to guide our teams through this evolution, not only by reskilling but by instilling a growth mindset.
Ultimately, the net effect on IT jobs remains uncertain but GenAI will amplify our strengths-and expose our weaknesses. It will force us to think beyond efficiency toward meaning: Why do we build? Whom do we serve? These are human questions, and they will remain human answers, even in an AI-powered world.
