Rituparna Chakraborty Writes: IT Workers are at a Crossroads in the Age of AI

A silent transformation is unfolding in the IT-business process management (BPM) sector. As artificial intelligence reshapes industries, professionals find themselves at a crossroads.

The hard truth? The job market is splitting into two distinct categories—AI creators and AI operators. Those who build, refine and push AI forward will dictate the rules, while those who merely use AI will see their roles commoditised and, in some cases, obsolete.

For the millions of professionals in their 30s and 40s working in IT services, software development and business process management, this is an inflection point. Their expertise, honed over decades, faces a test unlike any before.

In a landscape where AI can write code, automate workflows and optimise processes at lightning speed, what remains for the human workforce? The answer: strategic reskilling. Not the kind mandated by corporate training programmes but a deep, intentional shift in learning and career ownership.

A McKinsey Global Institute study predicts that nearly 375mn workers worldwide will need to shift occupations or acquire new skills by 2030 due to AI and automation. The IT-BPM sector is particularly vulnerable, as AI increasingly automates repetitive coding, quality assurance, customer support and even complex analytics.

The middle layer of tech professionals—those managing routine programming, infrastructure support and maintenance—faces the greatest risk. Companies will still offer upskilling programmes, but these are often reactionary and designed to fill immediate business needs.

The professionals who will thrive in the AI age will be those who take control of their learning beyond corporate-sponsored courses. They will need to ask themselves: Do I want to be an AI creator or an AI operator?

Designing the Future

AI creators are the individuals who design, build and refine artificial intelligence. These professionals develop machine learning models, engineer AI algorithms and push the boundaries of what AI can accomplish. Their work goes beyond using AI tools; they are responsible for creating the frameworks and technologies that shape AI-driven ecosystems.

To prepare for this role, professionals must dive deep into data science, machine learning and neural networks.

Mastering AI frameworks like TensorFlow, PyTorch and Hugging Face is fundamental. Strong mathematical and statistical proficiency is non-negotiable, as understanding probability, linear algebra and optimisation is essential to building AI models.

A commitment to research and development is crucial, as AI evolves at a rapid pace. Keeping up with AI research, contributing to open-source AI projects and experimenting with generative AI will separate the true AI creators from the rest.

Furthermore, ethical AI development will be a defining feature of this role. Ensuring AI models are unbiased, explainable and secure is as important as building them.

Mastering Utilisation

AI operators, on the other hand, focus on leveraging AI rather than building it. They integrate AI tools into business processes, enhance decision-making using AI-powered analytics and oversee AI-driven automation. While they do not create AI from the ground up, their expertise lies in optimising and applying AI effectively within organisations.

Preparing for this role requires an in-depth understanding of AI applications, business intelligence and process automation. AI operators must become proficient in AI-powered platforms, data visualisation tools and decision-support systems.

Learning how to interact with AI-driven automation, such as robotic process automation (RPA) and AI-enhanced customer relationship management (CRM) tools, is crucial.

The best AI operators will not merely follow AI’s lead but will understand when to override, adjust or question AI-generated outputs to ensure optimal outcomes.

The Right Path

The decision to become an AI creator or an AI operator depends on an individual’s aptitude, interests and career goals. Those with a strong technical background, a passion for coding and an interest in research-driven innovation may thrive as AI creators.

On the other hand, professionals with business acumen, process optimisation expertise and an ability to bridge the gap between technology and strategy will find success as AI operators.

Regardless of the chosen path, continuous learning is imperative. For AI creators, enrolling in AI and data science programmes from institutions. Engaging in Kaggle competitions, contributing to AI research and experimenting with AI-driven projects will be key steps.

AI operators should focus on developing expertise in AI-integrated business solutions, analytics platforms and workflow automation. Certifications in AI for business, AI-driven decision-making and domain-specific AI applications will add immense value.

The professionals who fail to position themselves in either category risk being left behind in the AI revolution. The age of generalist IT roles is fading. The workforce is shifting toward those who create AI and those who masterfully apply it. The time for comfortable career inertia is over.

The coming decade will see a profound realignment in the IT-BPM sector. AI will not steal jobs outright; rather, it will divide the workforce into those who wield it effectively and those who get displaced by it.

The distinction between AI creators and AI operators is not just theoretical—it is already taking shape. For professionals in their 30s and 40s, the choice is clear: passively wait for AI to render their roles obsolete or actively transform themselves to stay indispensable.

The question is—will you adapt, evolve and lead, or be left struggling to stay relevant?

The writer is co-founder, TeamLease and an independent director on various boards