How to prepare for the AI-related jobs that will emerge in the next decade

39% of key job skills will change significantly by 2030. This transformation, driven by the accelerated advancement of artificial intelligence (AI), is not only changing current jobs but also creating professions that didn't even exist a few years ago.

According to an estimate published in Forbes, AI could generate up to 170 million new jobs in the next decade, from specialized technical roles to roles linked to business strategy and ethics.

While the risks of automation and replacement are being discussed, the real change is already taking place on another level: that of collaborative work between humans and AI agents. Tools like GitHub Copilot write code, debug errors, and document processes without direct human intervention.

According to Microsoft CEO Satya Nadella, 30% of the company's code is produced by AI systems, demonstrating the concrete impact of these technologies on professional and operational development.

A New Class of Digital Workers

AI agents represent an emerging category within the workforce. They are autonomous systems that perform complex tasks such as research, analysis, customer service, and content generation.

Their performance depends on a technical infrastructure that allows them to operate on a large scale and securely. A key component is the Protocol Context Model (PCM), a standardized platform that enables these agents to interact with business data and tools.

This technology not only transforms existing functions but also creates entirely new jobs. According to Manikandarajan Shanmugavel, associate director of machine learning application development at S&P Global, understanding the functioning and potential of these agents is key for those seeking to remain competitive in a constantly evolving market.

The new technical roles dominating the landscape

At the heart of this transformation are technical professionals who design, maintain, and operate AI systems. PCM architects are responsible for building the infrastructure that connects agents to business tools. They also manage servers and logs, ensuring that the integration is scalable and secure.

Once these systems are deployed, MCP operators oversee their daily operations: they configure access, adjust the contexts used by agents, and monitor performance to ensure efficiency and protection. In turn, AI workflow designers develop multi-stage processes that allow multiple agents to collaborate seamlessly.

On the other hand, AI agent swarm managers manage large groups of autonomous systems, optimizing resources and ensuring that their actions are aligned with the organization's strategic objectives.

The link between technology and business

Beyond the technical level, business integration roles gain relevance in companies that adopt AI-based solutions. AI product managers define the direction of technological developments, coordinating between engineering teams, data scientists, and decision-makers.

At the operational level, business intelligence (BI) analysts interpret data generated by AI systems to guide concrete decisions. Their task includes identifying opportunities for use and ensuring that the implemented solutions respond to real needs.

On a broader organizational scale, AI transformation strategists drive cultural and technological change, promoting cross-functional adoption of these tools. According to Shanmugavel's analysis for Forbes, their role requires knowledge in change management and technological understanding to integrate agents without operational friction.

With the increasing autonomy of intelligent systems, the development of robust governance frameworks becomes essential. Compliance and ethics specialists work to create internal regulations and ensure that AI applications comply with external regulations. These roles require legal training, risk management experience, and deep technical knowledge.

Skills That Define Professional Success

The new work environment demands specific skills that were not considered in traditional models. Among the most valued is AI literacy, understood as the ability to identify its appropriate applications and limitations.

Swarm management, the coordination between humans and multiple autonomous agents to achieve complex objectives, is also gaining importance.

Another strategic skill is clear problem formulation, which allows challenges to be contextualized and measurable goals to be defined, especially in tasks where AI still relies on human guidance.

Finally, ethical governance is positioned as a cross-cutting axis: establishing criteria for accountability, traceability, and transparency is essential in environments where decisions are also made by non-human agents.

What organizations should consider today

The analysis published in Forbes suggests some urgent actions for companies that want to prepare effectively. These include adopting AI as a central policy, investing in specific training, eliminating bureaucratic barriers that hinder innovation, and developing governance rules before mass adoption.

According to Shanmugavel, these measures allow organizations to redesign roles, facilitate collaboration between humans and intelligent systems, and form mixed teams capable of adapting to the changes imposed by technological advancement.