Preparing the workforce for agentic AI and autonomous systems

Just a few years ago, people mostly thought of artificial intelligence (AI) as a productivity assistant helping professionals write emails, code, summarise documents, or answer questions.

But the AI of today is becoming something far more powerful.

A new generation of agentic AI systems can reason, plan, interact with software, use external tools, collaborate with other AI agents, and execute multi-step workflows with minimal human intervention. As enterprises investigate these capabilities, the conversation is rapidly shifting from ‘how can AI help employees?’ to ‘how can employees work effectively alongside increasingly autonomous AI systems?’

This is a workforce evolution, not just a technology evolution.

Gartner says that, by 2028, AI agents will autonomously make at least 15% of the decisions in day-to-day work, compared to virtually none in 2024. At the same time, McKinsey estimates that generative AI could contribute $2.6 trillion to $4.4 trillion annually to the global economy. 

Technology is moving at warp speed but the big question is are organisations preparing their people at the same pace?

From AI assistance to AI collaboration

The first wave of enterprise AI was about making the individual worker more productive. People used AI to write content, analyse data, automate monotonous work, and speed up software development.

The next stage is agentic AI, which can break down objectives into granular tasks, interface with enterprise applications, gather information, collaborate with other systems, and run workflows without waiting to be told what to do, while keeping humans in the loop when their judgement or oversight is required.

This doesn’t lessen the importance of people, it moves the source of their value. As AI assumes operational execution, professionals will spend more time on decision making, governance, creativity, innovation, and validation of the AI results. 

The skills gap challenge

There is a lot of attention on AI models and computing infrastructure, but many organisations don’t ask a more fundamental question: does the workforce have the skills to leverage these technologies effectively?

Getting ready for agentic AI is not about teaching employees to use yet another software tool. It’s about blending a new mix of technical and human capabilities.

Technical teams must be conversant with cloud platforms, AI orchestration, APIs, data engineering, cybersecurity, MLOps, and AI governance. Business teams need to understand how AI fits into workflows and how to evaluate AI-generated outputs and redesign processes around intelligent automation. Critical thinking, ethical decision making, systems thinking, communication, and sound judgement are equally important skills.

According to the World Economic Forum’s Future of Jobs Report 2025, 39% of core workforce skills will change by 2030 and 86% of employers expect AI and information processing technologies to transform their businesses over the next five years.

This is no longer an IT initiative. It’s a capability challenge across the enterprise.

Upskilling can no longer be event-based

One of the biggest lessons learned from enterprise AI adoption is that traditional learning models are lagging behind technology.

Agentic AI frameworks, cloud-native AI services, enterprise AI platforms, and orchestration technologies are continually evolving. One-off workshops don’t cut it because skills that are relevant today may need major updates in just months.

Hence organisations need continuous role-based education that blends formal learning tracks, hands-on labs, real-world scenarios, cloud environments, industry-recognised certifications, and real-world business scenarios.

The objective is no longer to help employees understand AI concepts. It is to enable them to confidently apply AI to solve real business problems.

The faster workers become ready for AI, the faster productivity, innovation, and business advantage are achieved. Organisations that invest in continuous capability building will be far better positioned to scale AI successfully than those that treat learning as a one-time exercise.

Responsible AI starts with responsible people

With increasing AI autonomy, governance matters just as much.

Employees need to learn how to build AI, but also how to govern it. To grow an AI workforce that can keep business goals in line with consumers’ expectations of AI, professionals must be well-versed in AI governance, cybersecurity, privacy, regulatory compliance, and ethical AI.

Governance in AI is not a look at the technology; it is about people, processes and accountability. Technology alone cannot make AI responsible. Investors, policymakers, and the general public are increasingly demanding transparency and governance. Therefore, leaders buy into the AI workforce of tomorrow through learning and building accountability.

India’s opportunity to lead

India is at a crossroads.

The country, with one of the largest technology talent pools in the world, a vibrant startup ecosystem, and growing investment by enterprises in AI, has the potential to position itself as the world’s master of AI-ready talent. Whether or not it does depends on how fast organisations invest in training their people.

By 2028, India’s digital skills gap could reach 28-29% according to Nasscom, even as the talent demand for AI, cloud, cybersecurity and emerging technology is increasing. Bridging the gap requires a joint effort by industry, enterprises, academia and the workforce development community to create a learning ecosystem that is rapid, responsive and adaptive to technology.

The real competitive advantage

All the great technology waves have paid off to those who moved early, not the ones who were simply early adopters of technology, but the ones who created people who, of course, were prepared to use it.

Agentic AI is no exception. Those who win will not be the ones with the most advanced AI model, but the ones who build a workforce that is ready to work with intelligent systems, make decisions, and keep learning as the technology moves forward.

The workplace of the future will be defined not just by AI, it’s going to be defined by people who know how to work with it.

The author is the co-founder and CEO of edForce, a workforce upskilling accelerator.