Impact of Agentic AI on Workforce in 2025 and Beyond

We are experiencing a paradigm shift from AI that analyses data and follows programmed rules, to Generative AI that creates new content from learned patterns, and now to Agentic AI, the system which goes further by reasoning, planning, deciding and taking autonomous actions to achieve goals across processes in dynamic environments.

Agentic AI is designed to handle uncertainty and equipped to make autonomous decisions, which is why enterprises are excited about its potential, with the Agentic AI market expected to touch USD196 billion by 2034, reaching an impressive CAGR (Compound Annual Growth Rate) of around 44%.

Scaling agentic solutions demand a specific delivery model that combines data, advanced scientific research and engineering breakthroughs, technology, and processes with specialized and focused talent. As more organizations are deploying agents, there’s a surge in the way to coordinate multiple specialized AI agents as an intelligent network. One of the emerging trends is agent orchestration that is standing out as the primary pillar supporting enterprise architecture. It necessitates bridging data, processes, and customer engagement through AI-driven workflows instead of point-to-point integrations. Moving forward, organizations will increasingly run AI-infused processes with agents handling data flows and making autonomous decisions with humans involved in monitoring outcomes.

For sustainability, relevance and growth, organizations are being compelled to reimagine how people and processes can continue to interact with technology in an effective manner. It requires deep reskilling of the workforce for a future where AI is ingrained in every business decision.

Success of Agentic AI and Workforce Talent Pool

According to a recent survey, around 43.5% of executives are using Gen AI tools, and only 26.5% of employees acknowledge. This data reveals an unpredicted skills gap between executives and employees, suggesting that there is a lot of interest in AI, and a shortage of skilled people in implementing the same. The global workforce is keen to learn the new AI related skills to have a better understanding and get aligned to the technological advancements, which needs to be supported at the organization level through well-crafted training programs.

Several organizations are taking action by segregating their workforce into AI builders and consumers. Builders include architects, data scientists, engineers, and domain experts who create and refine AI tools, while the broader workforce, the consumer, is trained to use AI outputs and incorporate them in decision-making. This two-fold investment in creating a specialized talent pool, and having a wider AI educated workforce, is now regarded as indispensable for thriving in the industry with the rise of agentic AI.

Realigning Roles, Skills, and Human-Machine Interaction

AI is gradually transforming legacy roles, with some getting extinct, and many new ones are emerging. We’re experiencing this shift in action, with prompt engineers, who design inputs for AI models, AI translators who convert machine outputs into strategic advice, and AI agent supervisors who handle the stack of AI tools. For successfully traversing the trajectory of changes, it is essential for organizations to acquire blended skillsets combining domain expertise, technical prowess, human judgment and decision-making capabilities.

Every organization will need to have a clear strategy on its expectations from any AI implementation and where it’s heading in the next few years. Human governance, interaction and collaboration will continue to be crucial as humans will have to take ownership of issues and resolutions, cognitive decisions, ethical values and judgment as applicable, while agents are deployed to handle the redundant and/or data intense workload. Organizational policy should enable more on-the-job training by engaging specialists to execute small-scale real-time projects for the workforce to learn and practice new skills.

Ethics and Values at the Core of Innovation and Upskilling

With the growth of Agentic AI, we are experiencing an upsurge in the need for governance and ensuring conscience-based outcomes. Employees are not so comfortable with the extent to which agents may penetrate into the human lives as it may have serious impacts such as job displacements and subsequent job losses. Concerns are being raised on the data usage by the agents and on the effectiveness of the mechanisms for ensuring data privacy.

Organizations need to implement processes to oversee every AI deployment inclusive of operating within controlled parameters and following guidelines for responsible AI. It implies emphasis on using role-based privileges for access control, audit logs, and clear checkpoints with humans in the loop from start. Setting up boundaries with clear expectations early, builds trust and prevents mistakes of direction less implementation. To combat the uncertainties of the present and to secure the future, a few organizations are consistently designing and executing upskilling programs, creating a more diverse and better equipped workforce to meet the demands of time.

Setting up and Growing an Agentic-Ready Team

The future looks bright for the early adopter organizations embracing the advancement in AI. In this endeavour, an important initiative is to first map the future organization and reimagine roles by identifying which roles will evolve, such as prompt engineers or AI ethicists, as well as which ones may become obsolete. Determining which employees are AI builders and who are the users or consumers of AI tools, will highlight any necessary changes and enable an organization to launch focused training for the workforce at a large scale.

After getting a clear picture of the future roles it will need, organizations must then pair investments in core AI talent with efforts to achieve extensive AI literacy. One way of doing this is by incorporating continuous learning into daily work routines and implementing hands-on learning through small scale projects, hackathons, internal training, and mentorship programs. Acknowledging these efforts during regular review sessions and building cross-functional teams that combine business, IT, and data skills will promote a collaborative culture that will be conducive for learning, research, and AI adoption to address any challenges.

Organizations must prioritize responsible AI to build an agentic-ready workforce by having systems with humans overseeing any AI implementation from the start and identifying risks with contingency as well as risk mitigation plans in place so that the ethics and values are not compromised. Keeping humans in loop will help in tracking what is working in alignment with the organizational strategies versus what needs attention or correction, what is trending and what should be decommissioned for good.

Growing organizations must understand that AI is like any other technology and is here to help humans work easily and comfortably. One such area where AI is doing wonders is with coding. For the unversed, vibe coding refers to AI-assisted coding with inputs in natural language, a practice that is trending since AI became a mainstream technology. According to a report by Entrepreneur, vibe coding today has become so predominant that AI is now responsible for writing up to 30% of project code at Microsoft and Google. This trending practice signals a fundamental shift in the role of software engineers and developers.

As is true for any innovation, building agentic AI oriented systems too will require iterative processes to measure skill building, infrastructure readiness, market demand and more, through upskilling/reskilling programs and PoC projects of smaller size to set the ball rolling. Since reskilling or upskilling have now become a survival mechanism to stay relevant, organizations are implementing training programs to support the trending shifts to build unified skillsets to gain momentum and secure growth.