For creators and makers, the arrival of autonomous AI agents means a fundamental shift from using software as a passive tool to deploying intelligent collaborators that can execute complex workflows without constant supervision. As adoption is projected to surge by up to 300% in the next two years, the implications for artists and builders are profound: the era of manually prompting simple scripts is ending, replaced by systems that coordinate tasks across multiple environments independently.
The reality for makers and artists
Unlike legacy automation that requires human intervention at every step, these new agents can interact with diverse tools and contexts within an organisation. Early deployments in customer service, human resources, and sales have already driven productivity gains of between 30% and 50%. For the creative industries, this autonomy positions AI not as a calculator or a typewriter, but as a partner working side-by-side with humans, poised to reshape traditional workflows.
More than three-quarters of human resources leaders believe this deployment will completely transform workplace norms, forcing a total reappraisal of how roles are distributed, which skills are prioritised, and how culture is formed. While many admit they are only in the preparatory phase, 86% of chief human resources officers predict that navigating this digital labour will become central to their roles.
Ateet Jayaswal, chief culture and employee experience officer at Wipro, argues that fluency in managing this change is the crucial differentiator for unlocking technology’s full potential. He notes that this moment “calls for a mindset shift in how HR leaders would enable their organisations.”
Redeploying roles for higher-value work
As agents assume ownership of complex tasks, the distribution of responsibilities within an organisation will undergo significant change. It is estimated that three-quarters of current roles will require redesign, reskilling, or redeployment by 2030.
For leadership, the focus must shift to reskilling employees toward higher-value work to optimise the potential of a hybrid workforce. Consider Wipro, a complex entity with 240,000 employees across 65 countries. Previously, fragmented policies and documents across different systems delayed responses to employee queries.
The company recently integrated a custom agentic AI assistant, co-created with the enterprise platform Ema Unlimited. This agent now handles 50 HR tasks that previously fell to humans, navigating the complex internal systems with speed. With this assistance, the average response time to queries has dropped from 48 hours to five seconds.
Human staff now have more time to focus on work requiring a creative and imaginative mind and cross-functional collaboration. The AI agent, meanwhile, handles rote administrative duties like sorting timesheets or helping employees navigate policies. However, Jayaswal cautions that humans must remain in the loop. When agentic AI processes sensitive data, it requires stringent guardrails and constraints that consumer applications do not.
“When you expose an AI agent to organisational data, when you integrate it into multiple enterprise systems, then pathways around the AI agent become extremely important,” he says. Governance must include robust data privacy rules and the establishment of layers such as an AI council. At a fundamental level, the nature of the job changes from being the hero who solves the problem to designing the hero who can solve it.
An evolving employee skillset
Just as roles are reconfigured, core skills are being reprioritised. More than four in five HR leaders say they are planning to reskill workers to remain competitive in a market shaped by AI agents.
Technical skills will be increasingly vital. Leading employers such as Salesforce, Danone, and Walmart are already rolling out dedicated AI and digital skills programmes to equip everyone from frontline staff to C-suite executives with a baseline of AI literacy.
But desirable soft skills are evolving too. Employees assigning tasks to an agent must be able to plainly articulate the modular steps needed, the desired outcome, and the parameters required to ensure the agent does not access confidential data. According to a recent survey, the top three skills emerging for recruitment are relationship building, collaboration, and adaptability.
Maintaining a healthy workplace culture
By freeing humans to focus on higher-value tasks, the hope is that AI agents can elevate the employee experience and deepen fulfilment. “At Wipro, our vision is to improve the life of Wiproites,” says Jayaswal. “We are taking away non-value added work… leaving associates with higher order work content.”
However, leadership teams must also plan for new pressures. There is already confusion, with 73% of HR leaders reporting that their employees do not yet understand how digital labour will impact their work. While some organisations define AI agents as teammates on org charts, new research suggests this could erode trust and a sense of professional identity, raising questions around accountability.
The role of management is critical. To maintain healthy dynamics, managers need to become skilled at orchestrating blended systems, splitting their focus between supervising AI agents and motivating human employees. Upgrading employee well-being programs will be a core part of this, as increased interaction with AI may reduce the human touch provided by colleagues and peers. Services that encourage social connection and empathetic communication may help teams navigate this transition.
A breakneck transformation
Agentic AI is set to scale at breakneck speed across many enterprises, significantly transforming how these organisations operate. Carefully considering how to adapt to this newly blended workforce is now a top priority for leadership teams. Reviewing and refining organisational strategies is essential for optimising both technological gains and the employee experience.
Key takeaways
- Adoption of autonomous AI agents is projected to surge by up to 300% in the next two years, shifting the paradigm from manual tool usage to collaborative, independent execution.
- Three-quarters of current roles are expected to require redesign or reskilling by 2030, moving human focus from repetitive tasks to designing, teaching, and optimising AI systems.
- Leadership must prioritise robust governance and data privacy guardrails, as agentic AI handling enterprise data requires stricter constraints than consumer applications.
- The most valuable emerging skills are not just technical proficiency, but the ability to articulate complex instructions clearly, build relationships, and adapt to a hybrid workforce.
