Artificial Intelligence & Machine Learning
,
Next-Generation Technologies & Secure Development
Autonomous AI Is Transforming the Workforce. Here’s What Managers Can Expect
For better or worse, artificial intelligence is here to stay. With its advanced – and evolving – capabilities, AI is integrated into most business processes and tasks, becoming nearly indispensable across industries. Its impact on the workforce is, thus, unsurprising and raises a familiar question: Can the technology take over jobs?
See Also: Solving business challenges with data & AI: 5 insights from C-suite leaders
Multiple studies and research indicate AI will disrupt the workforce, especially as it evolves to become more skilled to take on complex responsibilities with minimal human supervision. Autonomous AI systems leverage natural language processing, machine learning algorithms and access to large datasets to oversee tasks typically managed by human managers.
While generative AI is over the “peak of inflated expectations,” the global autonomous AI and autonomous agents market size is expected to grow at a CAGR of 42.8% from 2023 to 2030. Gartner evaluates autonomous AI to “perform any task a human can perform … moving slowly from science fiction to reality.”
Do Managers Need to Worry?
As AI continues to evolve, managers must ask themselves: Are we being sidelined or liberated? This question looms larger as autonomous agents step into roles previously occupied by humans.
This transformation is already underway. A survey by Gartner found that 80% of executives think automation can be applied to “any” business decision. The increasing reliance on AI is driven by the technology’s ability to delegate tasks, optimize workflows and even evaluate performance based on data analysis – often tied to a middle manager’s KPIs. “Autonomous agents pose an organizational workforce shift from delivery to supervision,” said Erick Brethenoux, distinguished vice president analyst at Gartner.
For example, consider Microsoft’s Team Copilot. It mimics many of a manager’s role – creating and assigning tasks, tracking deadlines, and notifying team members when an input is needed. Microsoft termed it a “valuable team member,” underlining that the control will always lie with the user so that the “whole team can be more productive, collaborative and creative – together.”
According to a report by CB Insights, more than 50 companies are developing AI-powered agents that can function as middle managers. These AI agents are capable of managing sales, customer service, software development and compliance tasks, among others, effectively acting as decision-makers in enterprise settings.
HR and Project Manager Roles See Disruption
AI could transform the entire employee life cycle – from recruitment to talent management. AI algorithms can predict which sourcing channels are most likely to attract the right candidates for specific roles, reducing recruitment costs. HR tasks, such as performance tracking, scheduling and resource allocation, could also be performed through automation, meaning that managers will have to shift their focus from administrative duties and develop new skills as their roles become centered on human interactions and strategic oversight.
According to a report by Gartner, this will result in the “shifting of roles over time as fewer people will be needed to complete the same amount of work.” In fact, 76% of HR leaders believe they will lag in organizational success if they do not implement AI solutions in the next one to two years.
While AI is automating recruitment processes in HR, project management is also feeling the ripple effect. A report by HBR predicts that “nearly every aspect of project management, from planning to processes to people, will be affected.” Tools such as PMOtto, a machine learning-enabled virtual assistant, can predict project timelines and allocate resources, offering real-time suggestions based on historical data and trends.
As these AI-powered tools become more sophisticated, the role of project managers will shift from managing processes to focusing on stakeholder engagement and collaboration. AI will handle the administrative tasks, while project managers will be expected to navigate complex interpersonal dynamics and drive innovation.
Multi-Agent Architectures Build a Digital Workforce
There is also a budding role of an AI agent managing other AI agents. The multi-agent architecture, says a CB Insights report, will include a “lead agent that will coordinate with specialized sub-agents.” The report cites San Francisco-based Sierra that uses a multi-agent approach to deploy “empathetic and sophisticated” AI agents to businesses. Similar to a peer review or managerial approval, the AI agent shares its responses with another agent before responding to the customer. If the agents are unable to respond, the query is directed to a human agent.
But, Do You Trust a Machine Over a Human?
Trust remains a critical barrier, with many companies double-checking AI outputs, especially in sensitive areas such as compliance. But as the use of explainable AI grows, offering transparent decision-making, companies may begin to relax their guard and fully integrate AI as a trusted part of the workforce.
But despite its vast potential and transformative abilities, autonomous AI is unlikely to work without human supervision. AI lacks the emotional intelligence needed to navigate complex human relationships, and companies are often skeptical of assigning decision-making to AI tools.
The world’s first software AI engineer, Cognition AI’s Devin, is able to successfully resolve only 13.86% of issues. Even if and when the success rates go up, companies will always need humans and “AI middle managers” will perhaps find it difficult to flatten hierarchies and eliminate human workforce.
“One thing that won’t change is that work is still centered around humans, so that people can bring their creativity, which is such an important human trait,” said Fiona Cicconi, chief people officer, Google. Accenture’s report highlights just that. Technology alone will not drive AI-driven growth. Prioritizing people alongside data can lead to productivity gains of up to 11%, while sidelining the human factor slashes that gain to 4%.
Having said that, managers will have to roll up their sleeves, upskill and adapt to AI and emerging technologies that benefit their teams and align with organizational objectives. To fully realize the potential of AI, businesses will need to prioritize human-AI collaboration. In the long term, we can expect to see the emergence of multi-agent AI architectures, where multiple AI agents work together under the supervision of a lead AI manager.
So, human managers will exist – they just may not only manage humans anymore.