The future of work is agentic - The McKinsey Podcast Recap
Podcast: The McKinsey Podcast
Published: 2026-01-02
Duration: 35 min
Summary
The episode explores the integration of AI agents into the workforce, highlighting how they can enhance productivity and transform team structures. Jorge Amar discusses the shift towards an agentic workforce, where AI not only generates content but also executes tasks autonomously.
What Happened
In this episode, host Lucia Raheli and Roberta Fasaro welcome McKinsey Senior Partner Jorge Amar to discuss the emerging concept of agentic AI. Amar explains that while generative AI has been at the forefront, the next evolution involves AI agents that can perform tasks independently. These agents not only generate content but also perceive reality, make decisions, and learn from their actions, leading to the creation of a digital replica of a workforce.
Amar provides insights into practical applications of agentic AI across various industries. He mentions examples in IT support, customer service, and talent acquisition, where AI agents automate processes such as screening candidates and managing customer inquiries. This shift towards using AI as a partner in the workforce raises questions about productivity and the potential for reducing headcount, as many companies explore ways to maintain or enhance their workforce capabilities while integrating AI.
Key Insights
- Agentic AI represents a significant evolution from generative AI by performing tasks autonomously.
- AI agents are increasingly being deployed in structured environments such as IT help desks and talent acquisition.
- The integration of AI can enhance productivity while also prompting companies to reconsider workforce structures.
- Executives are divided on the use of AI for reducing headcount versus leveraging it to complement and boost human skills.
Key Questions Answered
What is agentic AI?
Agentic AI refers to a new generation of artificial intelligence that not only generates content but also executes tasks based on its understanding of reality. Jorge Amar highlights that this type of AI can perceive information, make judgments, and learn from its actions, moving beyond the reactive nature of traditional generative AI.
How are companies currently using agentic AI?
Companies are experimenting with agentic AI in structured environments like IT help desks and HR. For instance, AI agents are employed to screen candidates by cleaning data and ranking them, while others manage customer service inquiries by following clear processes. This shows a growing trend towards automating repetitive tasks to enhance efficiency.
What are the implications of using AI in the workforce?
The use of AI in the workforce raises important considerations regarding productivity and employment. Jorge Amar notes that while some executives are contemplating reducing headcount with AI, many others see it as a means to maintain existing staff while improving productivity and redefining roles. This dual approach highlights the complexity of integrating AI into business operations.
How does agentic AI differ from generative AI?
Generative AI is primarily focused on creating content based on prompts, whereas agentic AI takes a step further by executing tasks autonomously. Jorge Amar explains that agentic AI can not only generate content but also perceive its environment, make decisions, and learn from its actions, creating a more dynamic interaction within business processes.
What future trends might we see with AI in business?
As companies continue to explore the capabilities of agentic AI, we may see a shift in workforce dynamics where AI plays a more integrated role alongside human employees. Jorge Amar suggests that this could lead to companies finding new ways to differentiate themselves based on their AI capabilities, as all firms gain access to similar technologies, creating a need for innovative strategies.