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Gen Z may be “agentmaxxing” according to McKinsey's latest report

McKinsey’s latest research suggests younger leaders are more comfortable working alongside AI agents

Patrecia Meliana

09 Mar 2026 • 5 min read

First there was “auramaxxing,” Gen Z slang for cultivating an ineffable cool and optimizing the vibe one projects online. Then came “looksmaxxing,” the trend of going to extreme lengths to improve one’s appearance.

Now another form of maxxing may be emerging in the workplace called “agentmaxxing”. The idea refers to going all-in on agentic AI, the next generation of artificial intelligence systems capable of pursuing multistep goals with limited human oversight. And according to McKinsey’s The State of Organizations 2026 report, younger leaders may be particularly ready for it.

In a global survey of more than 10,000 organizational leaders, the consulting firm found a clear generational difference in how executives think about AI’s role at work. While most leaders still view AI primarily as a support tool, younger leaders are significantly more likely to expect the shift toward autonomous AI teammates to happen soon.

This article explores how generational attitudes toward AI could influence the adoption of agentic systems, why younger leaders appear more comfortable working alongside AI agents, and what the shift could mean for marketing teams navigating the next phase of workplace automation.

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Why younger leaders expect AI agents to arrive sooner

Generational differences in technology adoption are nothing new. Younger professionals tend to be more comfortable experimenting with emerging tools, while senior leaders often approach them more cautiously.

McKinsey’s research suggests that the same pattern may be playing out with agentic AI.

In the survey, 27% of leaders aged 18 to 24 say they expect AI to take on agentic roles and function as autonomous teammates within the next one to two years. Among leaders aged 55 and older, that figure falls to 19%.

The gap may seem modest, but it highlights a meaningful difference in expectations. Younger leaders appear more ready to imagine AI operating as an active collaborator inside workflows rather than simply providing recommendations or automation.

That shift in perception could influence how quickly organizations move from AI experimentation to real operational adoption.

The shift from AI tools to AI teammates

Much of today’s enterprise AI still functions as a productivity assistant. Tools summarize information, generate drafts, analyze data, or automate repetitive tasks.

However, agentic AI represents a different model.

Instead of performing isolated tasks, these systems can pursue broader objectives, coordinate multiple steps, and adapt their behavior as new information becomes available. In practice, that means AI systems may soon be able to manage parts of complex workflows that previously required continuous human supervision.

For marketing teams, the implications could be significant. AI agents could monitor campaign performance in real time, generate new variations, run experiments across channels, and recommend strategy adjustments automatically.

The technology is advancing rapidly. But adoption will depend on whether organizations feel comfortable trusting AI to operate as part of a team rather than simply as a tool.

Why Gen Z could accelerate AI adoption across organizations

If Gen Z professionals already view AI as a collaborator, they may play an outsized role in bringing agentic workflows into everyday business operations.

Many younger workers have grown up alongside algorithm-driven platforms, recommendation systems, and AI-powered apps. As a result, interacting with intelligent systems often feels intuitive rather than disruptive.

Employees who are comfortable with AI tools are more likely to explore new use cases, test workflows, and share discoveries with colleagues. Over time, these experiments can reveal practical applications that formal AI initiatives might overlook.

In that sense, the rise of agentmaxxing may simply reflect a cultural shift inside organizations. Instead of waiting for top-down AI strategies, employees may begin integrating AI agents into their work organically.

What marketers should know about AI-native workers

For marketing teams, the emergence of AI-native workers could reshape how campaigns are created, tested, and optimized. As younger professionals enter the workforce with a higher level of comfort around AI tools, they may introduce new ways of working that prioritize experimentation and speed.

Several practical implications stand out for marketing leaders.

1. AI-assisted creativity will become standard practice

Younger marketers are more likely to treat AI as a collaborative partner during the ideation phase. Campaign concepts, messaging variations, and creative directions may increasingly be generated with AI support before being refined by human teams.

2. Campaign experimentation will accelerate

AI-native workers tend to approach marketing as a continuous testing environment. Instead of launching a small number of carefully crafted campaigns, teams may run dozens of AI-assisted variations simultaneously and refine them based on performance signals.

3. Workflow automation will expand across marketing operations

AI agents can monitor performance data, identify trends, and recommend adjustments in real time. This allows marketing teams to spend less time on manual optimization and more time on strategy, positioning, and creative direction.

4. Peer-led AI adoption may become the norm

In many organizations, younger employees may become informal guides for AI experimentation. By sharing workflows and practical use cases with colleagues, they can help accelerate adoption across the broader marketing team.

As organizations experiment with agentic AI, marketing departments may become one of the earliest environments where hybrid human–AI collaboration becomes routine. If younger professionals already see AI agents as teammates rather than tools, they may help accelerate that transition.

Over time, the normalization of hybrid human–AI workflows could reshape how organizations approach productivity, creativity, and decision-making.

In other words, the next workplace trend may not be about optimizing personal style or social media presence. It may be about agentmaxxing.

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