How AI Is Transforming Middle Manager Roles

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Discussions surrounding AI transformation in the workplace tend to focus either on leaders who make business decisions about AI integration or individual contributors tasked with using AI tools. But in between is an important, often overlooked, group of workers — middle managers.

At many organizations, middle managers are the connective between business leaders and individual contributors. They translate strategy into execution, maintain team cohesion, support worker engagement, and manage change on a day-to-day basis. 

As organizations embrace AI tools to increase productivity and streamline operations, middle managers are essential to helping teams navigate uncertainty and adopt new technologies they may not fully understand. However, many organizations are falling short when it comes to providing this essential group of workers with the support and resources needed to effectively lead change. 

Engagement is declining among managers

Gallup’s State of the Global Workplace: 2025 Report found that global employee engagement decreased from 23% to 21%, marking the first decline since 2020 and only the second in 12 years. The report also found that engagement declined further among managers compared to individual contributors and especially in managers in specific demographic groups. 

The research shows that the level of individual contributor research was flat year over year, while manager engagement dropped from 30% to 27% in just one year. Even more significant, engagement fell five points among managers under 35 and seven points among female managers.

These findings are alarming because disengagement at the management level can have a cascading impact across the organization. When middle managers are burned out or checked out, teams suffer, morale dips, and adoption of new technology — including AI — may slow down. Middle managers are cultural carriers and operational enablers; when they struggle, so does organizational performance.

This dip in engagement can be attributed to a range of factors. Middle managers have faced years of ongoing disruption — such as navigating the pandemic, transitioning to remote or hybrid work, dealing with organizational restructuring, and addressing shifting employee expectations. Now, the AI transformation is leading to even greater demands and increased workloads, often without the necessary resources or training to succeed.

The AI productivity and burnout paradox

In addition to disengagement, managers are also at a high risk for burnout. The Upwork Research Institute’s recent report, From Tools to Teammates: Navigating the Human-AI Relationship, found that middle managers are demonstrating high levels of AI-driven productivity — while also reporting high rates of burnout.

The report, based on a global survey of 2,500 workers — including executives, salaried employees, and freelancers — found that middle managers reported a 42% average increase in productivity from using AI tools, a slight uptick compared to 36% across all individual contributors. 

However, the same group also reported the highest burnout rate — 76% of middle managers surveyed said they were burned out, compared to 69% of individual contributors.

This paradox — high performance paired with high exhaustion — underscores a systemic issue. Middle managers are clearly adopting AI tools and realizing their benefits. But they’re doing so in a high-pressure environment, often with increased workloads and limited support. The result is unsustainable. Without intervention, organizations risk losing top-performing managers to fatigue and disengagement.

Learning from freelancers’ positive mindset 

Data in the From Tools to Teammates report suggests that while middle managers and other in-house employees may feel burned out amid AI adoption, freelancers are charting a more sustainable path forward. 

Rather than being required to use AI tools mandated by leadership, freelancers have more flexibility to experiment with AI on their own — and they see these tools as opportunities to build skills and grow their businesses. They select the AI platforms that align with their workflow needs, use them to enhance client service, and continually refine their approach based on outcomes.

The report found that 90% of freelancers surveyed said AI helps them learn faster. Additionally, while 37% of freelancers strongly agreed that AI helps them build new skills quickly, only 29% of full-time employees said the same

Freelancers are not only adopting AI tools but turning them into learning resources. They shape their own workflows, experiment with automation, and prioritize adaptability — capabilities increasingly critical in a rapidly shifting workplace.

The mindset freelancers have toward AI tools is something middle managers can learn from and tap into. Seeing AI as a tool to aid learning and growth can help middle managers more effectively use tools on their own and identify ways to build agile, hybrid teams that blend full-time, in-house workers with specialized freelancers and AI technology.

AI is shifting managers’ responsibilities

Some headlines and research suggest that middle manager roles may become obsolete in the coming years. Gartner research predicts that by 2026, 20% of companies will use AI to flatten their organizational structures, potentially eliminating more than half of middle manager roles. 

However, middle managers are far from becoming obsolete or redundant. Rather, middle managers are essential to organizational success in periods of significant transformation, such as the current push for AI integration and adoption. 

A survey of 1,500 executives and leaders conducted by Capgemini Research in 2024 found that more than half of leaders believe managers will play a critical role in leading generative AI-driven change. Additionally, more than half of respondents indicated that they believe generative AI will lead to more specialized manager roles.

In an AI-augmented organization, the role of a middle manager shifts from supervisor to orchestrator. Middle managers no longer simply ensure tasks get done — they’re responsible for determining how work gets done, who does the work, and how to support effective human-machine collaboration.

New middle manager responsibilities in an AI-driven workplace may include: 

• Redesigning team workflows to integrate AI tools alongside human contributors
• Reallocating tasks across in-house team members, freelancers, and AI tools or agents 
• Facilitating team member upskilling and knowledge sharing in an AI-enhanced environment
• Preserving team cohesion and connection amid increased automation and augmentation

Building a future-ready middle management model

For middle managers to effectively lead in an AI-driven workplace, organizations need to reimagine how their roles are defined, supported, and measured. Here are some steps organizations can take to rethink middle manager roles amid AI transformation. 

1. Redefine the role

Modern middle managers should be seen as orchestrators of dynamic talent ecosystems. In addition to team output, their success should be measured based on how effectively they allocate tasks across people and platforms, how well they foster trust, and how quickly they can pivot as new technologies emerge.

Job descriptions and performance reviews can reflect this new reality by going beyond focusing on supervising workers to include: 

• AI integration and fluency
• Cross-functional coordination
• Emotional intelligence and coaching
• Change enablement

2. Prioritize upskilling in AI fluency

Too often, managers are told to use AI without receiving much clarity on what that means — which can lead to slow adoption of AI tools. The Capgemini survey found that while 97% of leaders and managers reported that they have experimented with generative AI tools, only 15% use them at work at least once a day.

Middle managers need targeted training and talent development — not on how AI tools work, but on how to roll out AI to their teams, troubleshoot adoption barriers, and redesign processes to maximize benefits of AI. 

This isn’t about making every manager a data scientist. It’s about giving them the training, vocabulary, and confidence to navigate an AI-enabled workplace, make informed decisions, and model healthy tech adoption for their teams.

3. Encourage AI as a learning partner

Rather than framing AI as yet another technology feature, position AI as a partner in personal and professional growth. Just as freelancers use AI to accelerate upskilling, managers can do the same.

Whether they use AI to draft strategy documents, brainstorm solutions, or learn new analytical techniques, middle managers can focus on learning with AI in addition to simply using AI — which is a mindset they can pass on to other workers. 

4. Listen to and implement feedback from managers

The engagement decline among managers can lead to lost productivity and missed business outcomes in the long run. Organizations need to implement processes and tools to regularly listen to and address feedback from middle managers. Quarterly surveys, roundtable discussions, focus groups, and anonymous feedback tools can surface the challenges managers face in real time.

Listening to manager feedback isn’t enough. Organizations can act on that feedback by taking steps such as rethinking responsibilities, adjusting workloads, offering mental health resources, or revisiting expectations around AI adoption.

5. Reinvest in human connection

One of the risks of increased automation is a decline in genuine human connection. Yet emotional intelligence, trust, and empathy remain irreplaceable in the workplace. Managers should be encouraged to implement rituals that build team collaboration and cohesion, such as regular team check-ins, one-on-one discussions, cross-functional forums, and informal learning sessions.

In an AI-driven workplace, people still want to feel seen, supported, and understood. This is where managers can have a significant positive impact and drive employee engagement, retention, and positive business outcomes as a result. 

Equip managers for the future of work 

As organizations continue to integrate AI, middle manager roles are transforming. And as AI reshapes work, the demands on managers will only grow. With the right support, training, and talent strategy, organizations can keep middle managers engaged and turn them into one of the most important forces for shaping resilient, adaptive, and human-centered workplaces.

Engaging freelancers can help ease middle managers’ workloads, free up time for more strategic work, and enable your organization to access experienced professionals with the skills you need. Freelancers with more than 10,000 skills, including artificial intelligence research, big data engineering, talent management, and digital marketing are available on Upwork. 

Find qualified freelancers on Talent Marketplace™ or sign up for a Business Plus plan to reach the top 1% of freelancers on Upwork and shortlist top professionals based on your job post requirements. Create an account or log in to your existing Upwork account to get started.