Artificial intelligence has become a routine part of the modern workplace, but employee trust is emerging as a key obstacle to broader automation. A new global study from TeamViewer finds that while most employees use AI every day and recognize its productivity benefits, many remain hesitant to let autonomous AI systems make decisions without human oversight, highlighting what the company describes as the growing “AI Confidence Gap.”
As enterprises accelerate investments in artificial intelligence (AI) and workplace automation, the conversation is shifting from AI-assisted productivity to autonomous digital workplaces—environments where intelligent systems proactively detect problems, make decisions, and execute tasks with minimal human intervention. However, new research from TeamViewer suggests organizations may need to build greater trust before autonomous AI becomes mainstream.
The digital workplace solutions provider has released its global report, “Path to the Autonomous Digital Workplace,” examining how businesses and employees view the evolution of AI from assistant to autonomous operator. The findings reveal strong enthusiasm for AI-powered productivity, but also significant caution when AI moves beyond recommendations and begins taking independent action.
According to the survey, 75% of respondents use AI at least once every day, reflecting how generative AI tools and intelligent assistants have rapidly become embedded in knowledge work, IT operations, and business processes. Only 3% reported no measurable workplace benefits, while 64% described their overall experience with AI as positive, indicating that enterprise AI adoption has largely moved beyond experimentation.
Yet the research identifies a critical challenge for organizations planning to deploy AI agents and autonomous workflows. While employees are increasingly comfortable using AI to generate content, summarize information, or recommend actions, many are less willing to allow AI systems to act independently.
The study found that 61% of respondents prefer AI not to take autonomous action without human involvement. Among the 35% willing to delegate more responsibility, nearly three-quarters would only trust AI to perform clearly defined tasks within predetermined boundaries. Just 5% expressed no concerns about AI operating without a human in the loop, illustrating how trust remains a limiting factor for enterprise automation.
TeamViewer refers to this disconnect as the AI Confidence Gap—the difference between employees’ willingness to use AI as an assistant and their readiness to grant it operational authority.
The findings suggest organizations are not rejecting AI autonomy outright but instead demanding greater transparency and control. Nearly 70% of respondents said they would support autonomous AI systems if they retained the ability to intervene when necessary, while **40% favored AI that proactively detects and resolves issues while keeping users informed throughout the process.
Confidence in autonomous AI also depends heavily on governance mechanisms. Respondents identified strong cybersecurity and privacy protections (39%), notifications before significant changes (36%), restrictions on AI access (36%), visible activity logs (33%), and rollback capabilities (31%) as the most important safeguards for building trust.
These preferences reflect a broader industry movement toward responsible AI, where transparency, explainability, and human oversight are increasingly viewed as prerequisites for enterprise adoption rather than optional features.
Despite concerns around autonomy, organizations continue to anticipate significant changes in workplace operations over the remainder of the decade. One-third of respondents expect AI to function primarily as a collaborative assistant by 2030, while 28% believe they will delegate more routine tasks to AI and focus on higher-value responsibilities. Only 2% expect AI to eliminate their jobs entirely, suggesting employees increasingly see automation as a tool for augmentation rather than replacement.
Information technology departments appear to be leading this transition.
According to the study, 26% of IT leaders already describe their departments as at least partially autonomous, and 99% say they would delegate at least one IT responsibility to AI. The most commonly cited use cases include system updates (61%), routine device troubleshooting (53%), and device performance optimization (49%).
IT operations have emerged as an early proving ground for autonomous AI because many processes involve repetitive, measurable workflows that can be standardized and governed more easily than complex business decisions. Automated monitoring, predictive maintenance, endpoint management, and incident remediation are increasingly benefiting from AI models capable of detecting anomalies and initiating corrective actions without waiting for manual intervention.
However, the research also highlights the operational costs associated with limited trust. More than half of respondents (56%) regularly verify AI-generated outputs before relying on them, spending an average of two hours each week validating AI results. In addition, 51% admitted they are often uncertain about when AI outputs require verification, underscoring ongoing challenges around AI reliability and user confidence.
The findings align with broader enterprise AI trends identified by industry analysts. Gartner predicts that autonomous AI agents will become increasingly integrated into enterprise workflows over the next several years, while emphasizing that governance, transparency, and risk management will determine successful adoption. Similarly, McKinsey & Company reports that organizations generating the greatest value from AI combine technological investments with operational oversight, workforce training, and clearly defined governance frameworks.
The emergence of autonomous workplaces also reflects rapid innovation across major AI ecosystems. Technology companies including Microsoft, Google, Amazon Web Services (AWS), Salesforce, and NVIDIA are investing heavily in AI agents capable of automating enterprise workflows, customer support, software development, cybersecurity, and IT operations.
For enterprise leaders, TeamViewer’s research suggests the next stage of workplace transformation will depend less on expanding AI capabilities than on strengthening confidence in how those systems operate. As AI evolves from responding to prompts toward making decisions independently, organizations will need to demonstrate that autonomous systems remain transparent, secure, explainable, and aligned with human oversight.
Rather than pursuing fully autonomous operations immediately, businesses may achieve greater success by introducing AI within clearly defined guardrails, allowing employees to build trust incrementally while realizing measurable productivity gains.
Market Landscape
The enterprise AI market is rapidly evolving from generative AI assistants toward autonomous AI agents capable of executing workflows across IT, customer service, cybersecurity, and business operations. Companies including Microsoft, Google, Amazon Web Services (AWS), Salesforce, and NVIDIA are expanding AI agent platforms designed to automate increasingly complex enterprise tasks. Gartner expects AI agents to become a major enterprise technology trend over the next several years, while IDC projects continued growth in AI software and infrastructure spending. As organizations adopt autonomous systems, governance, transparency, and human oversight are emerging as key competitive differentiators.
Top Insights
- TeamViewer’s research shows widespread AI adoption, but employee trust remains a significant barrier to autonomous workplace systems capable of making independent operational decisions.
- Most employees support AI-assisted productivity, yet 61% still prefer human oversight before autonomous systems execute actions on their behalf.
- IT departments are leading enterprise autonomy, with nearly all IT leaders willing to delegate routine operational tasks such as system updates and device management to AI.
- Organizations view transparency, cybersecurity, audit logs, and rollback capabilities as essential safeguards for expanding AI autonomy responsibly.
- The findings suggest trusted AI governance, rather than technology alone, will determine the pace of autonomous digital workplace adoption over the coming decade.
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