New Research Reveals the Reason Work Feels Harder Than It Should

In this article we discuss:

• Employees are engaged, but buried in manual integration

• AI is more effective within workflows than as a peripheral tool

• AI adoption increases when the system is trustworthy

A new report from Workday finds employees are positive about work and AI, but stuck acting as glue between disconnected systems, limiting the impact of AI in the enterprise. AI was expected to free people to do more strategic and creative work, but more than 8 in 10 (82%) employees say they spend significant time acting as translators, copying and pasting information between systems. 

The research highlighted that:

• Over 75% of employees rely on AI to remove friction, reduce manual work, and make their jobs easier

• 43% of employees surveyed report their days feel busy, but not productive 

• Only 27% of organizations have embedded AI into the core of their business

By adopting AI tools that do not have direct access to core business data and processes, companies have buried their employees in busywork—translating, copying and pasting, double-checking, and coordinating between AI outputs and the core functions that actually run the business, like hiring, payroll, and closing the books.

The report, The Copy/Paste Economy: Why Task-Oriented AI is Failing the Enterprise, is based on a survey of 6,100 professionals across finance, HR, IT, and operations, all active AI users at organizations with 500 or more employees. 

Employees are saying that they believe in their work, and they believe in AI—but they’re stuck doing too much of the wrong kind of work. When AI is treated as a bolt-on tool for isolated tasks, it simply speeds up busywork. The real transformation happens when AI is integrated into the systems and workflows that already run the business, so people can focus on the strategic, creative, and human work that truly moves organizations forward.

Employees are engaged, but buried in manual integration

Contrary to the prevailing narrative that employees are disengaged and fearful of AI, the research reveals that 97% of respondents like their jobs. Nearly nine in 10 report a strong sense of progress, ownership, and connection to organizational goals. 

But they are spending an enormous part of their day doing busywork that systems could be doing: 

• 77% say their work requires them to reconcile conflicting data from different tools 

• 70% say they have to re-enter the same information into different systems or tools

• 20% lose more than seven hours a week to manual integration 

• 25% of IT professionals say these efforts define their workday

Before AI, people connected systems manually, moving data, chasing approvals, translating information from one tool to the next.

"My day feels busy but not genuinely productive when I'm pulled into constant coordination tasks and system-related issues that interrupt my actual work," said one study participant, a director-level employee in construction.

The research indicates that employees are not disengaged. They are overloaded with work that systems should be doing.

AI is more effective within workflows than as a peripheral tool

Most organizations have introduced AI, but only 27% have embedded it directly into core workflows. The rest are using it only at the periphery, for individual tasks, like drafting emails, summarizing documents, and answering isolated questions. 

AI agents operating without access to an organization's core systems tend to generate results that look reasonable, but they lack context and risk violating compliance rules because they cannot access the policies, approval chains, and data models that encode how a business actually runs. More than ⅔  (68%) of employees said missing or unclear information has delayed decisions, and nearly half have been forced to work around core systems altogether.

The difference in outcomes is stark. Among organizations with AI embedded in core systems, 60% of employees report time savings of 25% or more. Where AI sits outside core systems, less than a quarter of employees say they save that much time.

Employees want to use AI for more high-impact projects. The top use-case requests are:

• 47% monitoring metrics  

• 44% assisting with onboarding 

• 40% budgeting and forecasting 

• 38% routing approvals 

• 37% supporting financial close

Even among organizations scaling AI, 82% of employees still say navigating processes and systems is a source of stress. 

AI adoption increases when the system is trustworthy 

Nearly nine out of 10 (87%) of employees in the study say their confidence in AI increases when they trust the underlying system and data. Employees already trust the systems they use to run payroll, close the books, and manage their teams. When AI operates inside those same systems, the confidence gap largely disappears.

The report outlines a roadmap for leaders who want to move beyond task-based use cases and build an AI-powered operating model, including how to:

• Fix the foundation first. Modernize core systems and data so AI can produce consistent, reliable outputs.

• Integrate AI into end-to-end processes. Move from isolated task boosts to workflows where AI and humans each own clearly defined steps.

• Design for embedded, intelligent, invisible AI. Ensure AI is delivered in the flow of work, inside the tools and systems employees already use, rather than as yet another standalone solution.

Read the full research report.

Methodology: Workday commissioned The Harris Poll to survey 6,100 Finance, HR, IT, and Operations professionals globally, all actively using AI at organizations with 500+ employees. The survey was conducted March 2–24, 2026.