Eight in 10 IT decision-makers say the digital workplace is critical to successful AI-led transformation, yet only 10% report having fundamentally redesigned their workplace for AI, according to Lenovo’s sixth Work Reborn report, The AI-ready workplace.

The findings highlight a gap between deploying AI tools and establishing the operational capabilities needed to integrate AI into everyday business processes. The report identifies five interconnected dimensions of workplace readiness: people, workflows, technology, support, and governance. Together, these areas influence how organizations translate AI ambition into measurable business outcomes.

Based on an August 2026 survey of 1,200 IT leaders at organizations with at least 1,000 employees across 12 countries, the report examines the workplace conditions needed to move AI initiatives beyond initial deployment. While 76% of respondents rank AI-led transformation among their organization's top IT priorities, only 27% report having scaled AI across business functions.

AI Deployment Does Not Guarantee Workplace Transformation

Adopting AI tools is only one component of enterprise transformation. Organizations must also consider how AI affects workflows, employee responsibilities, IT support, and governance to enable employees and AI agents to work effectively together.

When AI implementation remains limited to individual departments or business functions, its potential value may remain confined to those areas. Integrating AI across the enterprise requires a broader approach that considers how processes, people, and technology interact.

Measuring Digital Workplace Readiness

The report introduces the AI Workplace Readiness Index, which evaluates organizational preparedness for AI-led transformation across five dimensions: Architecture, Operations, Trust, Workforce, and Value. Each dimension is scored on a scale of 1 to 5.

Organizations with AI embedded across core business functions recorded an average Index score of 4.1, compared with 2.7 among organizations still evaluating AI opportunities. These findings suggest an association between digital workplace readiness and progress in enterprise AI adoption.

The results also highlight the importance of evaluating workplace capabilities alongside AI deployment. Infrastructure, operational processes, security, employee readiness, and the ability to measure business outcomes all contribute to an organization's capacity to scale AI initiatives.

Continuous Measurement Helps Identify AI Value

The research distinguishes between measuring AI's broader business impact and continuously connecting AI use to workflow outcomes to guide investment decisions. Only one in 10 organizations reports having established this more mature measurement capability.

Metrics such as process cycle times, repeat incidents, and outcome quality can help organizations determine whether AI is improving end-to-end business processes. Rather than relying exclusively on individual productivity measures, workflow-level performance indicators provide a broader basis for evaluating AI initiatives and determining which applications should be expanded, revised, or discontinued.

“Every company we’re talking to is asking the same thing: what value are we actually getting from AI? That’s where workflow-level measurement matters. Are cycle times down? Are repeat incidents falling? Is the outcome better? That’s how you show where AI is creating value,” said Rakshit Ghura, Vice President and General Manager, Lenovo Digital Workplace Solutions.

Human-Agent Collaboration Requires Defined Roles and Support

The study also identifies gaps in how organizations prepare employees to work alongside AI systems and agents.

Although 70% of organizations have an AI adoption program, only 12% measure adoption and effectiveness at the individual or team level and use those findings to refine training, employee personas, and technology decisions.

Workforce role definition is another area requiring attention. Organizations are exploring how AI agents may change employee responsibilities, but fewer have formalized workforce models that define how people and AI agents will work together.

The report recommends identifying which routine tasks can be performed by AI agents and where human judgment, creativity, accountability, and oversight remain necessary.

Workplace readiness also extends to the underlying technology and operational environment. Organizations must consider where AI workloads run, whether IT support teams can anticipate and prevent problems, and how AI tools, agents, and data are governed. These capabilities are interconnected elements of an enterprise operating model rather than isolated technology initiatives.

Assessing Readiness Across the Enterprise

Rather than recommending a single implementation sequence, the report suggests that organizations assess all five dimensions of workplace readiness and prioritize the gaps most likely to affect their immediate AI objectives.

For IT leaders, this means evaluating more than technology deployment. Infrastructure capabilities, operational support, employee readiness, security, governance, and performance measurement all influence whether AI initiatives can move from limited applications to broader enterprise adoption.

“AI cannot deliver its full value in a workplace designed for the pre-AI era. The opportunity is to redesign how people and AI work together, with the technology, support and governance around them built for how work is changing,” concluded Ghura.

Source: Lenovo

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