Despite widespread recognition that artificial intelligence (AI) will reshape business operations, only one in 10 organisations have fundamentally redesigned their digital workplaces to support AI-led transformation, highlighting a gap between technology adoption and workplace readiness.
According to Lenovo's sixth Work Reborn report, The AI-ready workplace, eight in 10 IT decision-makers consider digital workplace redesign critical to successful AI transformation. However, only 10 per cent say their organisations have made fundamental changes to how work is structured around AI.
Based on an August 2026 survey of 1,200 IT leaders at organisations with at least 1,000 employees across 12 countries, the study found that 76 per cent rank AI-led transformation among their organisation's top IT priorities. Yet, only 27 per cent have scaled AI across business functions.
The findings suggest that deploying AI tools does not necessarily translate into organisational transformation, with many enterprises still struggling to integrate the technology into everyday workflows.
AI adoption needs broader workplace redesign
The report argues that becoming AI-ready requires more than introducing new tools. Organisations must rethink workflows, employee responsibilities, IT support systems and governance frameworks to enable employees and AI agents to work together effectively.
When AI deployment remains restricted to individual functions, its potential value can remain trapped in organisational silos, limiting the ability to translate technology investments into measurable business outcomes.
Lenovo's AI Workplace Readiness Index assesses organisational preparedness across five dimensions: Architecture, Operations, Trust, Workforce and Value, each measured on a scale of one to five.
Organisations that have embedded AI across core business functions recorded an average score of 4.1, compared with 2.7 among those still evaluating AI opportunities. The findings indicate a relationship between digital workplace readiness and progress in scaling AI across enterprises.
Few organisations measure AI's impact on business outcomes
The study also identified gaps in how organisations evaluate the returns from AI investments.
While many enterprises track the broader business impact of AI, only one in 10 continuously connects AI usage to workflow outcomes and uses those findings to guide further investments.
The report recommends measuring indicators such as process cycle times, repeat incidents and outcome quality to determine whether AI is improving end-to-end workflows. These measures can help organisations decide which AI applications to scale, revise or discontinue, rather than relying solely on individual productivity metrics.
"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 of Lenovo Digital Workplace Solutions.
Human-AI collaboration requires clearer role definitions
Workforce readiness is another area where organisations are falling behind. Although 70 per cent of surveyed organisations have an AI adoption programme, only 12 per cent measure adoption and effectiveness at individual or team level and use the findings to refine training, employee personas and technology decisions.
The report also found that organisations are exploring how AI agents could reshape job responsibilities more frequently than they are formally defining human-agent workforce models.
It recommends establishing clear boundaries between tasks that AI agents can perform and responsibilities that require human judgement, creativity, accountability and oversight.
Beyond workforce planning, AI readiness also depends on where workloads are hosted, whether IT support systems can anticipate and prevent technical issues, and how AI tools, agents and data are governed.
The report recommends that IT leaders assess all five dimensions of workplace readiness and prioritise gaps that could constrain their immediate AI transformation objectives.
"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," Ghura said.