A two-tier AI workforce is emerging across organisations

Why inconsistent AI experiences are limiting productivity gains and business value.

AI-led transformation is moving from experiment to execution across Asia Pacific. Organisations are investing in new AI tools and platforms to improve productivity, efficiency, and business performance.

But beyond the boardroom, something very different is happening.

Employees are adopting AI faster than many organisations can support and consistently govern it. AI usage inside many organisations remains ad hoc, often driven by enthusiastic individuals rather than clear enterprise strategy.

At the same time, AI governance frameworks and regulations are evolving across APAC markets, increasing pressure on organisations to manage AI use more consistently whilst maintaining compliance and reducing operational risk.

But many organisations still rely on disconnected AI tools that lead to uneven employee practices. As Lenovo’s latest Work Reborn research “Leading your workforce to AI triumph” highlights, the gaps between AI adoption and organisational readiness are growing.

Without stronger guidance and governance, disjointed employee AI adoption can create fragmented workflows, uneven productivity gains, and growing security and compliance loopholes. This fragmentation brings risk and crucially reduces the return on AI investments.

A divided approach dilutes AI-led transformation

Many employees still lack the tools and support they need to use AI effectively. Lenovo’s research reveals that almost one in four employees (24%) say their employer does not provide AI tools at all, while over a third (35%) receive no AI training.

This is creating a two-tier workforce:

On one side are employees with access to IT-managed AI tools, guidance and oversight. They are more likely to have guardrails, policies, and training that help them use AI productively and responsibly.

On the other side are employees who rely on unmanaged AI: public tools, unapproved plugins, or isolated experiments.

Because employees are so central to how AI is actually used day to day, this divide matters. Different teams begin to work in very different ways, using different tools, following different practices, and getting very different results. Over time, this fragmentation can limit collaboration, slow decision-making, and dilute the impact of AI-led transformation initiatives.

The difficulty for leaders is clear: the more AI spreads informally, the harder it becomes to steer it toward improving productivity, standardising ways of working, and strengthening ROI.

Employees want AI embedded into their daily work

Lenovo’s Work Reborn research shows that half of employees (50%) want AI woven into core workflows: smart assistance inside productivity suites and collaboration tools; proactive help resolving IT issues and reducing workplace friction; and automation of repetitive, low-value tasks that erode focus and morale.

Essentially, employees expect AI to reduce friction. Yet many organisations continue to roll out separate AI tools that sit outside everyday work. Employees find themselves constantly switching between systems, juggling multiple interfaces, and trying to reconcile different ways of working across teams and functions. 

The result is a patchwork of AI experiences that makes it harder to standardise workflows, measure impact and deliver consistent productivity gains across the business. AI becomes something you “go to” rather than something that is simply part of how work gets done.

Business value now depends on consistency

Lenovo’s research is clear: business value now depends on consistency. Organisations will struggle to scale and measure AI impact if employee experiences remain fragmented and uneven.

Inconsistent AI usage leads directly to: conflicting processes and standards that make collaboration harder; increased security, privacy, and compliance risks from unmanaged tools; and a weaker return on AI investments, as point solutions fail to add up to real transformation.

Organisations that treat AI as a collection of disconnected experiments will find it difficult to prove value to the board, meet rising regulatory expectations, or sustain employee trust.

By contrast, those that build a clear, consistent, and well-governed AI experience will be far better placed to turn enthusiasm into measurable outcomes.

Three priorities for leaders who want to turn AI investment into business value

The Work Reborn report sets out a practical agenda for leaders who want to turn fragmented AI usage into a coherent, high-performing digital workplace.

1. Lay the foundations

   Make accountability for AI explicit across tools and teams.
   Create guardrails that support experimentation without losing control.
   Align AI use with broader business and transformation objectives.

2. Unlock real value

   Ensure tools and training are relevant to individual roles.
   Apply AI to core business processes so routine tasks can be automated.
   Focus on use cases that deliver measurable productivity and efficiency gains.

3. Integrate and scale

   Enable natural language interaction across enterprise platforms.
   Focus on orchestration across workflows, not isolated tools.
   Standardise AI experiences to ensure consistent outcomes at scale.

From fragmented experiments to AI triumph

Across APAC, many organisations are now at a pivotal moment. They have made significant investments in AI, but lack a clear plan for how employees will use it in their day-to-day work.

If they continue on the current path, they risk deepening the two-tier workforce divide, amplifying operational risk, and missing the full potential of their AI spend. If they act now to deliver consistent, role-relevant, and well-governed AI experiences, they will be better positioned to scale productivity, reduce risk, and realise the full business value of their AI investments.

The organisations that succeed will not be those with the most AI pilots, but those that align employees, tools and governance to turn AI investment into consistent business results.

To dive deeper into how employees are using AI at work today and what this means for the future workplace, read the full Lenovo Work Reborn report, Leading your workforce to AI triumph.

Rakshit Ghura
Vice President and General Manager of Digital Workplace Solution

Rakshit Ghura is the Vice President and General Manager of Digital Workplace Solutions (DWS) at Lenovo, where he leads the
company’s strategic initiatives in the digital workplace and cybersecurity domains.

In this role, Rakshit is instrumental in shaping Lenovo’s vision for the future of work, focusing on areas such as workplace mobility, Device as a Service, Persona-based configuration, automation, analytics, employee experience, and collaboration, with a strong emphasis on consulting and advisory services.

Prior to joining Lenovo, Rakshit served as the Senior Vice President and Global Head of Digital Workplace Services & ServiceNow
business at HCLTech. During his tenure, he was responsible for defining, incubating, and creating the product roadmap and strategy for digital workplace services.

Rakshit is a recognised thought leader in the industry, frequently sharing insights on the impact of Generative AI, the evolution of the hybrid workplace, and the importance of unifying people, culture, and technology to redesign the future of work. He has contributed to various industry discussions, including podcasts and whitepapers.