Workplace AI: From what employers want to what employees need 

Workplace AI can look successful on paper and even deliver business improvements while still falling short of what employees actually need. An AI-enabled intranet might answer thousands of questions and speed up operations, but in the process create overwhelm and surface noise that doesn’t apply to employees’ daily work. That leaves people to figure out what’s relevant on their own, harming trust on an organizational level.  

Sophie Hamblett, Senior Content Marketing Executive at Interact, explores why employee experience deserves a place alongside productivity in assessing workplace AI tools. 

How do employers’ AI priorities differ from employees? 

Employers’ workplace AI priorities tend to differ from employee needs because leadership platform decisions often prioritize organization-wide targets for productivity, efficiency, and cost savings. Those are important goals, but they don’t always account for how a new technology serves employees in their day-to-day work. A rollout can meet broad targets while leaving the everyday problems of information overwhelm and access chaos unresolved. 

Launch metrics for an AI-enabled intranet typically include how many employees signed in, how many questions the platform answered, or estimates for how much time new processes are saving. Organizations should still be tracking these metrics. However, they won’t show whether a frontline employee found guidance that applied to their specific location, whether a new hire was presented directly with the steps to take to complete onboarding, or whether an action was completed to employee satisfaction. 

Research shows organizations are failing to provide their employees with workplace tools that keep them happy and productive. One Gartner survey found that just 23% of digital workers were completely satisfied with their work applications. The same research found that workers satisfied with their applications were nearly three times as likely to report being much more productive than those who weren’t. Although the findings weren’t specific to AI in the workplace, they nonetheless draw a direct line between employee experience, workplace tooling, and perceived productivity.  

“Without that knowledge, leaders risk leaving the same frustrations unresolved and missing opportunities to improve productivity.”

For organizations investing in AI-enabled intranets, this reinforces the importance of understanding what employees struggle with before introducing new capabilities and tools. Without that knowledge, leaders risk leaving the same frustrations unresolved and missing opportunities to improve productivity.

Employee needs should therefore help determine which AI capabilities organizations prioritize in their digital workplace solutions, and how they measure success. Productivity and efficiency matter, but are underpinned by whether those investments make employees’ everyday work easier, and therefore more valuable.

“Productivity and efficiency matter, but are underpinned by whether those investments make employees’ everyday work easier, and therefore more valuable.”

What do employees need from AI in the workplace?

Employees need AI in the workplace that can recognize who they are and what matters to them in the moment. In short, a combination of personalization and relevance. Personalization helps them see information that fits their role, location, and responsibilities. Relevance keeps that information useful as their priorities change throughout the day, rather than delivering a customized but static feed.

Take a national retailer with an AI-enabled intranet that serves the entire workforce. A store associate needs local shift updates, checkout procedures, and customer-service policies. A payroll manager needs payroll deadlines, approval requests, and reporting guidance. Each employee should see communications, tools, and features that reflect their role and location, rather than navigating the same company-wide information. That’s personalization.

But relevance adds another dimension. Before a store opens in the morning, that same associate might need their daily shift briefing. Later, a new, urgent safety policy might require their acknowledgment before they end their shift. Their role and location haven’t changed, but what needs their attention has. A relevant experience brings that priority forward instead of leaving it buried among information that normally applies to their job.

This is an important distinction for AI and employee experience. A personalized employee experience means employees don’t have to filter out information intended for someone else. A relevant and adaptive intranet experience.  means they don’t have to sift through everything that applies to them to identify what matters right now. When a workplace platform can use AI to do both, it saves employees time, helps them respond to immediate priorities, and enables them to do their best work.

Why isn’t a faster AI answer always a better employee experience?

A faster AI answer doesn’t necessarily improve the employee experience because speed alone can’t guarantee useful, trustworthy guidance. Employees still have to establish whether information is current, relevant to them, and clear enough to act on. If those checks create more work, any apparent time saving is misleading.

“If those checks create more work, any apparent time saving is misleading.”

As Simon Dance, CEO of Interact, asks in his introduction to What employees actually need from AI: “More can be achieved faster – but is the work better?”

For example, picture an employee asking their organization’s AI-enabled intranet how to submit expenses after a client visit. It returns an accurate summary of the company’s expense policy instantly. But the answer doesn’t account for the employee’s location, where different reimbursement rules apply, or direct them to the form they need to complete. They’re left searching for the information that applies to them and figuring out how to submit their claim. The platform answered the question quickly, but the employee still hasn’t accomplished what they came to do.

Speed matters only if it reduces the time and effort employees spend getting something done. An AI-enabled intranet may draw on reliable organizational knowledge and return an answer in seconds, but if employees then have to work out which guidance applies to them or search for their next step, much of that benefit is lost. The better measure is how quickly employees can resolve their need, not how quickly the platform responds.

How can you tell if your workplace AI is actually useful?

Workplace AI is useful when employees can find information that applies to them, identify what needs their attention, and move forward without unnecessary searching or handoffs. Relying on usage figures or total number of AI answers delivered won’t paint a full picture here. To truly assess usefulness, platforms should be tested against how they support everyday employee queries and tasks.

The employee usefulness test below provides three questions to ask when evaluating a new AI-enabled intranet or employee experience platform, during a pilot, or after launch.

The employee usefulness test for workplace AI

Test	Question to ask	What good looks like	What poor looks like
Personalization	Is the answer right for the employee seeing it?	The answer fits their role, location, and access permissions	Everyone receives the same broad guidance
Relevance	Is the answer relevant to them right now?	Current information is prioritized for the immediate need	Outdated or lower-priority content gets in the way
Access	Can the employee use the answer to move forward?	The employee can decide what to do or take the next step	An employee would have to restart their search or contact someone else

To put the test into practice, think of an example that would apply to your own workplace, for example an employee who needs to complete mandatory training. Does the platform show the training required for their role and location? Can it prioritize courses with approaching deadlines over less urgent information? Can the employee access the appropriate training easily, even if it’s hosted in another system?

If you’re evaluating an AI intranet platform right now, ask the potential vendor to demonstrate a similar scenario and explain what data and integrations are needed to support it. During a pilot or after launch, test it with real employees in different roles and locations. This can reveal where the experience may fall short and where improvements to personalization, relevance, or access could make a difference.

How do you decide which workplace AI best supports your organization?

Decisions about which workplace AI to implement should incorporate feedback from employees across the organization, alongside input and observations from internal communications, HR, IT, and operations. Involving employees throughout the process, from vendor selection to post-launch evaluation, helps leaders avoid judging a platform only against the goals of the team that advocated for and purchased it.

Treating AI and employee experience as connected priorities changes everything from the questions you ask an AI intranet vendor in a demo to how you evaluate success and make improvements after the solution goes live. It helps you look beyond features to determine whether a platform will truly support the workforce it was introduced to help.

What’s the best way to do this? Prior to the vendor selection process and throughout the rollout of any new platform, use surveys, focus groups, informal conversations, and everyday workplace observations to explore where the employee experience falls short. Keep an eye out for the types of questions people can’t resolve, updates they miss, or digital workplace tasks that are difficult to complete, like checking schedules or booking time off.

How can workplace AI make personalization and relevance an organization’s advantage?

Workplace AI helps organizations personalize intranet experiences for large workforces and keep information relevant as employee needs change. Doing that involves work employees never see: keeping policies current, targeting communications to different groups, and connecting answers with the next steps people need to take. To make it all work, the teams running the intranet need tools that make those jobs easier.

Interact is approaching this challenge from both sides. Cue, an AI-native intranet, adapts what employees see in real time and delivers relevant answers and the next steps they need to take. Conductor supports the teams behind the intranet experience, helping them manage communications, content, and intranet operations. Together, they help organizations deliver more relevant experiences for employees while reducing the work involved in managing them.

The success of workplace AI should ultimately be judged by how well it serves employees alongside the productivity and efficiency it delivers for the organization. Personalization and relevance are central to this. The real test for organizations evaluating new or existing workplace AI tools is whether employees can find what they need, see what’s important to them right away, and get things done with less effort.