Searching for impact, not speed

Over the past year, AI has shifted from future state to workplace reality. In many organizations, the question is no longer whether AI will have an impact, but how quickly that impact will be felt and where it will create the most value.

McKinsey reports that 92% of companies plan to increase AI investment over the next three years, and only 1% of leaders say their organization is “mature” in AI deployment.

That urgency is understandable. Tools are evolving quickly, expectations are rising, and the fear-of-missing-out is palpable. McKinsey reports that 92% of companies plan to increase AI investment over the next three years, and only 1% of leaders say their organization is “mature” in AI deployment.

But the businesses that will benefit most from AI will not be the ones that chase every new development. They will be the ones that understand where friction impacts work today, where better insight is needed, and where technology can genuinely help people perform better.

Staying out of the race

One of the biggest workplace developments in AI has been the sheer pace of its growth. In the past three years, more and more businesses have set AI-related targets, adopted AI-enabled workflows, and encouraged employees to engage with both general-purpose and domain-specific AI tools.

But this pace pales in comparison to the speed AI is developing. Technology always evolves faster than business readiness to adopt, but the constant coverage and media fascination with AI development and impact creates a sense of pressure, and often a fear of missing out.

Workplace leaders don’t need to treat AI as an arms race. In practice, the biggest gains rarely come from using the newest tool first. In fact, only 29% of businesses have reported ROI gains from generative AI.

The value comes from redesigning work, and the technology ecosystem that supports it, with more intention. If an organization understands where delays, duplication, low-value admin, or poor user experiences are holding people back, it is in a far stronger position to re-design with clear purpose rather than simply retrofitting AI into existing flows.
 

Understanding the workplace

Identifying the true impact AI tools can make matters because the workplace is becoming far more measurable than it once was. Across buildings, services, support requests, occupancy patterns and employee feedback, organizations are collecting more and more information. And while many businesses are now data rich, they are equally insight poor. 

This is where AI can have a very practical impact. It can help surface patterns, connect signals across multiple datasets, and identify issues leaders may not have known to look for. A good example is operational data that sits across multiple sites and systems. On its own, that information can be too fragmented and too detailed to interpret at scale. With AI, teams can start to identify broader trends, such as where workplace processes are breaking down, why resources are being used inefficiently, or which behaviors are creating avoidable friction. 

AI has the capability to turn that data into something more visible, more actionable, and ultimately more valuable to senior decision-makers.

As workplace experience receives more board-level attention, the ability to measure and explain value becomes increasingly important.  AI does not replace leadership judgment, but it can make the business case clearer. It can help leaders move from saying: “we think this matters” to quantifying why it matters and what should happen next. It achieves this by unlocking the value in unstructured data is a vital step to taking evidence-based workplace decisions.
 

Connecting the disconnected

Another area AI can have an impact is fragmentation. In many organizations, the employee experience is still spread across disconnected systems, inconsistent workflows, and layers of support. This leads to friction and frustration for employees – for example, Gensler found that two-thirds of employees are “hacking” their workspace to compensate for performance gaps.

It’s not about moving faster because the tech is rapidly developing, it’s about applying it thoughtfully, with clear goals and awareness of how it impacts the overall ecosystem.

AI can help here, but it is important to be realistic about how. Just saying your workflows are “AI-powered” won’t automatically fix siloed systems or weak process design. What it can do is improve the experience at the front end, making it easier for employees to interact with through agents, assistants, and more intuitive interfaces. 

And again, it can better utilize unstructured information that sits inside tickets, feedback comments, and other text-heavy systems that have traditionally been difficult to analyze. In that sense, AI can act as a bridge between fragmented experiences and better decision-making. But it still depends on strong controls, sound governance, and an underlying commitment to building a more effective workplace.

Identifying impact

For me, this is the real opportunity in workplace AI. It’s not about moving faster because the tech is rapidly developing, it’s about applying it thoughtfully, with clear goals and awareness of how it impacts the overall ecosystem. Using AI support to remove friction, turn information into insight, and create workplace experiences that are easier, more connected, and more effective offers tangible value for the users. 

There will continue to be uncertainty, and the tools themselves will keep changing, but organizations do not need to be on the cutting-edge to move forward. Just clarity on where value lies, confidence in the problems they are trying to solve, and the discipline to apply AI in ways that support better work.