When it comes to AI, there’s a big question leaders should be asking right now, and it’s probably not the question they’re actually thinking.
It’s not, “Is my company adopting AI?”
It’s, “Is AI actually improving business performance and employee well-being?”
Gabriela Mauch, ActivTrak’s Chief Customer Officer and Head of the Productivity Lab, recently joined Michael Waitze, host of A Global Tech Podcast, to unpack what organizations are getting right and wrong as they measure AI’s role in work. Together, they dive into how technology is shaping the way organizations operate, innovate and scale through conversations with industry leaders, founders and technologists.Here are the top five takeaways from their discussion.
Top 5 AI impact takeaways for executives
Gabriela took Mark through five important considerations many executives probably aren’t thinking about when it comes to AI today, and why they matter:
1. Adoption is not the same as impact
The most common mistake business leaders make is equating adoption with impact. Counting how many of your employees use AI – and maybe even how often they use it – is a great metric to start with, but it doesn’t give the full picture. What’s more important is measuring how AI changes work.
The big question is: How can you measure how AI actually impacts work? This is where productivity metrics come into play. When linked properly to AI usage data, productivity metrics show whether AI is leading to gains in speed, output quality or employee experience.
2. AI value looks different depending on the role
AI means different things to different employees, and leaders need to keep this in mind. Some may see AI as a threat to their entire job, while others view it as a way to improve work or work faster. For example, a salesperson may use AI to better understand clients, while a software coder worries a new AI program will automate them out of a job. The uncertainty can make some employees more hesitant to adopt AI than others, and cause emotional responses that lead to disengagement.
Understanding this changes how leaders drive adoption. Instead of demanding teams use AI, leaders need to show employees how to use it to drive productivity and free up time for deep thinking. Leaders should also focus on educating employees who may feel threatened by AI, rather than roles where the benefits are already clearly, so you can better direct time and resources toward AI adoption policies and training.
3. Measuring AI impact requires multiple metrics
Many leaders measure AI impact by looking solely at operational metrics. It makes sense to measure how AI usage improves productivity and efficiency, especially if you need to justify the cost of AI investments. But executives also need to consider how AI impacts the workforce as a whole, including company culture and individuals within the organization.
AI use can have ripple effects throughout an organization, which are sometimes negative if AI isn’t implemented mindfully. Beyond daily or weekly output, focus time and quality of work, managers need to monitor employee well-being metrics like disengagement and burnout to determine if AI is helping or hurting in these areas. You can also monitor behavioral change over time to see how AI changes the way employees work. Paired with sentiment surveys and feedback tools, executives can understand how AI is impacting the organization and individuals from a more emotional, cultural level, and make changes as needed.
4. Successful organizations do more than add tools
As with any big workforce transformation, AI adoption should be strategic and mindful. The organizations that do the best work with AI are redesigning their operations around the new tools as they come in, rather than adding AI automation on top of existing workflows and hoping for the best. This means focusing on redeployment, reallocation and upskilling, rather than using AI to reduce headcount. Leaders need to preserve institutional knowledge and move talent into higher-value work.
A good comparison is to think about how remote work has changed since the 2020 pandemic, when so many knowledge workers were sent home with their laptops to figure out how to get work done on their own. Now, distributed workforces provide much more support, including tools, technology and policies designed for remote work success. The same is true of companies doing the best with new AI tools: They’re finding ways to restructure work so it fits the new paradigm while keeping the human impact in mind.
5. The data on AI’s impact is still coming in
The last point Gabriela drove home is that our understanding of AI’s impact on the workforce is still very new. While ActivTrak has been tracking productivity metrics and workforce insights for years, AI use didn’t really explode until very recently.
As AI adoption continues to increase, tools like ActivTrak’s AI Insights will provide even more data on how AI impacts workforce performance, leading to new benchmarks and best practices for a variety of industries. We’re just getting started with seeing how AI changes work, and what changes leaders should make to maximize what AI can do for their organizations.
Start answering the right questions about AI with ActivTrak
AI’s true business value doesn’t come from measuring adoption as a sole metric. Instead, leaders need to measure how AI changes work and whether the business is truly getting better outcomes as a result.
Leaders will also need more tools like ActivTrak’s AI Insights to monitor AI’s impact on productivity, operations, compliance and performance if they want to truly understand how AI is helping (or hurting) their business. As datasets on AI at work continue to grow, insights into what works will drive organizational change for businesses of all sizes and separate the winners in the AI race from those who’ve been left behind.
Watch the full interview here.
