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Why boomers are catching up with AI faster than Gen Zers, according to Microsoft’s modern work lead

 


We’ve entered a new era of productivity–one that’s powered by generative AI. Already, a surprising skills gap has emerged: Digital natives, who we might expect to be at the forefront of this technological shift, are falling behind.

Unlike other technological tools that have come before, AI represents a new way of working. The key to unlocking the promised productivity gains of AI lies in a fundamental mindset shift: stop thinking of AI as a search engine–and start thinking of it as your newest direct report.

For the most tenured leaders, with years of people management experience under their belts, this shift has elements that are almost second nature. But for early-career employees who haven’t had the time and experience to develop these management skills, it’s a whole new ball game.

That’s the story we’re hearing from Microsoft customers, as well as our own employees. Based on our research, 65% of Gen Z employees say they don’t currently have the right skills to meet the demands of the AI era. A notable difference when compared to the 50% response we got from baby boomers.

Prioritize complexity over simplicity

I’ve been using generative AI tools at work for months now–and I never want to work without it again. In my experience, AI can tackle routine requests with ease. Ask it a simple question and you’ll get a simple answer.

However, relegating AI solely to these types of mundane assignments is a missed opportunity, because where it really shines–and where users are going to experience those tremendous productivity gains–is in the more complex and nuanced tasks.

Asking it to prioritize my tasks based on what’s top of mind for me today, analyzing options presented in a meeting I missed and recommending a decision, and brainstorming creative new names for an upcoming product feature, are the types of scenarios where AI saves me both valuable time and mental energy, freeing me to focus on the work that’s uniquely human, that only I can do.

Delegate with details

Just like you delegate work to an employee on your team, you’ll soon delegate work to AI. And, just like working with people, effectively delegating a task to AI requires clear communication.

Four ingredients are all it takes to get results that feel almost like magic:  

  • Goal: The response you’re looking for.
  • Context: Why you need it and who’s involved.
  • Source: Which information or samples AI should pull from.
  • Expectations: How it should respond to meet your needs.

So, while “What’s in my inbox now?” might yield some helpful results, I’ve found more specific requests, like: “List the five most important emails in my inbox that I’ve received in the past 24 hours. For each email, give a short summary, tell me why you thought it was important, and then give me a suggestion on what you think I should do,” generate actionable results that put me hours ahead.

However, the responses shouldn’t be taken at face value. Just as you work with a direct report, you’ll need to review what you get from AI, ask questions, and provide feedback to get the most useful, tailored response.

Working with AI is a deeply collaborative process. From start to finish, humans must remain in the driver’s seat–fully in control and responsible for making decisions.

The ability to break down multi-faceted projects, assign and evaluate work, and ultimately drive decisions and deliverables forward are skills we’ve traditionally thought of as most relevant to those who directly lead or manage people. That’s an assumption we’ll need to change.

Make every employee a manager

To get your organization ready for AI, you need to turn every employee into a manager by arming them with the managerial experience and skills they’ll need to thrive in this new era.

While prompt engineering is certainly a good place to start, the skills required to work with AI go so much deeper. Employees up and down the organizational pyramid need to learn how to think critically, solve complex problems, ask the right questions, and understand the dynamic factors at play both within and beyond the walls of the organization.

Some of these skills can be taught with training courses and how-to guides, but there’s just no replacing lived experience. Giving employees of all levels the opportunity to lead–whether formally or informally–is going to be critical. Within my own team, we’ve prioritized stretch assignments that require leading a cross-functional project or team, mentorship opportunities, and consistent feedback and coaching.  

The promise of AI has never been more real–but becoming an AI-powered organization doesn’t happen with the flip of a switch. It requires an intentional approach, with employee skilling at the core. Organizations that prioritize this kind of investment in their people are going to be the ones that reap AI’s benefits.

Jared Spataro is CVP of modern work and business applications at Microsoft.

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