What skills or mindsets do you see as most essential for thriving in an AI-integrated workplace?
Integrity is where I would begin, as it underpins our Leadership Character Model. Technology amplifies our ethical decisions, so starting with integrity is key. For our human organizations to thrive, it is critical that we use these new generative AI tools responsibly, in a way that aligns with our values. Integrity ensures that our decisions align with our values, not just speed or cost. That could mean becoming an advocate for responsible AI use in your organization to protect data privacy, eliminate bias, and ensure transparency. It could also mean advocating for AI that uses less natural resources or is trained on ethically sourced data.
Judgment and reasoning skills are also essential, because AI outputs are not infallible. Human judgment is critical for validating results, managing risk, and deciding when to override automation. Just because we can doesn’t mean we should.
Lastly, adaptability and a growth mindset are absolutely vital. If we can approach these technologies with openness and curiosity, there is so much opportunity to innovate and scale our impact. New capabilities are coming so fast that it is hard to keep up. By staying curious, we can adapt to this rapid change through continuous learning and experimentation. We can lead by jumping in and helping to create clarity from ambiguity.
Many people fear being replaced by AI. From your vantage point, how can professionals position themselves to stay relevant and indispensable as AI tools evolve?
You can stay relevant by adapting and keeping a growth mindset. Don’t let fear keep you from exploring the technology. Imagine that you’ve been assigned a new AI intern that is extremely capable in certain areas but can make serious mistakes and needs a lot of direction and oversight. Those who find creative ways to use generative AI to scale their own work and share their learnings with others will stand out. Rather than dwelling on how AI might do certain things better or faster than you, focus on what you can do now that you couldn’t do before. The world needs your creativity and your conscience.
As a software engineer, I can certainly empathize with the fear of being replaced, since writing code is the number one skill that large language models are being optimized for! All the excitement around AI has brought us a lot of wild speculation, both positive and negative. Ironically, AI-driven social media algorithms feed us the most fear-inducing stories about AI because that is what people click on. I do expect that there will be major impacts on the way we work in the long run, but I think it will be slower than the hyperbolic marketing would have us believe.
In my view, the fear of being replaced by AI is really rooted not only in economic uncertainty but also in the uneven distribution of technological benefits, which has left many wondering whether progress will truly lead to greater prosperity for all. In his 1930 essay “Economic Possibilities for Our Grandchildren”, economist John Maynard Keynes predicted that technological progress and capital accumulation would make societies so productive that scarcity would largely disappear within 100 years (5 years from now). We have indeed seen productivity rise with industrial automation, but the fruits of that productivity have not been shared as broadly as he imagined they could. In fact, the prospect of AI replacing jobs offers the potential for immense good—if, and only if, we seize the opportunity to reimagine our economy and push our political leaders to ensure that the extraordinary productivity gains brought by AI are shared broadly, not hoarded by a few. The real source of fear is not AI itself, but our current social contract in which survival depends on having a job. This is the elephant in the room. As AI lifts the burden of necessary labor, we must address the deeper question of how we organize society so that everyone can benefit from technological progress, embracing new possibilities for contribution, fulfillment, dignity, and shared prosperity beyond mere employment.
Organizations are rapidly adopting AI, but not everyone moves at the same pace. What can leaders do to create a culture where AI is embraced as an enabler rather than a threat?
Invest in your people. Provide opportunities for those interested to learn AI skills. Show through your actions that your goal is to empower, not replace. If you can provide psychological and financial safety, your top performers will feel much more excited about exploring ways they can use AI to execute faster, help the company thrive, and lift all boats.
What do you think AI fluency should look like for professionals who aren’t in tech roles?
That’s a good question. I’ve been studying AI for over 30 years, and the idea that non-tech folks need to “use AI” is still quite new. It’s important to recognize that generative AI is just one kind of artificial intelligence. Many other forms of AI are working behind the scenes in our daily lives, powering things like search engines, recommendation systems, fraud detection, and logistics optimization. These types of AI are often invisible and so widespread that we rarely notice them.
What is especially new for professionals outside of traditional tech roles is the growing presence of generative AI tools such as Copilot, Claude, and ChatGPT. These tools are designed specifically to help with work by enabling users to interact directly through natural language. This makes them accessible to people regardless of their technical background. For most professionals, AI fluency is not about understanding how algorithms work or learning to code. Instead, it is about learning how to use these generative AI tools thoughtfully to improve daily work. This includes knowing how to ask effective questions, how to critically assess outputs from AI, and how to spot opportunities where AI can drive efficiency or encourage innovation.
Developing a comfort with experimenting, understanding ethical considerations, and looking proactively for ways to integrate AI into business processes are all important aspects of AI fluency. By focusing on practical application, clear communication, and responsible use, non-technical professionals can use generative AI as a collaborative partner. This mindset helps transform technological progress into outcomes that are meaningful and centered on people.
If you’re interested in learning more about AI and developing your skills, Microsoft offers a free AI Skills Navigator, which I helped to develop. This resource offers guided pathways for a wide range of experience levels and is an excellent starting point for anyone looking to build greater AI fluency, particularly if your organization primarily uses Microsoft tools: https://aiskillsnavigator.microsoft.com/
I also recommend seeking out training and resources tailored to how these tools are being used in your particular industry or field. Many organizations and platforms now offer industry-specific workshops, webinars, and certification programs that provide hands-on experience and practical guidance for leveraging AI in context. By choosing training relevant to your professional environment, you’ll gain insights into best practices, understand regulatory considerations, and discover new ways AI can enhance your workflow and impact.
How should leaders decide what skills to invest in developing versus what to delegate to AI?
Delegating business processes to AI without a deep understanding of those processes you are automating is a recipe for costly mistakes. I would encourage leaders to empower the people doing and managing the work to experiment with AI and find out what job functions can be effectively automated. Dedicated hackathons and working sessions around AI automation can be helpful for this. Provide training opportunities for your employees who want to become fluent in AI tools, and find ways to incentivize collaboration across teams to share insights and best practices as they emerge. It’s essential to foster an environment where learning is continuous and open experimentation is encouraged, so teams can build both confidence and competence as they navigate which skills to nurture internally and which tasks are best delegated to AI. This approach not only mitigates risk but also ensures that automation aligns closely with your organization’s specific needs and expertise, reducing the likelihood of costly errors when implementing AI solutions.
Any final words for our readers?
Ultimately, AI is a human creation, and like all technologies since the discovery of fire, it holds great power. It is up to us to use it wisely.
