Asking Better Questions About Generative AI

Imagine this: You’re sitting at your desk, reviewing a business proposal powered by generative AI, when a question strikes you. Not about the proposal itself, but about the technology shaping it. How do we know if we’re asking the right questions to harness AI effectively? If this feels personal, it’s because it should. In the era of generative AI (GenAI), the power isn’t just in the answers AI provides but in the questions we, as leaders, ask.

Today, we dive deep into the art of questioning GenAI—an essential skill for executives navigating a world where AI influences everything from decision-making to customer engagement.

The AI Gold Rush: A Double-Edged Sword

Generative AI is heralded as the next big disruptor, akin to electricity or the internet. It can summarise reports, draft contracts, or even suggest strategic moves. But beneath the allure lies a reality: AI will only ever be as insightful as the people wielding it.

Take the story of a global consulting firm that implemented AI to enhance client solutions. On the surface, it was a success—efficiency skyrocketed, and clients were impressed. But internally, employees faced burnout, as expectations of productivity climbed disproportionately. The technology worked, but the questions driving its implementation didn’t consider human well-being.

This isn’t just a case study; it’s a cautionary tale. Leaders must ask better questions not just to avoid pitfalls but to unlock the full potential of AI.

Stephanie Creary’s Call to Action: Balancing Efficiency and Humanity

Stephanie Creary, a management expert from the University of Pennsylvania, poses a critical question: How do we balance AI’s efficiency with employee well-being? AI can enhance productivity, but unchecked, it risks amplifying workloads and stress.

For example, consider a multinational enterprise that introduced AI-powered tools for project management. Employees initially celebrated the streamlined workflows. But soon, the AI’s relentless optimization meant workers struggled to keep up with the increased pace. Turnover spiked, and engagement plummeted.

As executives, the burden is on you to interrogate AI adoption beyond technical feasibility. Ask:

• Will this technology support or hinder our team’s capacity?

• Are we considering mental and physical limits in our AI-driven workflows?

• How can we use AI to foster, not diminish, a culture of well-being?

This line of questioning isn’t just ethical—it’s strategic. Thriving employees are a company’s most valuable asset.

The 3 Es: Questions Leaders Can’t Delegate

Philosopher Pia Lauritzen emphasizes that while AI excels in answers, leaders must own the questions. She introduces the “3 Es” framework—three existential questions no executive can delegate:

1. Essence: What values define our organisation?

2. Empowerment: How do we enable our people to reach their potential?

3. Evolution: Where do we want to take our company?

Let’s translate this into action. Imagine an AI implementation project where the focus is solely on ROI. It’s tempting to delegate the intricacies to AI experts or consultants. But if leaders don’t address the “Essence” question, the AI might inadvertently reinforce biases or misalign with organisational values.

Pia’s insight reminds us that some questions demand human judgment. These questions aren’t just about GenAI; they’re about the future you’re building.

Sinan Aral’s Challenge: The Scarcity of Great Questions

MIT’s Sinan Aral makes a provocative observation: In a world dominated by AI answers, the ability to ask the right questions becomes the rarest and most valuable skill.

Think of GenAI as an oracle. It’s powerful but reactive. It thrives on clear, well-defined inputs. Yet, many executives fall into the trap of asking generic questions like, “How can AI help us?” instead of insightful ones like, “What unique problems can AI help us solve that we couldn’t solve before?”

Here’s a framework to guide your questions:

• Insight-driven: Does this question tap into a deeper understanding of our market or operations?

• Outcome-oriented: Is it aligned with a specific, measurable goal?

• Ethically grounded: Does it reflect our commitment to doing what’s right?

By refining your questioning techniques, you don’t just improve AI’s output—you redefine your organisation’s trajectory.

Real-World Case Study: Transforming Questions into Results

A global healthcare firm recently adopted generative AI to streamline patient services. Early iterations focused on obvious applications like appointment scheduling. But leadership, inspired by the “3 Es,” asked: What more can we achieve if we rethink our core processes?

This reframing led to breakthroughs. AI was used to personalize treatment plans based on patient data, reducing hospital readmissions by 20%. Employees were retrained to collaborate with AI tools, increasing satisfaction rates among staff and patients alike.

The takeaway? The questions leaders ask determine the scope and impact of AI. Narrow questions yield incremental improvements; expansive, strategic questions unlock transformational change.

Practical Steps for Executives: Start Asking Better Questions

If you’re ready to elevate your approach to GenAI, here’s how to begin:

1. Audit Your Current Questions

2. Build Cross-functional Teams

3. Invest in Questioning Skills

4. Engage Ethically

The Final Question: What’s Next for You?

As you close this article, I leave you with one final, personal question: What will you ask next? Whether you’re exploring GenAI for efficiency, innovation, or transformation, remember that the journey starts not with technology but with your curiosity.

AI is reshaping industries, but it’s the leaders who ask bold, insightful, and ethical questions that will shape the future.