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How Strategic Questions Drive Competitive Advantage in AI

In the rush to adopt artificial intelligence (AI), most organizations focus on tools and tech. However, the real competitive edge comes from something far less obvious: asking the right questions. This post explores how closing the “inquiry gap” leads to smarter decisions, sharper strategies and measurable business value.

Listen to “How Strategic Questions Drive Competitive Advantage in AI” Deep Dive.

Why Questions Matter More than Answers in AI Strategy

Known as the “father of modern management,” Peter Drucker once noted that “The most serious mistakes are not being made as a result of wrong answers. The true dangerous thing is asking the wrong question.”

This insight is particularly relevant today as companies rush to implement AI, the strategic value of which doesn’t necessarily equate to vast amounts of data for Large Language Models (LLMs) to train on or having more computing power. Instead, AI’s value lies in developing your ability to ask a series of strategic questions that begin to shape and craft your hypothesis, which can reveal pathways you hadn’t previously considered.

We see this as an “inquiry gap”—not to be confused with a technology gap—that will require a new approach to questioning and problem-solving. This strategy will ultimately separate companies that are gaining a competitive advantage from those that are merely deploying another tool.

How to Close the AI Inquiry Gap for Better Business Results

If companies want to broaden AI adoption beyond basic editing or generating stylized images, their employees need to learn how to ask better questions or how to reframe their “prompts” to encourage deeper exploration of AI’s capabilities in search and reasoning. Using advanced prompt engineering to close the inquiry gap focuses on crafting language that guides LLMs toward more accurate and relevant answers.

While the willingness to use AI continues to grow, many professionals struggle with effective engagement. Recent studies highlight significant barriers:

53% of domain professionals admit they don’t know how to get the most value from AI technology.

70% of non-users would use generative AI more if they knew more about the technology.

According to McKinsey, organizations remain in the early stages of value capture from generative AI, with “few experiencing meaningful bottom-line impacts.”

Google recently published a comprehensive, 69-page Prompt Engineering Whitepaper detailing the best practices and common challenges users face when crafting prompts. As we shared in our earlier posts, “Fostering a Culture of Adoption with AI” and “What Essentials Should You Include in Your AI Playbook?”, establishing robust AI frameworks is crucial—especially when taking a strategic approach to prompt engineering that drives enterprise-wide innovation and sustainable competitive advantage.

“AI’s value lies in developing your ability to ask a series of strategic questions that begin to shape and craft your hypothesis”

Five Strategic AI Roles that Drive Competitive Advantage

To rapidly close the inquiry gap, individuals should expand their prompting approach beyond basic goals and instructions to incorporate McKinsey’s strategic framework. Their research explores how strategists should change their approach to fully leverage AI benefits, from “enhancing every phase of strategy development” to analyzing markets, competitors and strategic initiatives.

McKinsey’s framework demonstrates how strategists close the inquiry gap by engaging with AI through five distinct roles:

1. Researcher Role in AI Strategy: Asking AI to gather comprehensive data and identify connections across sources that humans might miss, while focusing questions on insights that provide a distinctive competitive advantage.

2. Interpreter Role in AI Strategy: Prompting AI to transform raw data into meaningful patterns and strategic implications, revealing adjacencies, opportunities and trends that align with organizational goals.

3. Thought Partner Role in AI Implementation: Engaging AI in collaborative ideation to challenge assumptions, overcome biases and test strategic thinking against established frameworks in order to identify blind spots.

4. Simulator Role in AI-Driven Decision Making: Directing AI to model multiple scenarios based on market conditions, competitor moves and stakeholder reactions to inform strategic decisions and provide early warnings for course corrections.

5. Communicator Role in AI-Enhanced Strategies: Leveraging AI to adapt strategic narratives for various stakeholders while maintaining consistency, making complex strategies more accessible and actionable across different contexts.

Case Study: Applying Iterative AI Questioning for Website Redesign

To demonstrate this methodology, we’ll walk through how these five roles apply to identifying strategic insights for an industrial equipment company website redesign. Below is our dialogue with Claude 3.7 Sonnet, showcasing iterative questioning in action.

Starting as Researcher

ScheinerInc.: We need to redesign a website for an industrial equipment company. What information should we gather about our client’s audience?

Claude 3.7: For an industrial equipment website redesign, we should start by understanding their audience’s research patterns. Looking at data from industrial equipment buyers, I see they typically spend 70% of their purchase journey researching online before contacting sales. Let’s examine who visits your client’s current site, how they navigate it and what content they engage with most. Do you have Google Analytics or similar data we could analyze?

ScheinerInc.: Yes, our analytics show that most visitors spend time on product specifications and case studies, but that the company has a high bounce rate on their homepage.

Transitioning to Interpreter

Claude 3.7: That pattern suggests that their technical content meets needs, but that their homepage isn’t connecting with visitors’ initial intent. This could indicate a misalignment between their homepage’s messaging and their customers’ primary concerns. Which specific industries do their most valuable customers come from?

ScheinerInc.: Primarily manufacturing, with growing segments in food processing and pharmaceuticals.

Claude 3.7: Interesting. Manufacturing customers typically prioritize reliability and cost efficiency, while pharmaceutical clients focus more on precision and compliance. Your client’s current homepage might be speaking too generally rather than addressing these specific priorities. Let’s go deeper: Do you know which decision-makers within these companies typically visit your client’s site?

ScheinerInc.: Usually engineers and operations managers, sometimes procurement.

Evolving to Thought Partner

Claude 3.7: This gives us an opportunity to rethink your client’s website strategy. Engineers and operations managers have different priorities than procurement teams. Engineers value detailed specifications and performance data, while operations managers focus on reliability, maintenance and downtime prevention. Procurement prioritizes cost justification and comparative analysis.
What if we created personalized entry points on your client’s homepage that direct these different personas to content specifically designed for their concerns? This could significantly reduce the bounce rate. Would that approach align with the company’s sales process?

ScheinerInc.: Yes, but we’d need to understand how these different roles influence each other in the buying process.

Becoming a Simulator

Claude 3.7: Let’s simulate a typical buying journey for your client’s equipment. An engineer identifies a need and begins researching solutions, finding your client’s site. They’re impressed by the technical specifications, but need to justify the investment to operations. The operations manager then visits, looking for reliability data and total cost of ownership information. If convinced, they involve procurement for final pricing negotiations.

If this website redesign creates clear pathways for each role and provides content that helps them build internal consensus, this could shorten the sales cycle by an estimated 15%-20%. Let’s model how different homepage designs might affect this journey. What if we tested three different approaches:

1. Industry-specific entry points
2. Role-specific entry points
3. Problem-solution entry points

Which do you think would resonate best?

ScheinerInc.: Role-specific sounds promising, but we’d like to understand how competitors approach this.

Acting as Communicator

Claude 3.7: Based on competitive analysis, I see three distinct approaches among industrial equipment providers:

1. Category leaders emphasize their innovation and industry expertise, with content organized by solution type
2. Specialist competitors focus on specific applications with in-depth case studies
3. Value-oriented competitors emphasize cost efficiency and ROI calculators

What’s notable is that none effectively segment their content by decision-maker role, despite clear evidence that purchasing involves multiple stakeholders. This represents a differentiation opportunity.

I can help draft messaging that speaks directly to each role’s priorities while maintaining your client’s brand voice. For example, for engineers: “Precision-engineered solutions with industry-leading specifications” versus for operations managers: “Maximize uptime with equipment that delivers 99.8% reliability.”

This approach could position your client’s website as uniquely responsive to how industrial purchases actually happen rather than how they’re traditionally marketed.

Returning to Researcher

ScheinerInc.: Before we commit to that approach, our client would like more specific data on how their target customers actually research industrial equipment.

Claude 3.7: That’s an excellent question to validate our strategy. Looking deeper into B2B industrial equipment research patterns, recent studies show:

1. 65% of industrial buyers report using manufacturer websites to compare technical specifications directly.
2. 82% value vendor websites that make it easy to share information with colleagues involved in the decision.
3. 74% are frustrated by websites that require contacting sales to access detailed information.

What’s particularly relevant is that buying committees have expanded from an average of 5.4 stakeholders in 2018 to 7.3 today. Each brings different priorities to the decision.

The Future of Competitive AI Strategy

The future of AI strategy won’t be defined by who has the most advanced tools; rather, it’ll be defined by who knows how to use them to ask smarter, more strategic questions. Adopting roles, like researcher, interpreter and simulator, isn’t about the process—it’s about unlocking deeper insights and faster decisions.

The real question now isn’t whether you’re using AI, but whether you’re asking it the right questions. Those who master this approach will discover competitive advantages their technology-focused competitors miss entirely.

As always, thank you for reading or listening. Questions? Feel free to email me here.