Executive summary:

• Most companies overestimate AI's immediate impact while underestimating its 5-10 year potential
• Business model design matters more than the technology itself for long-term success
• The explore-exploit framework helps leaders balance innovation with core business needs
• Building structural advantages and moats requires strategic thinking beyond product features

The AI paradox: Everything and nothing has changed

"Many people are overestimating the impact of AI today, but underestimating the impact of AI in the next 5 to 10 years," explains Alex Osterwalder, renowned business strategist and creator of the Business Model Canvas. This paradox explains why so many AI initiatives fail while simultaneously disrupting entire industries.

The challenge isn't the technology—it's how companies integrate AI into their broader business strategy. Companies focusing solely on implementing AI tools without considering their business model implications are setting themselves up for disappointment.

David Pires, head of growth at Strategyzer, puts it succinctly: "The point is not to say that everything you heard about AI is true. The point is to think about how your business model is going to be negatively impacted by AI, or can be positively impacted if you adapt."

Assessing your business model's AI vulnerability

Not all business models face the same level of AI risk. Some fundamental questions can help you assess your position:

Value delivery assessment:

• Can AI replicate your core value proposition faster or cheaper?
• Are you competing primarily on efficiency or uniqueness?
• How dependent are you on human labour that AI could potentially replace?

Customer relationship evaluation:

• Do you own direct customer relationships or depend on intermediaries?
• How easily could customers switch to AI-powered alternatives?
• Are your customer touchpoints susceptible to automation?

Revenue model resilience:

• Does your pricing depend on time-based billing that AI could compress?
• Are you selling outputs that AI could potentially generate?
• How defendable are your current revenue streams?

The consulting industry provides a stark example. "Consulting companies like McKinsey or Accenture are literally firing people right now and are afraid for their business," Pires observes. These companies built their models on human expertise and time-based billing—both vulnerable to AI efficiency gains.

The explore-exploit framework for AI strategy

One of the biggest mistakes leaders make is treating AI as either a complete game-changer or irrelevant distraction. The reality requires a more nuanced approach through what Osterwalder calls the "explore-exploit" framework.

Exploit (core business focus):Your existing business model likely generates most of your revenue and cash flow. Don't abandon what works, but ask:

• How can AI improve efficiency in your current operations?
• Where can automation reduce costs without compromising quality?
• Which processes would benefit from AI-powered optimization?

Explore (innovation focus):Simultaneously, allocate resources to explore new AI-enabled opportunities:

• What new value propositions could AI make possible?
• How might AI change customer expectations in your industry?
• Where could you build AI-powered competitive advantages?

"I'm not worried about the speed of the cycles, I'm worried about leadership not embracing the explore-exploit framework," Osterwalder emphasizes. "People are falling in love with tech, not value propositions and business models."

Building structural advantages beyond technology

While competitors can copy AI tools, they cannot easily replicate well-designed business models. Sustainable competitive advantage comes from creating what strategists call "structural advantages"—barriers that make your position defensible regardless of technological changes.

Network effects:Design your business model so that each new customer makes your offering more valuable to existing customers. Platform businesses excel at this, but traditional companies can build network effects too.

Data advantages:AI is only as good as the data it trains on. Companies with unique, high-quality datasets maintain significant advantages even as AI tools commoditize.

Customer switching costs:Build business models that become more valuable over time, making it costly for customers to switch. This goes beyond product features to include processes, integrations, and relationships.

Ecosystem integration:Position your company as an integral part of your customers' operations, not just a vendor. The deeper the integration, the harder it becomes to replace.

Accelerating value proposition development with AI

Here's where AI becomes genuinely transformative: it can dramatically accelerate the innovation process itself. "Developing value propositions is literally 10 times, if not much, faster with the support of AI," Osterwalder notes.

Rather than replacing human creativity, AI amplifies it. Teams can:

• Generate multiple value proposition hypotheses rapidly
• Test and refine ideas more quickly
• Iterate through business model variations efficiently
• Analyse customer feedback at scale

"Humans combined with AI are going to beat people without AI, for sure. At the very least, in speed," Osterwalder explains.

System thinking: AI in the context of business models

AI in isolation is "silly and useless," according to Osterwalder. Success requires system thinking that combines technology solutions with value propositions and business models.

This systems approach means:

• Technology serves the business model, not vice versa
• AI implementations align with customer value creation
• Business model changes accompany technology adoption
• Multiple components work together to create competitive advantage

"The business model is the combination of different pieces. From the solution to the value proposition to the business model, it's a combination of a lot of different pieces that create the system that leads to success."

Taking action: Your next steps

Understanding these principles is just the beginning. Here are practical steps to strengthen your business model for the AI era:

Immediate actions (next 30 days):

1. Map your current business model using frameworks like the Business Model Canvas
2. Identify which components are most vulnerable to AI disruption
3. Assess your explore-exploit balance and resource allocation
4. Begin experimenting with AI tools to accelerate your innovation processes

Strategic initiatives (next 90 days):

1. Design alternative business model scenarios incorporating AI
2. Test new value propositions with customer segments
3. Build partnerships or capabilities that create structural advantages
4. Develop metrics to track both efficiency gains and innovation progress

Long-term positioning (6-12 months):

1. Create feedback loops between your explore and exploit activities
2. Build business model components that become stronger with AI adoption
3. Develop unique datasets and capabilities that competitors cannot easily replicate
4. Position your company as an integral part of your customers' AI transformation

The companies that thrive in the AI era won't be those with the flashiest algorithms. They'll be the ones with the strongest, most adaptable business models. As Osterwalder concludes: "Don't compete on tech alone. Compete on business models."

The AI revolution is just beginning, but the fundamental principles of value creation remain constant. By focusing on business model innovation rather than technology alone, you can build competitive advantages that no algorithm can easily replicate.

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Ready to future-proof your business model for the AI era? Book a strategic workshop on AI and business models with our team to assess your current position and design competitive advantages that last.


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