Adopt the Technology Wave
Adapt the business model before a technology wave displaces it
- Difficulty
- Advanced
- Time to result
- ~ongoing to results
- Steps
- 5
- Confidence
- 96%
Start by examining adoption and behavioral change independently from market valuations or promotional hype. Determine whether the technology is changing how customers buy, communicate, work, or evaluate products. Next, identify which parts of the existing business model could be displaced and begin adopting the new capability through funded experiments. Leaders must be willing to alter products, workflows, margins, and organizational assumptions rather than waiting for the threat to disappear. Because hype generally moves faster than implementation, adoption should be persistent rather than panicked: invest early, learn continuously, and expand practical applications as the technology matures. The output is a business that participates in the new wave instead of becoming one of its casualties.
Origin
Calcano derived the model from watching successive waves—client-server computing, the Internet, and AI—replace previously dominant technology companies. Extracted from Masters in Business.
Core principles
- 01Technological displacement is continuous
- 02Hope cannot protect an obsolete business model
- 03Adoption may require accepting lower margins
- 04Hype often precedes practical impact
- 05Early experimentation builds readiness
How to run it
- 1
Identify the wave
Determine which emerging technology could materially change customer behavior, industry economics, or how work gets done.
Pro tip Study adoption patterns separately from company valuations.
Watch out Do not dismiss a technology merely because current valuations appear excessive.
- 2
Map displacement risk
List the products, margins, workflows, and customer relationships that the technology could weaken or replace.
Pro tip Study how earlier leaders in analogous markets lost their positions.
Watch out Assuming an established market position is safe creates strategic blindness.
- 3
Test practical applications
Fund pilots across customer-facing products and internal operations to discover where the technology produces real value.
Pro tip Use multiple bounded pilots rather than betting everything on one speculative application.
Watch out Avoid confusing experimentation with full deployment.
- 4
Adapt the model
Change the business model, operating process, or economics where adoption evidence warrants it, even if the transition reduces legacy margins.
Pro tip Prioritize long-term relevance over protecting every existing revenue stream.
Watch out Waiting for perfect certainty can leave too little time to respond.
- 5
Scale with patience
Expand successful applications while recognizing that implementation usually takes longer than the hype cycle suggests.
Pro tip Track customer adoption and operating outcomes rather than headlines alone.
Watch out Neither complacency nor indiscriminate urgency is a strategy.
In the wild
A financial platform sees AI changing document processing and product discovery. Instead of waiting for a complete industry transformation, it pilots AI for subscription-document creation, client preference capture, and data extraction. Successful pilots are integrated into normal workflows while weaker ideas are retired.
→ The company gains practical AI capabilities without making its strategy dependent on hype.
A store chain detects customers moving product research and purchasing online. It maps the threat to physical-store economics, launches an integrated digital channel, and accepts temporary margin pressure while rebuilding fulfillment and customer service around online demand.
→ The retailer participates in the new channel instead of relying on customers to return to old behavior.
Common mistakes
Treating hope as a plan
Leaders assume the technology will disappear and protect the legacy model rather than developing a credible response.
Following valuation hype
Teams mistake speculative market prices for evidence about the speed or direction of real-world adoption.
Protecting every legacy margin
A company refuses necessary adaptation because the new model initially offers less attractive economics.
Is it for you?
Best for
It is best for leaders navigating AI, platform shifts, automation, or another structural technology transition.
Not ideal for
It is not ideal for reacting impulsively to technologies that lack credible adoption evidence or strategic relevance.
From the transcript
“hope is not a strategy, right.”
“You've got to adopt it, even if it means you've got to change your business, even if it means your business model has got to…”
“The one thing I would say is this always takes a little longer than people think.”
From the episode
Building 'The World's Alternative Investment Marketplace' with Lawrence Calcano
Lawrence Calcano