Kodak, Blockbuster, and Your SEO Strategy
Technology adoption failure is what happens when a company sees a disruptive shift, decides to wait for it to mature, and discovers the window closed while they were planning. Kodak, Blockbuster, and Nokia are the most studied examples. The same pattern is playing out right now in search marketing, where AI platforms are replacing the Google clicks that businesses built their revenue on.
#What did Kodak, Blockbuster, and Nokia have in common?
All three dominated their markets. All three saw the new technology coming. All three chose to wait.
Kodak's engineer Steven Sasson built the first digital camera in 1975. When he showed it to executives, they called it "a cute toy" and told him not to talk about it. Film was too profitable to risk. At its peak in 1997, Kodak's market cap hit $31 billion. They employed over 140,000 people. By January 2012, they filed for bankruptcy with $6.8 billion in debt. The technology they invented destroyed them because they refused to bet on it.
Netflix offered to sell Blockbuster their company for $50 million in September 2000. Blockbuster's CEO laughed them out of the room. At the time, Blockbuster had 9,000 stores, 84,000 employees, and 65 million registered customers. By 2010, Blockbuster was bankrupt. Netflix is worth over $200 billion.
Nokia held 51% of the global mobile phone market in 2007. When Apple launched the iPhone, Nokia executives dismissed it. By 2013, Nokia's smartphone share had dropped to 3%. They sold the phone division to Microsoft for $7.2 billion, a fraction of its former value. Microsoft wrote off the acquisition as a failure within two years.
The pattern: the incumbent sees the threat, believes their current position protects them, waits for the new technology to prove itself, and loses.
#Is the same pattern happening with AI search right now?
Yes. And the data is further along than most business owners realize.
Gartner predicted in February 2024 that traditional search engine volume would drop 25% by 2026. Pew Research Center tracked 900 U.S. adults and found that when Google shows an AI summary, users click a traditional result only 8% of the time, down from 15% without it. Ahrefs studied 300,000 keywords and found the #1 Google position loses 58% of its clicks when an AI Overviewan AI-generated summary Google places at the top of search results, answering the query before users see any links appears.
The business that ranks first on Google for their most important keyword is losing more than half its traffic to a feature Google itself built. That's not a dip. That's a structural change in how buyers find providers.
And it's accelerating. 31% of Americans now interact with AI multiple times per day, up from 22% a year earlier. The shift from Google to AI isn't coming. It happened.
#What happens to businesses that wait?
Harvard Business Review published an article in December 2018 titled "Why Companies That Wait to Adopt AI May Never Catch Up." The core argument: AI advantages compound. By the time a late adopter finishes preparing, early adopters will have taken market share, lowered costs, and built feedback loops that are hard to replicate.
A Verizon-sponsored Harvard Business Review survey of 672 business and technology leaders found that technology "Pioneers" experienced more than 2x the revenue growth of Followers and 3x the growth of cautious adopters. 20% of Pioneer companies saw revenue growth above 30%.
McKinsey's 2025 State of AI report found that 88% of organizations use AI somewhere, but only 6% see significant EBIT impact. Those 6% are compounding their advantage quarter over quarter. The gap between leaders and the rest is widening, not narrowing.
Applied to search: the businesses that optimize for AI citations now build authority with AI platforms. AI learns to trust them. AI recommends them. Each citation reinforces the next. A competitor that starts in 12 months faces an incumbent that AI already trusts and recommends. Displacing an established AI citation takes the same kind of sustained effort it takes to outrank a domain that's held position #1 on Google for years.
#How long does the first-mover window last?
Research published in Small Business Economics (Springer) on AI adoption in micro-businesses found that first movers gain measurable advantages, but the window isn't permanent. In technology markets, first-mover advantage typically holds for 3-7 years before the field levels.
We're in year one of the AI search shift. Most businesses haven't started. McKinsey found only 1% of executives describe their AI strategies as mature. eMarketer's survey of 400 B2B tech CMOs found that while 42% say traditional search is failing them, 94% plan to increase GEOGenerative Engine Optimization, the practice of making content visible in AI-generated search answers spending in 2026. The budget is moving. The question is whether you move with it or after your competitors do.
I've launched 8+ products over 20 years and watched three major platform shifts play out: the move from desktop to mobile, the rise of social media as a distribution channel, and the shift from organic to paid search dominance. Each one followed the same arc. Early movers looked foolish for about six months. Then the data proved them right. By the time the majority moved, the best positions were taken.
#What does the "too late" scenario look like?
Imagine your competitor starts optimizing for AI search today. In three months, their practice area pages start getting cited in ChatGPT responses. In six months, they've built entity authority across directories, reviews, and third-party mentions. AI recommends them by name when a prospect asks for help in your market.
You start 12 months from now. You restructure your content, implement schema, build your directory presence. But AI already has a default recommendation for your city and your service. Your competitor has six months of citation history, review momentum, and content that AI has learned to trust.
You're not starting from zero. You're starting from behind. The effort to displace an established AI citation is the same as the effort to outrank a competitor who's held position #1 on Google for years. It takes sustained investment, months of work, and results that come slowly because you're swimming upstream against an algorithm that already picked a winner.
That's what "too late" looks like. Not impossible. Just expensive and slow.
#What does "early enough" look like?
The opposite scenario. You start now, while most competitors are still debating whether AI search matters.
You restructure your top pages for AI extraction. Question-based headings, direct answers in the first two sentences, FAQ schemacode that marks up your questions and answers so AI can read and extract them directly. You clean up directory listings so AI can verify your entity across sources. You publish content that answers the specific questions your prospects ask AI.
In three months, AI starts citing you. In six months, you're the default recommendation in your market for your service. Your competitor starts 12 months from now and faces the upstream battle described above.
The cost: $2,000-$5,000 per month for AEO work. The return: a position in AI answers that compounds over time, sends traffic that converts at 4.4x the rate of organic search, and doesn't stop the moment you stop paying.
Kodak had 37 years between inventing the digital camera and filing for bankruptcy. Blockbuster had 10 years between the Netflix offer and going under. Nokia had 6 years between the iPhone launch and selling its phone division.
The AI search shift is moving faster than any of those. The data is already published by Gartner, Pew Research, Ahrefs, and McKinsey. The question isn't whether this is real. The question is whether you act while the window is open or explain to yourself why you waited.
If you're reading this and haven't run the ChatGPT test for your business yet, today is a good day to start.
#Frequently asked questions about technology adoption and AI search
Is AI search mature enough to invest in right now? The data says yes. Pew Research reports 31% of Americans use AI multiple times daily. Ahrefs measured a 58% CTR drop for Google's #1 position when AI Overviews appear. The shift is past the "experimental" phase. Waiting for more data means waiting while competitors build positions you'll have to displace later.
How much does it cost to be "early" in AI search? AEO engagements run $2,000-$5,000 per month. Compare that to what you're already spending on Google Ads or SEO. If AI search produces even one additional client per quarter at a high-ticket deal size, the return exceeds the annual cost.
What if I invest in AEO and AI search doesn't grow as predicted? AEO work improves traditional SEO performance too. Structured content, schema markupcode that tells search engines and AI what your page content means, entity authorityhow well AI recognizes your business as a verified, trustworthy provider, and answer-first formatting all help Google rankings. You're not betting on one channel. You're building for both.
Can my current SEO agency handle AEO? Some can, most haven't started. eMarketer's research found that fewer than 10% of sources cited by AI platforms rank in Google's top 10 for the same queries. SEO and AEO are related but different disciplines. Ask your agency what they've done specifically for AI visibility. If the answer is vague, that tells you something.