By Jim Shimabukuro (assisted by Claude)
Editor
Introduction: After watching the YouTube videos “The WORLD’S LARGEST Abandoned Building – Sears Headquarters” and “ABANDONED IBM Complex Left UNTOUCHED Since 2016,” I was left with the overwhelming sense that large companies such as Amazon will someday, perhaps sooner rather than later, succumb to a similar fate. The following is Claude’s take on this question. -js
The abandoned corporate monuments—the hollow Sears tower, the vacant IBM complex—serve as architectural memorials to a simple truth: no commercial empire is permanent. The question isn’t whether Amazon could fall, but rather what form its disruption might take.
Before exploring Amazon’s potential vulnerabilities, it’s worth understanding why these giants fail. Sears dominated American retail for over a century, yet couldn’t adapt when the fundamental nature of shopping changed. IBM controlled computing’s hardware era but missed the personal computer revolution’s implications. The pattern isn’t merely about technology—it’s about organizational rigidity meeting paradigm shifts. Large companies optimize for their current reality so completely that they become structurally incapable of recognizing when the ground itself is moving.
Artificial intelligence represents the most likely disruptive force, though perhaps not in the way commonly imagined. The threat to Amazon isn’t that AI will make better recommendation engines or more efficient warehouses—Amazon will implement those improvements themselves. Rather, AI threatens to eliminate the very premise upon which Amazon’s empire rests: the need for a centralized marketplace intermediary.
Consider the current Amazon model. The company’s power derives from aggregating sellers, managing logistics, controlling customer relationships, and extracting rent from each transaction. But advanced AI agents could fundamentally restructure this arrangement. Imagine personal AI assistants that autonomously search across all available suppliers, negotiate prices directly, arrange logistics through decentralized networks, and verify product quality through distributed reputation systems. In this scenario, Amazon becomes unnecessary infrastructure—a middleman rendered obsolete by automated disintermediation.
The technology enabling this transformation is emerging now. According to research on AI agents and autonomous systems, we’re seeing rapid development in AI’s ability to handle complex, multi-step tasks that previously required human judgment. When AI can reliably negotiate, verify, and transact on behalf of individuals across fragmented markets, the convenience Amazon provides—having everything in one place—loses its competitive advantage.
The second force working against Amazon’s model is the growing sophistication of decentralized technologies and peer-to-peer networks. Blockchain-based systems, while often overhyped, are maturing in their ability to provide trust and verification without central authorities. Combined with AI, these technologies could enable a new commerce paradigm where buyers and sellers connect directly, with smart contracts handling escrow, AI agents managing logistics coordination, and distributed reputation systems replacing Amazon’s reviews.
This isn’t purely theoretical. We’re witnessing the early formation of these systems in 2025. The rise of AI agents capable of interacting with multiple platforms, the increasing sophistication of decentralized finance protocols, and the growing consumer desire for alternatives to big tech monopolies are all convergent trends. Amazon’s current dominance in e-commerce—while substantial—exists partly because the infrastructure for alternatives hasn’t matured. That’s changing.
Amazon’s vulnerability extends beyond technology. The company faces mounting regulatory pressure across multiple jurisdictions. Antitrust scrutiny has intensified, with regulators questioning whether Amazon’s dual role as marketplace operator and competing seller creates inherent conflicts of interest. European regulators have been particularly aggressive, and American policy is shifting as well.
More subtly, there’s a cultural shift occurring. The initial wonder of next-day delivery and infinite selection is giving way to concerns about Amazon’s market power, treatment of workers, environmental impact, and effect on local communities. This isn’t merely performative criticism—consumer behavior is beginning to reflect these values, particularly among younger demographics who are more willing to sacrifice convenience for ethical considerations.
Ironically, Amazon’s greatest strength—its logistics network—could become its fatal weakness. The company has invested hundreds of billions in warehouses, delivery vehicles, and fulfillment infrastructure optimized for the current model of centralized inventory and last-mile delivery. If AI-enabled peer-to-peer commerce takes hold, this infrastructure becomes a massive liability rather than an asset. Amazon would be locked into maintaining expensive facilities while nimbler competitors operate with minimal physical infrastructure, using AI to coordinate distributed resources.
This pattern has historical precedent. Sears’s vast catalog infrastructure and retail footprint seemed unassailable until they became anchors preventing adaptation. The very scale that protects an incumbent can prevent the radical restructuring needed when paradigms shift.
Are we seeing early signs of these forces? Arguably, yes. The explosion of AI capabilities throughout 2024 and into 2025 has been remarkable. Models can now handle increasingly complex reasoning, multi-step planning, and autonomous operation. Companies are racing to develop AI agents that can perform sophisticated tasks with minimal human oversight. While these are still early days, the trajectory is clear.
Meanwhile, Amazon’s growth is showing signs of maturation. The company’s retail margins remain thin, and its profitability depends heavily on AWS cloud services—a business that faces intensifying competition and could be disrupted by AI-optimized cloud architectures. The easy growth from simply being better than traditional retail is exhausted. Future growth requires defending against AI-native competitors who don’t carry legacy infrastructure costs.
If this scenario unfolds, Amazon’s decline likely won’t be sudden. Sears’s fall took decades. IBM survived by transforming into a services company. Amazon has resources, talent, and time to adapt. But adaptation requires recognizing the threat and being willing to cannibalize current revenue sources—something large organizations historically struggle with.
The disruption might begin in specific product categories where AI-coordinated peer-to-peer exchange works best, then gradually expand. Amazon might maintain dominance in some areas while losing ground in others. The company could remain significant even as its cultural and economic centrality fades, much as IBM still exists but no longer defines computing.
Those abandoned headquarters aren’t simply monuments to failed companies—they’re evidence of capitalism’s creative destruction, the process by which new organizational forms replace old ones when technological and social conditions shift. Amazon’s current dominance is real, but dominance has never been permanent. The combination of AI-enabled disintermediation, decentralized technologies, regulatory pressure, and cultural shifts creates plausible pathways for Amazon’s eclipse.
Whether this happens soon or later depends on how quickly AI capabilities advance, how effectively decentralized alternatives scale, and whether Amazon can transform itself as radically as would be required. History suggests that betting against such transformation is wise. The forces that could topple Amazon are already forming. The question is whether they’ll mature fast enough, and whether Amazon’s advantages can hold against a fundamental restructuring of how commerce operates.
The abandoned buildings weren’t always abandoned. They were once vital centers of American economic life, as unassailable as Amazon seems today. That’s the lesson worth remembering as we watch the present giants. Somewhere, perhaps in a small AI lab or decentralized protocol project, the seeds of Amazon’s eventual replacement may already be growing.
Sources
On AI Agents and Autonomous Systems (2024-2025 developments):
- AI agents moving from theory to infrastructure – The Conversation: “AI agents arrived in 2025 – here’s what happened and the challenges ahead in 2026” (Thomas Şerban von Davier, 29 Dec 2025).
- Multi-agent systems surge – MachineLearningMastery: “7 Agentic AI Trends to Watch in 2026” (reports 1,445% surge in multi-agent system inquiries from Q1 2024 to Q2 2025) (Vinod Chugani, 5 Jan 2026)
- Enterprise adoption projections – IBM: “AI Agents in 2025: Expectations vs. Reality” (99% of enterprise developers exploring AI agents) (Ivan Belcic & Cole Stryker, n.d.)
- Market growth forecasts – AWS Blog: “The rise of autonomous agents” (Gartner predicting 15% of work decisions made autonomously by 2028, market growing to $52.6 billion by 2030) (Sri Elaprolu, 13 June 2025)
On Amazon’s Regulatory Scrutiny:
- FTC antitrust lawsuit – TechPolicy.Press: “FTC v. Amazon.com” (comprehensive timeline of the case filed September 2023, which survived motion to dismiss in October 2024) (14 Nov 2024)
- $2.5 billion settlement – FTC: “FTC Secures Historic $2.5 Billion Settlement Against Amazon” (September 2025 settlement over subscription practices) (25 Sep 2025)
On Amazon’s Financial Performance:
- AWS margins and profitability – Amazon 2024 Annual Report: AWS revenue reached $108 billion in 2024, up 19% YoY
- Operating margins – Futurum Group: “Amazon Delivers Strong Q4 FY 2024” (AWS operating margins at 36.9% in Q4 2024, accounting for 60% of company’s total operating income) (Olivier Blanchard, 10 Feb 2025)
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Educational Technology and Change Journal 
Jim,
I’m old enough to have experienced several of these replacement scenarios. The analysis seems accurate to me. Any company based on physical facilities seems doomed to me, but people can make fortunes from them before they collapse. Google isn’t as easy to destroy.
I built Smart Science Education Inc. to be highly flexible and independent of physical delivery. Curiously, no one has duplicated its highly successful learning model. Georgia Cyber Academy credits the Smart Science® system for achieving the highest average state science score in Georgia history. I took the most difficult path to learning in science education, while everyone else took the easy way. Sadly, we have not built a juggernaut because we lacked the money and expertise to market ourselves successfully. We’re hopefully changing that now.
The future depends on distributing and democratizing businesses. AI will accelerate these trends. The cloud will deliver.
Harry, the steps to placing Smart Science on an AI platform may not be that difficult. You could develop a “localized” LLM that doesn’t bleed out of SS. It would be trained on an LLM that’s based in SS material. All students would have a 24/7 personal guide and tutor to all your SS resources. I’m not sure what the cost for the platform would be, but I’m guessing that the chatbot interface might make a huge difference in appeal. The idea is to pioneer this innovation if no competitor has already done so. -Jim
Harry
Yes indeed you must use AI in your programs
You should be a sembol for AI