Contrastive Theory: AI has been overhyped And incremental at best
A common counterargument is that AI, while impressive, will not fundamentally change how businesses compete. From this perspective, AI is just another productivity tool, similar to spreadsheets, ERP systems, or cloud computing. Useful, yes, but not transformative.
Proponents of this theory argue that competition for most AI advantages will soon disappear. If every company can access similar models, similar agents, and similar tooling, AI becomes table stakes rather than a source of sustainable advantage. Margins normalize, differentiation evaporates, and the primary drivers of success are brand strength, execution quality, and distribution.
He also pointed out that many AI deployments quietly underperform. Models are deceptive, agents require monitoring, and data quality problems erode promised returns. In this structure, AI essentially reduces headcount pressure or accelerates existing processes without changing the underlying business model.
This theory seems attractive because it is serious and historically grounded. Many past technologies promised revolution and instead delivered optimization. The weakness of this argument is not that it is always wrong, but that it assumes that organizations do not change structurally. AI seems to thrive when forced to operate within legacy workflows, incentives, and organizational charts.
Provocative Thoughts on AI in 2026
A more aggressive view: AI will disrupt traditional organizations
A more aggressive and painful position is that AI will not only enhance business. It will expose how much modern corporate structure exists primarily to coordinate human beings rather than to create value.
From this point of view, many intermediate layers of management, coordination roles, and even entire departments are examples of pre-world optimization. AI agents that can plan, execute and monitor tasks can eliminate the need for these layers altogether. What’s left are small, high-leverage teams setting the direction while AI systems handle most of the operational execution.
In this world, companies that cling to traditional, headcount-heavy structures are streamlined by leaner, AI-native firms, with lower operating costs and faster decision loops. Disruption is not only technical but also organizational. The firm itself becomes smaller, flatter and more volatile.
This view implies that the benefit of AI is not really about productivity. It’s about who is willing to eliminate parts of the organization that no longer make sense, even when doing so is culturally and politically painful.
more A look of despair: AI will not make as much difference as claimed
Conversely, the most pessimistic view is that AI will fail to deliver a meaningful competitive advantage for most businesses. According to this argument, AI capabilities will be rapidly commoditized, regulatory deployment will be slow, and risk aversion will have an impact in real-world settings.
Under this scenario, AI becomes something that every firm has but little trusts. Decision making remains human because accountability cannot be automated. Mistakes, concerns about bias, and regulatory scrutiny push AI into advisory roles rather than autonomous ones. Productivity gains exist, but they are modest and unevenly distributed.
In this future, AI doesn’t reshape industries so much as quietly integrate into existing software stacks. The winners are not those with the best AI systems, but those with superior strategy, pricing and customer relations. AI becomes background infrastructure rather than a source of disruption.
The danger of this theory is not that it is implausible. That is, businesses that adopt it too quickly may miss the narrow window where structural change is still possible. If AI does lead to change, late adopters won’t just buy the same tools and catch up.