Contrasting view: Artificial intelligence is overrated And incremental at best
There is a common paradoxical argument that artificial intelligence, while impressive, does not fundamentally change how companies compete. From this perspective, AI is just another productivity tool, similar to spreadsheets, enterprise resource planning (ERP) systems, or cloud computing. Helpful, yes, but not transformative.
Proponents of this view argue that most AI gains will be quickly contested. If every company has access to similar models, similar agents, and similar tools, AI will become table stakes rather than a source of lasting advantage. Margins normalize, differentiation evaporates, and the primary drivers of success remain brand strength, quality execution, and distribution.
They also point out that many AI deployments are underperforming. Models go haywire, agents need supervision, and data quality problems erode promised returns. In this context, AI essentially reduces headcount pressure or speeds up existing processes without changing the underlying business model.
This view seems attractive because it is sobering and has historical foundations. Many previous technologies promised revolution and delivered improvement instead. The weakness of this argument is not that it is always wrong, but that it assumes that organizations remain structurally unchanged. AI seems incremental when forced to work within legacy workflows, incentives, and organizational charts.
Provocative Perspectives on artificial intelligence in 2026
The most aggressive view: AI will hollow out traditional organizations
The more aggressive and uncomfortable position is that AI will not only enhance companies. It will reveal how much of the modern institutional structure exists primarily for human coordination rather than value creation.
From this perspective, many middle layers of management, coordination roles, and even entire departments are optimization products of the pre-AI world. AI agents that can plan, execute, and monitor work eliminate the need for these layers entirely. What remains are small, highly influential teams that set the direction while AI systems handle most of the operational implementation.
In this world, companies that cling to traditional, high-staff structures are systematically being outcompeted by smaller, AI-driven companies, which have radically lower operating costs and faster decision loops. The disruption is not only technological, but also organizational. The company itself becomes smaller, flatter and more volatile.
This view suggests that the advantage of AI is not actually about productivity. Rather, it is about who is willing to dismantle parts of the organization that no longer make sense, even when doing so is culturally and politically painful.
More Pessimistic outlook: Artificial intelligence will not be as important as it claims
In contrast, there is a pessimistic view that AI will fail to provide a meaningful competitive advantage for most companies at all. According to this argument, AI capabilities will rapidly become commoditized, regulation will slow their deployment, and risk aversion will weaken impact in real-world environments.
In this scenario, AI becomes something that all but few companies trust. Decision making remains a human matter because accountability cannot be automated. Mistakes and concerns about bias and regulatory scrutiny are pushing AI into advisory rather than independent roles. Productivity gains are there, but they are marginal and unevenly distributed.
In this future, AI will not so much reshape industries as it will quietly integrate it into existing software stacks. The winners are not those with the best AI systems, but those with superior strategy, pricing power, and customer relationships. AI becomes essential infrastructure rather than a source of disruption.
The danger of this view is not that it is implausible. The problem is that companies that adopt too early may miss the narrow window of opportunity where structural change is still possible. If AI turns out to be transformative, late adopters won’t catch up by simply buying the same tools.
