Why the Stock Market suddenly questions Consulting
- Claas
- Feb 12
- 3 min read
When easy explanations start to feel wrong
In the last two weeks many employees and shareholders of technology companies rubbed their eyes in disbelief. Within days, share prices dropped sharply. The explanation came quickly: new developments in generative AI, particularly around Anthropic.
It is a convenient story. Easy to tell, easy to headline. AI replaces knowledge work. Knowledge work is the core business of many technology and consulting firms. Therefore, those firms must be under threat.
At first glance, the logic seems sound. On closer inspection, it starts to fall apart. Because if AI truly increases productivity, reduces cost, and enables new use cases, then the companies best positioned to benefit should be those that have spent years building, selling and implementing technology at scale.
Firms like Accenture or Cognizant. Platform providers such as Salesforce, Microsoft, SAP, or Google. These companies are not watching this development from the outside. They are deeply embedded in it. The market reaction shows how difficult it has become to clearly interpret technological progress.
Progress rarely moves in one direction
Technological progress has never been a pure growth story. It creates new opportunities while quietly devaluing existing ones. Both effects happen at the same time, often in the same moment.
AI intensifies this pattern. It is exceptionally good at tasks that were long considered demanding: analysis, structuring, summarisation, variant generation. Activities that once required experience, time, and often entire teams can now be executed with remarkable efficiency.
This is real progress. But progress has side effects. The more efficiently these activities can be automated, the harder it becomes to justify their former economic value. Not because they are useless, but because they become interchangeable.
Â
When effort stops being a convincing argument
Many business models, far beyond consulting, are implicitly built on effort. On the assumption that complexity takes time and time can be billed. AI challenges this assumption directly.
When analysis takes minutes instead of days, the benchmark shifts. Not every analysis becomes worthless. But its value no longer lies in the act of producing it. It lies in what happens afterwards.
This is where discomfort begins to surface. Many services were accepted for years precisely because their value was difficult to isolate. Because outcomes were indirect and benefits hard to measure. AI reduces that grey zone. And once the grey zone shrinks, justification becomes harder.
Â
The slow erosion of certain kinds of work
What we are witnessing is not sudden displacement. It is a gradual, almost silent commoditisation.
Work that can be clearly described becomes reproducible. Work without clear ownership becomes interchangeable. Work that does not force a decision loses sharpness.
This does not affect isolated tasks. It affects entire bundles of services. Including consulting. Analysis without accountability. Documentation without consequence. Concepts without execution. These elements were under pressure long before AI entered the picture. AI merely accelerates a process that was already underway.
Â
Why the nervousness feels different this time
The current nervousness in the markets is therefore not just hype or overreaction. It is also a signal that underlying value assumptions are shifting. Not everything that worked in the past can simply be extrapolated into the future.
This does not mean that technology companies or consultancies are facing extinction. But it does mean that certain forms of legitimacy are eroding. Effort alone is no longer persuasive. Expertise without responsibility is questioned. Efficiency no longer substitutes for decision-making.
The unease is less about replacement and more about justification.
Â
Where value starts to migrate
As some forms of work become cheaper and faster, value does not disappear.
It moves. It moves toward ownership. Toward responsibility. Toward making choices when the data is incomplete, contradictory, or uncomfortable. Toward prioritisation, trade-offs, and decisions that have consequences beyond a slide deck or a report.
These are not activities that scale easily. They cannot be automated in the same way. And they were never the comfortable part of the job.
Many organisations relied on consulting precisely to create distance from these moments. To analyse without committing. To explore without deciding. To recommend without owning the outcome. That buffer is thinning.
Â