When Skill Stops Feeling Special. What AI Really Commoditises in B2B Sales
Once the emotion around AI settles, a straightforward question appears.
What exactly is being threatened?
Sales professionals are not wrong to feel uneasy. But the source of that unease is
often misunderstood. The issue is not that skills are disappearing. It is that some
skills are losing the status they once held, because buyers and teams can now
access the outputs of those skills far more easily.
That is the real shift.
The difference between skill and value
In B2B sales, particularly in technical markets, skill and value have often been
treated as the same thing.
Knowing the product range.
Remembering the specifications.
Being able to recommend quickly.
Answering questions with confidence.
Those abilities mattered partly because access to information was uneven.
Salespeople were often the bridge between complexity and clarity. The person who
knew more carried a certain advantage.
AI changes that balance.
Information becomes abundant.
Comparisons become instant.
First-pass recommendations become cheap.
That does not remove skill. But it does change which skills actually create differentiation.
Research from McKinsey suggests generative AI is already reshaping how B2B sales teams work, automating parts of research, proposal writing and product comparison while increasing the importance of contextual judgement and decision support.
What AI really commoditises
AI does not commoditise salespeople. It commoditises repeatable thinking.
That includes things like:
• retrieving known information
• comparing standard options
• summarising existing knowledge
• producing first-draft recommendations
• responding quickly to predictable questions
In lubricants this might mean pulling product data sheets, comparing viscosity grades, listing OEM approvals, or suggesting technically compatible equivalents.
In filtration and engineering supply it may involve matching part numbers, comparing
product ranges, or producing standard proposal text.
All of that still matters. It just no longer differentiates in the same way.
Why this can feel like devaluation
For experienced sales professionals, those were not “basic” skills.
They were earned. They required time, exposure and responsibility. They were built through site visits, failures, customer escalations and small wins that only come with repetition.
So when a machine produces something similar in seconds, it can feel like that effort is being dismissed. That reaction is understandable. But effort was never really the value. Outcome was. AI simply makes that separation clearer.
The skill that was never as valuable as it felt
This can be uncomfortable to say, but it is worth acknowledging.
Being the fastest with answers was never the highest-value contribution in technical
B2B sales. It was rewarded in a world where answers were scarce, and where speed
could sometimes be mistaken for competence.
Buyers did not ultimately trust salespeople because they were quick. They trusted them because their answers held up over time. AI exposes that difference. When everyone can generate an answer instantly, the real question becomes:
Which answers survive contact with reality? That is not a product knowledge question.
It is a judgement question.
Judgement is not commoditised
Judgement tends to live in places AI does not occupy very well.
• knowing when a recommendation is technically right but operationally fragile
• understanding consequences beyond the data
• reading organisational politics and risk tolerance
• sensing when a buyer is confident versus cornered
• pushing back when the “optimised” option creates long-term exposure
In industrial environments, the best salespeople rarely win by being clever. They win by being steady, practical and useful in the real world.
AI can surface possibilities. It cannot own outcomes.
Responsibility is where meaning concentrates
AI introduces a quiet separation between recommendation and responsibility.
Sales professionals who found meaning in being the person with the answers can
feel threatened. Those who found meaning in being the person who stands behind
the outcome tend to adapt faster.
Responsibility becomes visible when things go wrong.
A decision backfires.
A plant goes down.
A cost saving introduces hidden risk.
A substitution meets specification but fails under operating conditions.
AI does not stand in front of the customer when something fails. People do. That is why this work remains deeply human.
The industrial context makes this sharper
In sectors like lubricants, filtration and engineering supply, experience often remains
invisible until something goes wrong.
People remember the failures.
The misapplied lubricant.
The contamination issue.
The wrong filter.
The delayed delivery that shut a line down.
That kind of institutional memory rarely sits neatly in data. It lives in people.
Industry research continues to show that while digital tools are becoming central to commercial work, organisations that combine technology with experienced sales talent perform better than those relying on automation alone.
https://www.mckinsey.com/capabilities/quantumblack/ourinsights/the-state-of-ai
AI is changing how work is done. It is not removing the need for judgement.
The skill stack is being rearranged
What changes is not whether sales professionals are skilled. It is which skills actually create advantage.
Skills that weaken as differentiators:
• memorisation
• speed alone
• product recall
• repeating known frameworks
Skills that strengthen:
• sense-making
• prioritisation under constraint
• ethical judgement
• contextual awareness
• emotional regulation under pressure
• the ability to say, “This might be technically right, but it could be risky for your
operation.”
This is not a downgrade. It is simply a reweighting.
Why average practice feels exposed
AI has a levelling effect. It raises the floor rather than the ceiling.
Sales professionals who relied on being slightly better informed may feel exposed.
Those who already operated at a higher level of judgement, preparation and buyer understanding often find these tools helpful.
That is why reactions tend to polarise. Some people see opportunity. Others feel threatened. The difference is rarely age or seniority. It is how value was previously created.
Looking ahead
Part 1 explored why this moment feels personal.
Part 2 clarifies what is actually changing and why it can feel like devaluation even when it is really a reshaping of value.
Which leads to the next question.
Where does meaning sit now?
Part 3 explores how the human role in sales begins to shift when information becomes abundant and recommendations become easy to generate.
