Position Descriptions in the AI Age: Why Most Organisations Are Already Behind

For years, position descriptions were treated as administrative documents.

They outlined:

• responsibilities,

• tasks,

• reporting lines,

• and required experience.

  
  

In many organisations, they changed very little over time because the nature of work itself changed slowly.

That is no longer the case.

As AI becomes embedded into customer operations, contact centres and enterprise workflows, organisations are discovering that many existing position descriptions were designed for work that AI is increasingly capable of performing.

Tasks such as:

• answering standard enquiries,

• retrieving information,

• processing routine requests,

• summarising interactions,

• and guiding basic workflows

are steadily moving toward:

• AI agents,

• chatbots,

• workflow automation,

• and self-service environments.

But while technology is evolving quickly, workforce design often is not.

Many organisations are still using role structures built for high-volume transactional work while simultaneously trying to implement AI-enabled operating models.

That creates a disconnect between:

• how work is now performed,

• and how roles are formally defined.

Research increasingly reinforces the need for organisations to rethink work design as AI adoption grows.

“The use of artificial intelligence in work processes requires the anticipatory change of work roles.”

A. Röltgen, “Pathway to Work with AI: Testing the AI Role Development Method in an Industrial Work Environment”

This is the core issue.

Traditional position descriptions were built around execution. They assumed humans would perform most operational tasks directly.

AI changes the value humans provide.

As routine activity becomes automated, human contribution increasingly shifts toward:

• judgement,

• exception handling,

• empathy,

• policy interpretation,

• risk assessment,

• and oversight.

That is a fundamentally different type of work.

And yet many position descriptions still primarily describe:

• process adherence,

• task completion,

• and transactional throughput.

Very few clearly define:

• when humans should intervene,

• when AI should escalate,

• who validates AI outputs,

• where decision authority sits,

• or how accountability operates in hybrid human + AI workflows.

This becomes a serious operational issue.

Because unclear role design in AI-enabled environments often leads to:

• inconsistent customer outcomes,

• fragmented escalation pathways,

• duplicated effort,

• and confusion around accountability.

In many cases, organisations focus heavily on deploying AI technology while leaving the underlying workforce model largely unchanged.

That approach rarely scales well.

AI-enabled operating models require role clarity with far greater precision than traditional environments ever needed.

This is why position descriptions are becoming strategically important again.

Not simply as HR documents. But as operational design tools.

Modern AI-ready position descriptions increasingly need to define:

• decision boundaries,

• escalation logic,

• AI interaction responsibilities,

• governance expectations,

• and continuous improvement obligations.

Because in AI-enabled operations, humans are no longer primarily managing transactions.

They are increasingly managing judgement.

The organisations adapting fastest to AI are not just deploying new tools.

They are redesigning work itself.

And increasingly, that redesign starts with the position description.

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