Artificial intelligence Part 2: impact on the structure of employment and reduction of entry level roles

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As artificial intelligence (AI) continues to be developed and implemented in various forms across workplaces, the exact impact for employment is becoming apparent even in this early stage of adoption. When discussing AI, it's important and extremely relevant to define the capabilities of AI.

AI carries out three activities across all industries -

1. automates the repetitive layer
2. compresses the workforce pyramid
3. raises the value of senior decision-makers (to an extent)

An example only to demonstrate this impact is the organisational structure in industry. 

An industry that once had this structure -

• 1 Director
• 3 Senior professionals
• 15 junior staff

Under AI capability becomes a structure with -

• 1 Director
• 3 Senior professionals
• 3-5 AI-assisted operators

AI across many white collar industries removes what is called the "first draft economy''. Many jobs existed primarily to produce first drafts of various outputs such as reports, media releases, policy notes, research documents, scripts, designs, code for information technology. AI can now produce much of this instantaneously.

AI is starting to hollow-out the traditional 'career ladder'. The junior roles that people once used to enter professions are disappearing first. This situation does have long term consequences for how expertise and experience is developed in society. This creates a "pipeline problem" and is becoming one of the largest and dominant structural challenges of implementing AI.

AI does compress some organisational hierarchies and enables an increase in the number of people or functions that a single leader can manage. This is known as the 'span of control' which AI increases while reducing certain managemernt layers in organisations. Hierarchical compression is only one aspect of the AI's impact but equally the very shape of organisations also changes with -

• fewer administrative workers
• fewer reporting layers
• smaller teams with higher productivity
• leaders responsible for larger spans of activity

Roles that involve accountability, legal responsibility or political authority will remain human dominated. AI does reduce the documentation workforce that produces reports, compiles data, drafts documents and summarises information. It does not replace roles that have decision authority, physical presence, strategic judgement and/or legal accountability. 

As another example of structural change, before AI implementation, a very large organisation often had this structure -

• Executive leadership
• Senior managers
• Middle managers
• Supervisors/team leaders
• Large operational workforce

After AI implementation, the organisation could be structured as -

• Executive leadership
• Senior specialists
• Fewer managers
• AI-enabled reduced operational staff

Effectively the middle and bottom tiers shrink.

The multi-part series covering AI, published in this blog, has been researched and compiled using Claude ai (Anthropic), ChatGPT (OpenAI), and Grok (Xai). Later posts on this topic will list specific industries where change is already happening.