Leaning into Leadership – Podcast Episode #1

Organisations are rapidly automating tasks and redesigning processes. Many are starting their redesign focused on what the technology can do – rather than what good work should look like.

AI can make work more efficient. But what happens when that redesigned work leaves people less capable, less engaged, and less able to exercise judgment.

The potential workforce impacts are clearly not limited to job losses. They include skills erosion, cognitive dependence, reduced autonomy, fragmented roles, and uncertainty about professional identity. If an organisation goes down that path, have they really lifted performance?

Joining us for this podcast episode are Rory Gregg from SpencerMaurice, and Rachel Linton from Cognize.

In this podcast discussion, they explore how leaders can capture the benefits of AI while protecting capability, wellbeing, judgment, and meaningful work.

You can watch the video on Youtube, or continue reading below.

Rory Gregg:
Rachel, can I start by asking what do we mean when we talk about the human cost of AI-driven work design?

Rachel Linton:
AI-driven work design is when organisations design work based on what the technology can do. They tend to take a very narrow approach to the situation. It often results in workflows being heavily dissected, based on what the technology can do. It often overlooks or ignores the human side of the design process

Rory Gregg:
So putting the technology elements ahead of the people elements of design.

Can you explore that further. What might that look like for a large organisation focused around service delivery, for example?

Rachel Linton:
There can be top-down and bottom-up ways of looking at this. The bottom-up approach gives staff the incentive to start using AI as much as possible. The focus becomes which tasks can be replaced by AI.

A more top-down version might be a structured program, or a redesign project. You redesign a process using a particular tool that uses AI.

In either case, the human impacts of these changes are often not fully considered in the design process.

Considerations such as:

• What are the impacts on workforce skills?
• How do workforce roles change?
• What are the workforce wellbeing impacts?
• Are job demands appropriate?
• Are we expecting unrealistic levels of productivity?

Rory Gregg:
What are some of the risks of taking an AI-driven approach to work design?

Rachel Linton:
There are several key areas of risk that can occur if you do not fully consider the human factors.

• These workforce related risks include:
• cognitive skill decline over time
• increased psychosocial hazards
• disengagement from work
• reduced sense of ownership and connection to their work

Looking at the cognitive impacts first, there is already research showing that people tend to over-rely upon LLMs when it comes to thinking and reasoning tasks. Studies have shown that when given the opportunity to use an LLM to do some research and present some recommendations, people tend to process the information that they find in a more superficial way, compared to if they are finding source material themselves, synthesising it, and then coming up with their own thinking.

People are tending to outsource judgment to LLMs rather than thinking things through for themselves, or using these tools to challenge their own thinking. Over time these patterns of technology use can start to reduce people’s critical thinking skills, their ability to reason and solve problems, and their ability to write effectively.

Rory Gregg:
I imagine it could also have further implications for organisational culture and that notion of humans wanting to connect with other humans, particularly around tasks-focused things.

The breaking up of some of these processes into discrete tasks essentially starts to pull apart some of those elements of connection for people within an organization.

Rachel Linton:
Absolutely. There’s an interesting recent study that actually looked at a firm of attorneys in the US. The effect of introducing AI in that organisation was significant. People started to disconnect from their identity as attorneys. So being an attorney involves quite a holistic way of understanding work, ethics, and who they are in relation to their work.

But as more and more tasks were done in this firm by AI, work carried out by the attorneys really started to fundamentally change. It became prompting, reviewing, and validating outputs. There was less actual reasoning and problem-solving.

This was viewed by many of the workforce as a problematic change.

Rory Gregg:
In your view, when is it okay to incorporate AI into work? Are there examples of where it is quite useful and beneficial?

Rachel Linton:
It can be when it is looked at in a holistic way. That means looking at the whole workflow, and involving people in that process. Really understanding which of the tasks that people do in their jobs actually require them to think for themselves, reason, and use their judgment.

Determining which tasks or parts of their roles they really enjoy, and that energise them, versus the parts that are really draining. There is often a lot of unnecessary administration or processing associated with roles which can be reduced.

Also looking at it from that human lens as well when working out which aspects to automate, or how to use AI in a way that is going to support people’s cognitive capacities, and support their positive experience of work.

Rory Gregg:
If an organisation is redesigning work using an AI-driven approach, what are some of the implications around balanced scorecards, overall organisational performance, performance of individuals?

Rachel Linton:
I think governance is really important. Having the guardrails in place to ensure that organisations are considering the human impacts, and having ways of monitoring those guardrails.

In terms of that people lens, organisations need to be monitoring the cognitive impacts of AI use. Implementing ways of monitoring and managing when it becomes clear that there are workforce skill declines.

Also, monitoring the psychosocial risks of any changes in workloads and work demands. Are people still deriving a sense of meaning from their work? Do they have that engagement with the organisation, and intrinsic motivation?

Measuring and monitoring these different lenses of the people impacts, is important if you need to achieve a sustainable, positive implementation for an AI driven workflow.

Rory Gregg:
So in summary, an AI automation driven approach to work design can potentially have some benefits, if it is focused carefully on automating administrative elements of work that require little judgement or reasoning.

Redesign of work should be done in a way that ensures that we are not hollowing out work to remove purpose, collaboration, and meaning for people.

And I finally, it is about having very clear goals relating to the overall outcomes you want to achieve for the organisation. Goals that encompass both the efficiency and productivity objectives, as well as the workforce culture and wellbeing.

Rachel Linton: Yes – absolutely.