For years, organisations have pursued productivity as a straightforward goal: complete tasks faster, produce more output and increase efficiency.
AI is delivering on that promise at a pace few expected. Across many organisations, people are discovering they can accomplish far more in a working day than they could just a few years ago.
But what happens next?
Many conversations about AI focus on job displacement, automation and efficiency. Those issues matter, but they risk overlooking a more immediate challenge.
As people become more productive, expectations rise alongside them. What feels exceptional today quickly becomes standard practice.
Step one: Redefine what productivity means
HR leaders have an opportunity to redefine productivity before old performance measures become a barrier to future success.
As technology takes on more routine tasks, the value of human contribution increasingly comes from judgement, prioritisation and decision making.
The employee producing the highest volume of work may not be the employee providing the greatest value.
HR teams can review competency frameworks and ask whether they are measuring the capabilities that will matter most over the next five years.
As AI takes on more routine execution, organisations will need to place greater emphasis on critical thinking, problem solving and the ability to make good decisions in situations where the answer is not obvious.
The ability to use AI effectively will matter, but so will the ability to challenge assumptions, identify risks, understand context and exercise sound judgement.
HR sense check:
Use performance reviews to set and review regular goals and objectives specifically related to judgement and prioritisation.
A practical ‘productivity scorecard’ could measure judgement quality, prioritisation of the most important work, AI stewardship and responsible usage, value created and noise reduction (ie. did they simplify, clarify or reduce unnecessary activity).
Organisations will need to place greater emphasis on critical thinking, problem solving and the ability to make good decisions in situations where the answer is not obvious
Step two: Question where time saved actually goes
HR leaders need to ask: ‘What happens to the time AI gives back?’.
Employees might already be assuming that if they complete their work faster, they will simply be given more work. And many organisations will be tempted to answer yes.
Productivity improvements are an opportunity to gain valuable thinking time.
That time should not automatically be consumed by additional tasks. It can be used to strengthen planning, improve decision making, explore new ideas, develop skills or solve problems that have been pushed aside in the rush to deliver.
Managers need to ask whether additional work genuinely improves outcomes, customer value or decision making. If it does not, AI may simply accelerate activity that was never particularly useful in the first place.
HR sense check:
Don’t assume there is ‘extra work time’. Provide questions to managers to ask themselves:
- Does this extra work contribute to a strategic priority?
- Will it improve quality, customer value or decision making?
- Is this work necessary, or are we just filling capacity?
- Should the time be used for learning, reflection, experimentation or recovery?
The goal is not to keep people continuously busy. It’s to make sure human attention is used where it creates the most value.
Step three: Set clear standards for AI-assisted work
HR leaders and managers will need to become more deliberate about defining quality.
Employees need clear guidance on what good work looks like in an environment where AI is involved in the creation process. Speed should not become a substitute for rigour. The fact that content can be generated quickly does not remove the need for fact-checking, critical review or original thinking.
That means managers may need to become more comfortable rejecting average work, even when it arrives ahead of schedule.
Performance conversations need to focus more on decisions. Managers should spend more time exploring how employees prioritised competing demands, where they applied judgement, what they chose not to focus on and how they used AI to improve the quality of their work.
Understanding how someone approaches decisions often reveals far more about performance than reviewing a list of completed tasks.
This also creates an opportunity for managers to understand how employees are adapting to new ways of working.
Some individuals will embrace AI and use it to strengthen their performance. Others may struggle to adjust, become overwhelmed by the pace of change or rely too heavily on technology without applying sufficient critical thinking.
These challenges are unlikely to be visible through traditional productivity metrics alone.
HR sense check:
Employees and managers need to be able to answer these questions before submitting AI-assisted work:
- What was AI used for?
- Were sources or assumptions checked?
- What human judgement was applied?
- What risks, limitations or uncertainties remain?
- What was improved beyond the AI’s first answer?
Step four: Watch out for burnout concealed by high output
A common assumption is that greater efficiency will automatically reduce pressure.
In reality, many employees are now operating in environments where they are reviewing large volumes of AI-generated information, managing multiple tools and making a constant stream of decisions about what should be accepted, rejected or refined.
Burnout in a high-output environment may not look the same as it did previously.
Employees may continue to meet deadlines and produce large amounts of work while becoming increasingly exhausted beneath the surface. Managers therefore need to pay closer attention.
HR sense check:
In high output environments, people may display a negative and critical attitude towards their work, or they might dread coming into the office.
A drop in energy and interest levels, along with trouble sleeping and frequent absences, could point to burnout. Employees might also complain of physical ailments like headaches or back pain and show irritability toward team members or clients.
Crucially, prolific use of AI may cause individuals to feel their work lacks meaning or importance; they may start to disconnect emotionally from colleagues or feel unrecognised.
HR needs to create a culture of continuous, healthy feedback and ensure managers are adept at coaching conversations with their teams.
HR leaders and managers will need to become more deliberate about defining quality
Step five: Review roles before AI redesigns them for you
Many job roles today become obsolete as responsibilities change with AI. As a result, HR leaders should begin reviewing roles systematically to understand where AI is changing expectations and where human expertise continues to create the greatest value.
Rather than focusing solely on tasks and responsibilities, organisations should examine the purpose behind each role. Some activities may be automated entirely. Others may evolve. HR teams will need to redesign roles around uniquely human strengths rather than simply adding AI to existing job descriptions and hoping for the best.
HR sense check:
One of HR’s most complex problems is keeping up with what people actually do.
Designing job scopes is a time consuming process, which is why most job specs end up looking the same. This is where AI can help.
Here’s a five-part framework:
- Map the current role: What tasks does the person actually do, not just what the job description says?
- Identify AI-compressible tasks: Which activities are now faster, automated or partly delegated to AI?
- Identify human-value tasks: Where does the role still require judgement, context, relationship-building, ethics, creativity or accountability?
- Redesign outcomes: What should the role now be responsible for achieving?
- Update competencies and rewards: What behaviours, standards and decisions should now be measured?
There is no doubt that AI is changing how work gets done. The bigger challenge is deciding how to measure work once higher productivity becomes the norm.
That challenge sits squarely with HR. By rethinking how performance is measured, how potential is developed and where people create the greatest value, they can shift the understanding of productivity.
By the time AI resets the baseline, those decisions will already matter.
If you enjoyed this Five Steps article, why not read another: Five steps: Turn organisational strategy into team-level impact
