What Remains Human May Not Actually Be Procurement's Decision To Make
The locus of control over Procurement’s relevance is shifting outward
In my last post, I introduced The Human Edge matrix, a framework for classifying procurement work in the AI age - what should be automated, what should be augmented, and what should remain human.
(I also included an interactive tool to apply the framework to your own role to assess how much of it should be done by AI as well as which aspects should remain human.)
The response was encouraging, but one question keeps surfacing in conversations with practitioners and leaders:
“Sure, but will any of this still be human in five years?”
It’s a fair question. And the honest answer is: probably not all of it.
The boundary between human and machine work is not a fixed line; it’s moving - but only in one direction. That doesn’t mean everything eventually will go to the machines. Some work will remain human for a long time, perhaps permanently. The question is: what work is that and who makes that call?
Here’s what I’ve come to believe: it’s not procurement’s decision to make.
In this and next week’s post, I’ll get into why this is as well as how to assess what Procurement work stays human and what goes the way of the machine.
The False Binary
Is there any work that is irreducibly human?
I’ve been thinking about this question a lot lately, as have many others. If you read the popular press, you can’t help but be pulled in two completely different directions.
At one end of the spectrum are the Dismissers, those who believe that AI is overblown and there is, and always will be, plenty of work that is and should remain human.
Some of this is based on beliefs that are grounded in sentimentality and emotion, but many dismissers have valid reasons to feel this way. AI hallucinates, it makes mistakes, it can’t do the simplest things (for humans) like read the room. It also lacks real world context, doesn’t understand people in the full human sense, or make thoughtful trade-offs based on variables not codified in the data.
But it’s also worth remembering that AI is still in its infancy, so we should expect the technology to continue to improve. It has already improved considerably in the last few years, and as this improvement continues, we should expect its capabilities viz-a-viz work traditionally done by humans to expand. So it’s entirely plausible that what is human today may not remain human in future.
That’s not to say all of it will go the way of the machine.
At the other end of the spectrum we have the Utopians, the believers who argue that AGI will be upon us soon enough, and that we will have amongst us a superintelligence that will be able to do everything a human can do and more. There will be little or nothing that won’t be done by machines, allowing us all more time to do all we ever aspired to do.
I get where they’re coming from as well - capability gains are arriving faster than ever, the machines are becoming multi-modal and agentic, and there are a ton of incentives, suggesting that human-like general intelligence may not be far off.
But today’s systems still confuse fluent performance with genuine understanding, and I believe that we don’t even know what we don’t know in terms of our brain’s architectures. As such, I personally don’t believe AGI is realistic or achievable, at least not in its full utopian form, any time soon.
What AI Can Fake…And What It Can’t
That said, there is some research that suggests AI has qualities that border on the “human” - and even improve on them in some ways.
For example, there is some evidence that AI can model ‘empathy’, though not without caveats. Specifically, research over the last couple of years finds that:
AI is clearly getting good at empathy-shaped language - that is, for many text-based tasks, LLMs can produce responses that people rate as highly supportive, compassionate, and emotionally intelligent, even outperforming humans in benchmarked test.
But this is mostly evidence of simulation, not sentience - they show patterns of empathy (cognitive empathy and emotionally appropriate language), with no evidence of real empathy (concern, emotion, consciousness, etc.)
In addition, human authenticity still matters - even where AI responses are rated as excellent, people value empathy more when they believe it comes from a human.
Labeling effects matter a lot - there is a ‘human-label’ premium; AI could outperform in building closeness when labeled as human but explicit AI-labeling reduced closeness.
(For the specific sources, look here, here, here, here, here, here, here and here.)
It’s Not About Procurement…
We can draw some interesting insights from this research.
Broadly speaking, people accept AI for analysis and understanding, but resist it for emotional sharing and genuine care. As good as AI might be, the value of human involvement in certain work is not about capability but about perceived legitimacy and trust (that is, perceived intention, shared vulnerability, and the belief that another mind is genuinely with you).
In other words, what people value isn’t capability but perceived human investment, which means that what stays human is going to be determined by what stakeholders value, not by what machines can or can’t do.
This leads to an uncomfortable conclusion for procurement professionals: the question of what stays human isn’t entirely for Procurement to answer. It belongs to the people it serves and the markets it manages; their willingness to trust, to accept, to engage, is what draws the line between human and machine work. Which means if we want to understand what remains human, we need to stop looking inward and start looking outward.
…It’s About The Stakeholders
Of course, there are multiple stakeholders, including the CFO, the board, regulators, internal customers, and suppliers. While the CFO and the board shape what Procurement is measured on, theones that shape how the work gets done are the two constituencies “external to the function”:
The “Internal Customer” (Who Procurement Serves):
What do the internal customers that procurement serves (the business units, support functions such as marketing or HR or legal etc.) think about the work that procurement does?
What are the things that they absolutely want a human to do?
In which situations do they absolutely want a human to interact with?
What will they NOT trust from a machine output?
What do stakeholders actually pay for (in attention, trust, political capital) when they engage procurement?
The “Supply Market” (Who Procurement Manages):
Given that Procurement represents the organization to and manages suppliers (and supply markets at large), how do they perceive the work that the function does?
In which instances do they require a human presence for reasons that go beyond capability?
Outcomes, Not Tasks
So what kind of Procurement work do these stakeholders value?
There are two ways to look at this - at the role/task/subtask level (the actual work Procurement does) or at the outcome level (the key outcomes expected by each stakeholder group)
The task/subtask levels is where most practitioners normally look to answer the question of what remains human. But there’s a problem with this approach.
Procurement’s stakeholders don’t care about the practitioner’s task list. A marketing director who needs a creative agency contracted doesn’t think about whether the procurement person ran a three-bid process or used an AI-assisted evaluation tool. They care only about whether they got a capable agency, on reasonable terms, without it taking months to complete. Therefore, the practitioner’s role/tasks is too insular a view to take. It doesn’t take into account the perspectives of those the function serves.
These outcomes, on the other hand, represent what Procurement’s prime stakeholders - those it serves and those it manages - actually care about. Not policies, not processes, not tools, but outcomes.
As such, outcomes are, then, the most appropriate basis upon which to conduct this analysis.
Seven Outcomes That Define Procurement’s Value
So, what are those outcomes?
Broadly speaking, there are seven broad outcomes worth considering:
Speed and Responsiveness of the Procurement Process
When a business unit needs something purchased, how quickly and painlessly can they get it? The point here isn’t just speed but overall efficiency and effectiveness i.e. is the function seen to be an enabler or a bottleneck? Think elapsed time from request to delivery, in how many times they had to chase someone, and whether the process felt proportionate to what they were buying.
A three-week sourcing exercise for a $5,000 software license is a failure of responsiveness regardless of how well the process was executed.
Achieving Optimal Total Cost of Ownership
This goes beyond the purchase price to encompass the full economic cost of a buying decision, including implementation, maintenance, switching costs, quality failures, etc. From a stakeholder standpoint, this manifests itself when the cheapest option ends up costing more in rework, downtime, or internal frustration.
The valued outcome here is not a 12% reduction of the unit price, but that the money spent yielded the highest utilization and produced the best possible return over the life of the relationship.
Maintaining Supply Resilience and Mitigating Risk
This is a ‘sleeper’ outcome i.e. you only notice it when there is a disruption. Can the business count on having what it needs, when it needs it, without disruption?
Is the category’s distinct risk profile (supplier dependence, geopolitical exposure, commodity volatility, technology obsolescence, regulatory change, cyber threats, etc.) understood and being well managed on their behalf?
The valued outcome here is supply continuity that encompasses not just reliable delivery but supply base resilience itself. The goal is also not to eliminate risk but to ensure risks are identified, quantified if possible, and either mitigated or consciously accepted with the right people informed.
Ensuring Compliance and Ethical Assurance
Stakeholders need to know that what they’re buying, and who they’re buying it from, won’t expose the organization to legal, regulatory, or reputational harm. This covers a host of factors, including sanctions screening, labor and environmental standards, anti-bribery obligations, data privacy requirements, and industry-specific regulations.
The outcome isn’t just that the organization passed an audit, but that the business can operate confidently knowing procurement has built guardrails that protect them from risks they may not even be aware of.
Ensuring Optimal Supplier Relationships
Suppliers are not interchangeable inputs; they each have their own capabilities, knowledge bases and priorities, and the quality of the relationship directly affects what the business gets from them.
This outcome is about not just performance to agreed standards and remediating problems when they arise, but also whether the relationship is managed in a way that earns the organization preferential treatment (better allocation, priority access to new tech, faster response times, access to senior attention, etc.).
Driving Supplier-Enabled Innovation
Some of the organization’s most valuable innovation doesn’t come from internal R&D but from suppliers who bring new materials, processes, technologies, or ideas that accelerate product development and time to market, improve quality, or open new market possibilities.
This outcome is about whether procurement is positioned to unlock that value: identifying innovation opportunities, creating the commercial structures that incentivize suppliers to share their best thinking, connecting the right suppliers with the right internal teams, and ensuring the organization is seen by the supply market as a customer worth innovating for.
Crisis Management
When something breaks e.g. a key supplier goes bankrupt, a pandemic disrupts global logistics, a geopolitical event closes a trade corridor, a quality failure triggers a recall, the organization needs procurement to respond with speed, judgment, and authority. This is episodic work that demands real-time decision-making in challenging circumstances.
The outcome is that the organization survives the crisis with its financials, operations, relationships, and reputation as intact as possible - which calls for coordination across functions, direct engagement with suppliers and stakeholders, and the willingness to make consequential calls without the luxury of full analysis.
The Harder Question
The question that follows, then, is the harder one: for each of these outcomes, what must remain human, what can be augmented, and what should be fully automated?
That’s not a question you can answer in the abstract. It depends on who’s asking, what they’re willing to trust, and whether Procurement’s involvement makes the outcome measurably better.
In Part 2, I’ll introduce a framework for making that determination - one that’s grounded not in what AI can or can’t do today, but in what Procurement’s stakeholders will and won’t accept, and why that distinction matters more than capability ever will.