AI is changing how procurement and supply chain consultants work: what they can analyze, how deeply they can go and where their time is best spent. It is also making human expertise more important, particularly when it comes to context, judgment and turning outputs into recommendations clients can act on.
Through the perspective of Christoph Schenter, Principal in Digital & AI at Inverto, this article looks at what has actually changed in the work, which capabilities are becoming more important, and why this could be one of the most exciting times to build a consulting career.
This article discusses:
- How AI is transforming procurement and supply chain analysis
- Why human judgment and domain expertise matter more than ever
- Which capabilities are becoming more important for consultants
- How AI is enabling consultants to go further in the impact they deliver for
Christoph Schenter
Principal Digital & AI
Christoph Schenter is a Principal in Digital & AI at Inverto, where he leads the Digital & AI expert team and is closely involved in Inverto’s own AI transformation. He has spent more than five years at Inverto and has seen first-hand how AI is changing procurement consulting. Raising what clients expect, and making human expertise more important.
AI is changing how consultants work. Not by replacing the thinking, but by changing what they can analyze, how deeply they can go and where their judgement is needed most.
Many people assume that AI is the Swiss Army knife of procurement, or of consulting in general, but a sophisticated AI output requires more than typing a prompt into a chat.
Producing a reliable output still takes significant human knowledge. Consultants need to understand how to frame the question, provide the right context, interpret the result and recognize when the technology has got it wrong.
According to Christoph, AI is not removing the need for expertise. It is exposing where that expertise really sits.
What Has Actually Changed in the Work
Five years ago, the analytical work in Christoph’s Digital & AI team was relatively linear. Data came in from the client, the team ran a standard set of analyses, completed the data transformation and enrichment, then handed the results back.
That has changed on several fronts. Analyses now draw on far more data points, including a comparable volume of external data alongside the client’s own. Where a price variance or time development analysis was once enough, scenario analysis and index development analysis have become the norm. In one case, around half of a client’s products were linked to indices, so the team mapped the spend against them and built out a far more detailed picture from there.
AI has also made textual information usable at scale. Terms and conditions sitting in thousands of supplier frame contracts can now be pulled into the analysis rather than left to one side.
Our analyses are becoming much more sophisticated in terms of the data points we can consider.
The time saved does not simply disappear from the project. Consultants spend less of it on repetitive data preparation and more of it on deeper analysis, scenario work and testing what the information actually means in the client’s specific context.
At the same time, the standard expected from consultants is rising.
Clients also have access to AI. We need to deliver more in terms of analytical depth and data processing.
The value of a consultant can no longer come from producing an answer a client could generate themselves. It comes from deep expertise, and the ability to connect different data points, scenarios and commercial realities into guidance a client can confidently act on.
Where the Human Stays in the Loop
Christoph’s team spends around 80 percent of its time in the opportunity analysis phase. One of the first tasks there is categorizing spend. The team may receive millions of rows of invoice and purchase order data that need mapping against a defined category tree, so that a line reading “Microsoft O365” lands correctly in IT software licensing. AI makes that possible at a scale that would otherwise be extremely time consuming.
It also gets things wrong. At that volume, the model can latch onto the wrong element of an invoice description and return a classification that looks entirely plausible, yet incorrect.
AI certainly helped to categorize all that information. However, you really need a human in the loop to check the output, because you never fully know which information the model has taken from the context.
Contracts show the same pattern. AI is effective at extracting clear framework data points such as contract dates, durations and payment terms. It is far less reliable when the question is qualitative: what a volume clause means for a supplier relationship, or the contractual implications of splitting volumes differently. On a project screening a large volume of statements of work, AI handled the framework data points while the team built a human-in-the-loop review to evaluate everything that mattered commercially.
AI is good at understanding the framework data points. But when it comes to the key qualitative information, we still need the human in the loop to evaluate the output.
AI has changed how projects start, too. At the beginning of a new engagement, or when moving into an unfamiliar procurement category, it can enrich the brainstorming process and surface relevant insights that would previously have taken far longer to access, so teams can build stronger proposals faster.
The Capabilities That Are Becoming More Important
The skills Inverto has always looked for still apply. Christoph sees four areas that will increase in importance.
The first is human-AI orchestration. The structure and organization needed to run several workstreams at once. Rather than moving through an analysis step by step, a consultant may be driving multiple tasks forward while AI works on others in parallel.
They can have multiple topics on their table at one point because AI is working on several different things. They have to be very structured and well organized to keep all the balls in the air and drive progress across multiple topics.
The second is AI fluency. Knowing how to frame a question, provide the right context and guide the technology towards an accurate output. A weak prompt, or missing context, can still produce a convincing answer. Convincing does not necessarily mean correct.
The third is judgement and quality control.
AI still hallucinates. It can tell you that something is completely correct when it isn’t.
Consultants need to be able to validate whether an output is plausible, identify where information is incomplete or incorrect and decide what needs testing further.
Underpinning all three is deep domain expertise.
You cannot evaluate the AI output if you do not have the actual expertise.
The more confidently the technology produces information, the more it matters that the people reviewing it can identify when that information should not be trusted.
Where AI is used well, the effect on individual contribution is significant. Consultants can apply their time and expertise where it matters most and shape the outcome of an engagement more directly, and that contribution becomes visible.
Building a Long-Term Career Alongside AI
Christoph does not believe AI will make consulting redundant, because the analysis was never the product.
The core of consulting is not the analysis or the insight we provide. It is more about decision assurance. A CFO wants to be sure that we will deliver and that they can count on us.
Clients need to know that a recommendation has been tested and validated, and that the expertise behind it is real. AI can support that process, but responsibility for the decision and for the client relationship ultimately remains with people.
As repetitive tasks become faster, consultants have more time for judgment, decision-making, collaboration and trust, as well as more room to go deeper into the analysis and bring their expertise to the questions that are hard to answer.
Keeping pace with that takes more than having AI tools available. At Inverto, consultants have access to the full range of AI tools alongside a dedicated training curriculum. That includes the AI Fluency Ladder, a BCG-designed program that helps colleagues build AI fluency as part of their development.
We need to be ahead of our clients and the best at what we do. That is why we invest heavily in ensuring our consulting teams are trained and enabled.
For anyone considering a consulting career, Christoph sees this as an opportunity.
For me, this is one of the most exciting times to be a consultant. AI can help us move away from some of the less enjoyable tasks and focus on what matters most: decision-making, trust and building strong teams.
AI is not reducing the impact a consultant can have. For people with the AI fluency, curiosity and judgment to use it well, it is expanding it.
10th August 2026
