AI negotiation can generate ROI quickly, but you need to know where to begin – and this is the question I am asked the most: “give me some examples of where it is working?”
It’s very easy to get carried away with the implications of what AI negotiation could do for you (tell me about it 😆😉) but, in our experience, an AI negotiation POC pays for itself fastest when your sourcing work has three characteristics:
- High volume: hundreds (or thousands) of similar negotiations per month — usually driven by a long tail of suppliers.
- Tactical rather than strategic: fixed scope, repeatable requirements, and relatively interchangeable suppliers.
- Low-touch today: renewals roll over, price increases get accepted, and the team wishes it had time to run more RFQs… but doesn’t.
The sweet spot you are looking for is a category that has lots of repeatable value left on the table, and not enough human capacity to pick it up.
Why these categories produce fast ROI
The categories that pay back fastest have two things going for them:
- The maths works. There’s enough volume and enough value per interaction that even modest improvements stack up quickly.
- The operational friction is low. You can standardise the approach, reuse playbooks, and run negotiations without turning every event into a bespoke project.
Remember, you don’t need perfection on day one. You need scale. Most teams don’t have a savings problem in their strategic categories, rather they have a coverage problem in their long tail. i.e. they are just not spending enough time on it.
The categories to start your AI negotiation POC in
Below are the “usual suspects”. Not because the category names themselves make it so, but because they often contain repeatable, under-negotiated buying motions.
1) Facilities management
Why it pays back fast: local supplier long tail, frequent renewals, and lots of negotiable levers beyond price. What AI negotiation is great at:
- extending payment terms
- standardising SLAs and contract language
- handling renewal conversations at scale
Typical use case: a working capital optimisation push where you extend payment days across dozens or hundreds of small suppliers without emailing each one manually.
2) Consumables and packaging
Why it pays back fast: high frequency, fixed specs, and relentless “inflation” requests. What AI negotiation is great at:
- challenging price increase requests consistently and with reference to market benchmarks to demand high quality reasons for any increase
- running multi-supplier quote comparisons
- enforcing standard terms (and making exceptions visible)
Typical use case: reduce inflationary increases by responding to every request with a consistent negotiation blueprint at volume.
3) MRO, fasteners, and standard components
Why it pays back fast: the work is repetitive, the events are “too small to bother”, and the cycle time cost is high. What AI negotiation is great at:
- running small RFQs quickly
- increasing competition among approved suppliers
- closing on price + payment terms without weeks of admin
Typical use case: convert “email-and-spreadsheet RFQs” into fast, governed, repeatable negotiations that actually get run.
4) Transport and logistics
Why it pays back fast: AI negotiation can replace cumbersome auction processes, ensuring each supplier gets a fair chance to offer their best terms while buyers achieve faster, more balanced outcomes.
What AI negotiation is great at:
- balancing price with service requirements
- finding the best bidder extremely fast allowing speedier decisions
- giving each supplier a structured, fair process (without running a heavy auction every time)
Typical use case: run an automated, simple auction process with small medium haulage providers to collect their best terms.
5) Chemicals and lubricants
Why it pays back fast: recurring volumes, repeat specs, and often a manageable supplier set with benchmarkable (is that a real word 😂) pricing. What AI negotiation is great at:
- periodic price revalidation
- negotiating terms on recurring buys
- preventing “silent rollover” creep
Typical use case: stop paying renewal-by-default pricing when nobody has time to revisit it.
6) Basic SaaS renewals
Why it pays back fast: lots of small renewals simply get waved through, even when usage has changed. What AI negotiation is great at:
- aligning price to actual usage / seat counts
- tightening renewal terms
- standardising requirements like e-signature, payment terms, and renewal notice periods
Typical use case: recover budget by right-sizing and negotiating consistently without turning it into a procurement “project” each time you need to renew non-core and small software contracts.
7) Repeatable engineering & fabrication services
Why it pays back fast: predictable scopes exist more often than people admit (machining, inspection, welding, standard jobs). What AI negotiation is great at:
- quoting and rate alignment for repeat scopes
- turnaround time and scheduling trade-offs
- reducing the admin burden on technical stakeholders
Typical use case: faster cycles and fewer “we just accepted it because we were busy” outcomes. It still allows decisions to be made locally and within the business unit so business can proceed at pace. This is about Procurement facilitating the business and being a commercial partner to their needs and not slowing tings down.
A simple way to find your fastest-payback categories
The best categories vary by industry and business type but hopefully the examples above have given yu some great ideas.
If you want to identify where an AI negotiation POC will pay back fastest in your business, don’t start with a category map. Start with a filter. Look for pockets of work that score highly on these areas:
- Volume: how many negotiations / renewals / RFQs per month?
- Repeatability: could you reuse the same playbook 50 times with minor changes?
- Under-negotiated today: do these roll over, or get accepted by default?
- Low exception rate: are outcomes usually within standard guardrails?
- Clear negotiation levers: e.g. price, payment terms, SLAs, rate cards, renewal terms.
If a category area ticks most of these boxes, it’s a strong candidate even if the category name isn’t on anyone’s “AI negotiation list”!
Where AI negotiation adds less value (and why)
There are still categories where humans are the right tool:
- Highly strategic suppliers and relationship-led negotiations
- Highly bespoke scopes which often occur in software contracts
- Complex multi-variable deals where creativity and stakeholder alignment are the work like marketing services annual contracts
- High-risk operational categories without clean escalation and approval paths
AI negotiation isn’t about replacing senior procurement expertise. It’s about finally covering the work that isn’t getting covered and doing it safely, consistently, and at scale.
Your key takeaway
The categories where AI negotiation pays for itself fastest are the ones hiding high-volume, repeatable, low-touch negotiations. Basically, it’s the places where value leaks simply because nobody has enough time.
If you want to move quickly, don’t debate category theory for weeks. Give us a call! We can run a no integration test fr you in 4-6 weeks
Pick one or two areas that match the buying pattern, define clear guardrails, and run enough volume through to let the ROI show up. Once you can prove negotiation at scale, it becomes much easier to develop further use cases and branch out into wider categories or explore your ‘bigger’ AI negotiation ideas.
If you are interested in diving deeper into ROI to check this project doesn’t need budget allocation, I wrote about that last week here: https://blog.nibbletechnology.com/how-to-calculate-roi-for-ai-negotiation/
Find out more from Nibble’s experience negotiating 100,000 times a month here.
Just One More Thing
NEC — Japan’s first tender where both sides can be AI agents
Why it’s interesting: This is early evidence of agent-to-agent negotiation in live commercial settings. NEC isn’t automating tasks; it’s automating the entire exchange — rules, proposals, counters, and agreement. NEC position it as a way to “eliminate the need for human intervention in basic procurement,” not least because it sets its own rules for concessions requiring minimal input from the human team.
Details as follows: https://www.nec.com/en/global/solutions/ai/analyze/negotiationai.html
“NEC’s proprietary Negotiation AI replaces human-led coordination and negotiation tasks. It automatically derives non-negotiable conditions and desirable outcomes, then proposes favorable terms that are likely acceptable to the counterpart. This AI is designed not only for human-AI negotiations but also for AI-to-AI interactions.
While solutions for adjusting between AI-to-AI exist, most of them involve sharing data or setting rules for mutual concessions in advance. This Negotiation AI is NEC’s unique technology and does not rely on “data sharing” or “cooperative control,” but rather on adjusting and negotiating with the counterpart.”
Initial use cases are being trialled in procurement and logistics for NEC.
