# Sarah Toomey

Sarah Toomey leads procurement within Levelpath’s finance team. Toomey has built and run procurement functions at technology companies and writes about procurement processes, AI automation, and supplier relationships.

- Profile: https://b2binfluencer.marketing/creators/sarah-toomey/
- LinkedIn: https://www.linkedin.com/in/satoomey
- LinkedIn followers: 2,577
- Topics: artificial-intelligence, procurement, ai-in-procurement
- Based on 11 dated posts, latest 2026-09-10

## Summary

Useful for procurement and finance software campaigns that need a practitioner explaining process-first AI adoption.

- Best for: Enterprise procurement or finance software vendor wanting sharper messaging for AI-assisted buying.
- Not for: Consumer or lifestyle brand seeking broad reach, product reviews, or aesthetic creator content.
- Check first: Confirm whether they offer creator partnerships, terms, rates, and audience analytics.

### Takeaways

- Change the process before buying procurement software, or new tools disappoint.
- AI can handle contract scanning, bid comparison, and intake triage.
- Automation raises the value of supplier relationships, negotiation, and human judgment.

## Main ideas

- **Change the process before you buy the tool**: Sarah Toomey argues that procurement software succeeds or fails on what happens before the purchase. Teams that get results from new tools change how they work first; teams that buy good software and see no improvement usually run it on top of unchanged processes and policies. They apply the same test to AI: the technology works only as well as the process it supports, so teams should rethink and update the job before choosing a tool built for the new version.
- **Automation makes relationship work more valuable, not less**: As AI takes over contract scanning, bid comparison and intake triage, Sarah Toomey expects human procurement work to become more valuable, not redundant. What remains includes building supplier relationships to secure better deals, turning vendors into partners through negotiation and making judgment calls about where a deal lands. They describe finance as the function that helps the business reach a yes faster, not a checkpoint that slows it down. Automation lets them spend more of the day on those relationships and decisions.
- **Speed and rigor are not opposites — buyers need visibility**: Sarah Toomey argues that buying AI is often the slowest and most expensive purchase an enterprise makes, even as businesses want new tools live immediately. Security reviews, more stakeholders and longer cycles are nothing new, they say; those steps used to be called rigor. What changed is that businesses under pressure now treat rigor as a bottleneck. The teams pulling ahead are not skipping steps: they build visibility so they can keep pace with the business while knowing exactly what they signed up for.
- **AI-native as a foundation, with the process expert building the automation**: Sarah Toomey treats an AI-native approach as a foundation, not a feature bolted onto existing software. In keeping with their process-first view, they highlight that anyone can build a procurement agent in plain language in Levelpath, with no technical background required. That lets the people who know the process best automate it: the tool meets the workflow expert rather than requiring them to become a developer.

## Work to read

- [Introducing Ranger, Levelpath's autonomous source-to-pay platform](https://www.linkedin.com/posts/satoomey_i-fell-into-sourcing-15-years-ago-and-never-activity-7503864757632835584-dqcg)
- [Why buying AI is slow and expensive for enterprises](https://www.linkedin.com/posts/satoomey_buying-ai-is-often-the-slowest-most-expensive-activity-7486453899428585472-ap2-)
- [Process first, then procurement technology](https://www.linkedin.com/posts/satoomey_the-teams-i-have-seen-win-with-new-procurement-activity-7483987234082168832-ufQw)
- [AI takes on procurement tasks, making relationships more valuable](https://www.linkedin.com/posts/satoomey_ai-is-taking-on-more-procurement-tasks-every-activity-7481380472120373248-Kq9O)
- [Plain-language procurement agents for process experts](https://www.linkedin.com/posts/satoomey_taylor-makes-this-look-easy-in-levelpath-activity-7478118982047252480-zMfe)

## Brand relationships

- **Levelpath** (employment)

## Partnerships

No partnership or sponsorship program is described in Sarah Toomey's posts. They write as a procurement practitioner working inside Levelpath's finance team, and the commercial content is tied to that employer: announcing Levelpath's Ranger source-to-pay platform, sharing a colleague's take on AI buying cycles, and linking to Levelpath pages. That is an employer relationship, not a creator partnership offer with published formats, terms, or rates. Any collaboration would need to be negotiated individually rather than selected from a listed package. Ask directly about deliverables, pricing, disclosure practice, availability, and how to inquire about partnerships. Brands should also expect their public activity to sit close to Levelpath's product narrative rather than run as independent sponsored placements.

## Alternatives

- Matt Barnard: Choose Matt Barnard over Sarah Toomey when the campaign is aimed at the finance side of the same decision — the CFO or finance leader who has to answer what the company spends on AI and whether the approval process is holding the business back. His posts approach procurement from the finance seat: a first-person account of how the approval model broke between 50 and 500 people, why adding more gates only moves the bottleneck to a committee, and what replaced it — low-risk requests routed and approved automatically, high-value contracts flagged with the context to decide fast, and compliance checks built into the workflow rather than added after the fact. A second post tackles the same problem from the spend side, arguing that a finance leader's job is not to shrink the AI number but to know what drives it and where it can be optimised — something that cannot be answered from a bill read after the event. For a vendor whose product story is spend visibility or approval logic embedded in the workflow, Barnard is a more direct match than a process-and-supplier-relationships argument.
- Vinod Kumar: Choose Vinod Kumar when the campaign is aimed at retail, ecommerce or merchandising rather than enterprise procurement. His work covers a neighbouring question — how an AI assistant should decide what a shopper sees — from the merchandising seat. One post breaks product discovery into five functions: answering a question, retrieving products, reading shopper intent, deciding what gets shown, and carrying the merchant's accumulated judgment. His argument is that most vendors build the first two or three and call the job done, while the ranking and curation decisions are where the value sits. A second post reports an AI-visibility audit that found one brand surfacing consistently in ChatGPT and largely missed in Gemini across tested shopping queries. It separates two questions most vendors collapse: whether a brand is mentioned, and what the AI says about it. For a vendor selling a conversational agent whose real value lies in deciding what appears rather than in the chat layer, Kumar names the problem more precisely than a process-first procurement argument.
- Ali Oztan: Choose Ali Oztan when supplier negotiation and cost data are the focus rather than the adoption process. One post takes a single procurement problem and shows the mechanism: a supplier requests a 15% price increase; the information asymmetry behind the request gives way to a counter based on identifying the cost drivers in a part, comparing the request against relevant producer price indices and a should-cost model, and giving the buyer objective data before negotiating. The second post explains why that cost work is skipped in the first place, tracing it to incentives: design engineers are rewarded for speed, so cost and lead time are optimised later, when changing anything is expensive. Cost modelling happens only if it is fast enough to fit the design cycle. For a vendor whose product supports negotiation, should-cost or supplier cost analysis, Oztan's material sits closer to the product than Toomey's process-first argument.

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AI-assisted summary of public posts. Audience demographics are not available. Engagement appears only where we checked recent posts. Method: https://b2binfluencer.marketing/methodology/