# Michael Taylor

Michael Taylor writes about using AI and data analysis to find payment errors, recover value, and improve contract compliance in procurement and finance.

- Profile: https://b2binfluencer.marketing/creators/michael-taylor/
- LinkedIn: https://www.linkedin.com/in/cheblanco49
- LinkedIn followers: 21,637
- Topics: artificial-intelligence, ai-in-procurement
- Based on 16 dated posts, latest 2026-10-07

## Summary

They explain how finance and procurement teams use data and AI to find payment errors and contract compliance gaps.

- Best for: Contract-intelligence SaaS companies targeting finance, procurement, and accounts payable leaders for webinars and whitepapers.
- Not for: Neutral category guides or broad AI-leadership campaigns needing independent commentary, vendor comparisons, or measured audience delivery.
- Check first: Ask for recent comparable results and audience job function, seniority, and geography data.

### Takeaways

- Review one theme, like rebates or payment terms, across contracts and invoices.
- Oilfield technology company review of six million invoices returned $6 million, mainly rebates.
- Retailer audit found more than $12 million in recoverable value before process changes.

## Main ideas

- **Compliance failures come from process falling behind volume, not from bad intent**: Michael Taylor lists six practices for keeping contracts enforceable after signature: maintain one central, searchable repository with version and access controls; build obligation tracking into the process at signature rather than rediscovering obligations during a dispute; use approved clause libraries and playbooks before negotiating; continuously monitor service levels, milestones and pricing accuracy; keep a retrievable audit trail of every amendment, approval and communication; and assign one named person, not a department, accountability for each contract. The diagnosis: teams fail not from bad intentions but because scale outpaces process. A vendor that combines contract technology with service support can close the gap.
- **The question that finds the money is whether you actually get what you negotiated**: Taylor poses the same question to a chief financial officer and a hospital supply chain lead: are we actually getting what we negotiated? The link between a signed agreement and the invoices that follow breaks when an ERP system is upgraded or a buyer leaves, so rebates, tiered pricing, payment terms and rate caps drift out of line with what is paid. The recommended answer is an independent third party with no stake in defending any one system, working across procurement, accounts payable and the ERP, and repeatedly comparing contracts with invoices. The ends differ by sector, in Taylor's framing: finance wants the cash; healthcare wants margin back for patient care.
- **Recover the leak, then fix the process that produced it**: Recovery audits are more than a one-time cash find. Taylor argues that transactional errors, duplicate payments, missed credits and supplier overcharges drain money already earned. The lasting fix is root-cause analysis: identify the process flaw behind the leakage so the improvement holds. Working capital optimization, in this view, is not about squeezing the business or damaging supplier relationships. The commercial model is often contingency-based, paid out of what is recovered, so the work can fund itself. Taylor's rule of thumb is to run a global recovery audit at least every two years.
- **Let AI read at volume, keep the judgment with people**: Taylor argues AI is becoming core business infrastructure and that contracts are among the most underused places to apply it: surfacing risks, leakage and non-standard terms across thousands of contracts in hours; continuously comparing actual spend and performance against contracted terms; and shifting playbooks toward optimization rather than compliance alone. The counterweight is human judgment about which categories to challenge and how to turn insights into better deals. The design they describe is 'AI proposes, humans dispose': the system flags potential non-compliance and missed benefits, while experts apply context, judgment and client strategy. Machine-learning ideas are explained in procurement terms—pattern recognition, anomaly detection and supervised learning trained on years of audit data—which Taylor says turns static contracts into continuously learning systems.
- **Shrink the question to find the pattern**: A repeated teaching move is to narrow the scope deliberately rather than audit everything at once. Pick one theme, such as rebates, payment terms, rate caps or pricing tiers, and test every contract and invoice against that single question. Patterns surface quickly, and the usual fix is a process change rather than recovery of one invoice. The same logic runs upstream: standardize clause libraries and negotiation playbooks before signing. The fewer bespoke terms in circulation, the easier downstream compliance becomes.

## Work to read

- [The Core Practices of Strong Contract Compliance](https://www.linkedin.com/posts/activity-7505284838858407937-CFEJ)
- [Checking what you negotiated against what you pay](https://www.linkedin.com/posts/activity-7512493733343350784-569Q)
- [Six million invoices, one oilfield technology company](https://www.linkedin.com/posts/activity-7390018310593183744-rCNJ)
- [A global retail recovery audit and a $12M find](https://www.linkedin.com/posts/activity-7384609010228043776-6EAH)
- [AI, Contracts, and the Next Frontier of Value for Procurement](https://www.linkedin.com/posts/activity-7453078677237698561-dEJQ)
- [Human Compatible: keeping people in the AI loop](https://www.linkedin.com/posts/activity-7437507422065258496-ZbSP)

## Brand relationships

- **PRGX** (employment)

## Partnerships

Michael Taylor's LinkedIn explainers position PRGX's AI contract-review and recovery-audit products as a fix for payment leakage, contract compliance gaps, and lost working capital. Several cite client outcomes in concrete figures: six million invoices screened, $50 million in duplicate payments caught, $22 million in working capital unlocked, and $12 million recovered in a single retail audit. Two posts invite readers to contact Taylor for a complimentary payment-accuracy assessment—a customer sales route, not a partner or collaborator route. The content is closely tied to one employer's product line and uses an operational, example-first style, covering contract-to-invoice matching, obligation tracking, thematic reviews, and human-in-the-loop AI. Before planning a contract intelligence campaign, ask whether Taylor takes on independent speaking, webinar, or whitepaper work; the posts do not address those opportunities.

## Alternatives

- Simon Frost: Choose Simon Frost when the campaign’s hook is how procurement teams use AI agents and what skills buyers need, rather than where contract value leaks after signature. The posts are written for that audience and argument. One explains what an AI agent is, as distinct from ordinary AI: it plans, searches, checks, adapts, repeats, and delivers a shortlist with evidence. It then lists what agents can do in procurement: analyse spend, research markets, discover suppliers, prepare sourcing events, compare responses, create and monitor contracts, track supplier performance, identify supply risks, support negotiations, and create reports. It also lays out the buy-versus-build question and the boundary between autonomy and oversight, noting that an agent researching 50 suppliers is a different decision from one selecting a supplier, negotiating, and committing $5M. The other post reports a poll where 81% of respondents ranked category management skills above category knowledge. It argues that AI closes knowledge gaps fast, while the human work — stakeholder engagement, commercial judgement, communication, influencing, curiosity, storytelling, leadership, critical thinking, and relationship building — becomes more valuable. Frost also runs a training offer, the Procurement Adventurer Academy, with the next cohort stated as February 2027. The fit is strongest for a campaign about procurement capability and AI adoption, and for a practitioner-training audience.
- Martin Foerster: Choose Martin Foerster when the campaign has to reach compliance, legal, and vendor-risk buyers and the argument is regulation-driven rather than recovery-driven. Both posts take a regulation and work through what it means for contracts. One covers the EU Data Act, in force since 12 September 2025, which gives customers of data processing services switching rights with a defined notice period and transition window, and phases out switching charges from 12 January 2027. The post argues that existing cloud contracts probably still conflict with it through egress fee schedules and vague assistance obligations, and that this strengthens DORA exit strategies for critical functions. The other covers NIS2 Article 21(2)(d) supply chain security. It argues that an annual vendor questionnaire is not compliance, lists what the obligation actually pushes toward — security requirements in the contract, a supplier incident notification duty, defined rights on evidence and subcontractor changes, and a response path when a supplier reports at 23:00 — and gives a sequencing method that ranks suppliers by the function they support rather than contract value, with German BSIG management liability noted. That is a sharper fit than Taylor for a campaign aimed at regulated-sector compliance teams making contract changes on a statutory deadline.
- Chris Wicker, MBA: Choose Chris Wicker when the campaign targets hospitality or property-management finance teams and the problem is AP process design across many properties rather than contract terms. One post runs a nine-question diagnostic that starts where a demo would not: how invoices arrive today — at the property, at head office, in both, or in four formats depending on the vendor; who keys the data by hand and for how many hours a week; how long one invoice takes from receipt to approval and how many reminder emails it costs; when a vendor was last paid twice and whether anyone would know. It then covers duplicate detection, exception handling, invoice-history search, and how long a new AP hire takes to become useful, framing the nine steps as a diagnostic rather than a pitch. The other groups finance and accounting executives’ recurring concerns into margin, people, and visibility — costs rising faster than rents, lean teams, and payables invisible until close — and argues these are one problem: an AP process built at eight properties scales by adding effort rather than structure. Growth does not break AP; it stops hiding what was already fragile. That is a strong fit where the campaign needs a vertical-specific AP process assessment rather than a general contract-compliance message.

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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/