From the Campus Operations edition of September 28, 2026
AAUP On-the-Field playbook pushes workers into AI procurement mapping, RFI/RFP influence, and CBA tech clauses
American Association of University Professors (with Collaborative Research Center for Resilience / NYU Law clinic) · Higher education labor / shared governance / technology procurement · United States (higher-education focused playbook with cross-sector examples)
- Publisher
- American Association of University Professors
- Original publication
- September 2026 (AAUP 2026-09 toolkit path)
- Source retrieved
- 2026-09-29
What happened
AAUP's 2026 On the Field playbook (hosted under the association's September 2026 AI activism toolkit path) gives workers and unions a stage-based strategy for intervening in AI and technology procurement before, during, and after contract award. Thirteen plays cover procurement power mapping; collective-bargaining contract audits; raising awareness of tech harms; designing tech-focused bargaining demands; redefining the employer problem; drafting RFIs/RFPs; public advocacy; vendor and technology evaluation; leveraging worker decision-making; demanding ongoing transparency; addressing harms; planning pauses/moratoria; and strikes or scrapping AI. Higher-education illustrations include Michigan LEO-GLAM and University Staff United joint technology committees, other campus CBA references (CUNY, Yale, Brown, Oregon State, Maine AFUM), and the SEIU668 Pennsylvania generative-AI labor-management group that raised PII concerns and saw pilots slowed. The document argues early problem-definition and RFI/RFP influence prevent surveillance and automation harms that audits alone cannot unwind.
Why it matters
Campus-operations labor and procurement-constraint evidence for administrative AI acquisition—not instructional AI policy alone. Why now: never archived; distinct from the archived AAUP/AFT Tech Audit Guide by focusing on procurement-stage plays; newly relevant alongside Pitt contract/indemnification friction and URI gateway centralization.
Evidence and measured results
Opened AAUP HTTPS PDF and confirmed toolkit linkage describing it as a higher-ed procurement playbook. Association guidance with cited CBA examples; not measured deployment outcomes.
Limitations and uncertainty
Advocacy playbook without campus outcome metrics; exact day-of-month not printed on cover (September 2026 path); cross-sector plays need HE adaptation.
Put this evidence to work
Lighthouse Advisory interpretation, grounded in this source. Enriched 2026-09-28; this does not change the original publication date. Each role follows the same checklist so takeaways compare across sources.
Sales
Role takeaway
- Customer problem
- Campus AI procurements proceed without worker visibility, creating later bargaining conflicts, privacy incidents, and stalled pilots.
- Stakeholders
- CIO
- Procurement
- HR/labor relations
- Faculty/staff unions
- Shared governance bodies
- Discovery questions
- What CBA clauses cover technology notice or committees?
- At what procurement stage are current AI pilots?
- Can unions request vendor contracts and data-flow docs?
- Have any AI pilots been paused over PII or jobs?
- Value hypothesis
- Transparent procurement with early worker input can reduce later stoppages—AAUP offers process plays, not proof of faster deployment.
- Potential engagement
- Five-week AI procurement resilience review: map intake stages, draft RFP AI addendum, and align labor-management checkpoint calendar.
- Unsupported claims
- Guaranteed strike avoidance
- Guaranteed faster procurement
- Playbook as binding campus law
Pre-sales engineering
Role takeaway
- Fit
- AI solutions whose architecture and contracts answer worker evaluation questions on data, oversight, bias, and kill-switch before award.
- Architecture and integration
- Attach AI vendor fact sheets, data-flow diagrams, logging/override designs, and secondary-use controls to RFI/RFP packages.
- Prerequisites
- Procurement process map
- CBA/info-request path
- Privacy review capacity
- Vendor questionnaire
- Constraints
- Advocacy source
- Variable union density
- Pilot rules may bypass full RFP scrutiny
- Security
- Require disclosure of training/retention, subprocessors, and unattended remote-access risks; mandate human gates for consequential admin actions.
- Proof of value
- Completed vendor evaluation rubric
- Documented kill-switch/override design
- PII handling accepted by privacy/labor reviewers
Delivery
Role takeaway
- Work
- Embed committee review in intake, run vendor Q&A, negotiate transparency/audit clauses, and define pause triggers for unresolved harms.
- Dependencies
- Procurement
- Labor relations
- Privacy/CISO
- Application owners
- Legal
- Ownership
- Procurement lead with HR/labor relations co-ownership for bargaining impacts; CIO for technical standards.
- Skills and adoption
- Train procurement and IT owners to answer Play 8-style vendor questions; brief committees without dumping raw marketing PDFs.
- Governance checkpoints
- Pre-RFI problem definition with workers
- Pre-award vendor evaluation
- Post-award monitoring report to committee
- Acceptance criteria
- AI RFP addendum used on next admin AI buy
- Committee review recorded before award
- Contract transparency clause present
- Risks
- Process delay without decision rules
- Symbolic committees without data access
- Scope creep after pilot
Implementation considerations
Lighthouse Advisory interpretation across the operating dimensions a public-sector buyer must settle before this evidence becomes a design. Each note answers the question under its heading for this specific source.
Architecture and integration
What must connect, and where does the AI sit in the workflow?
Expect unions/shared governance to demand evaluation access to vendor materials, logging/kill-switch evidence, and limits on secondary surveillance uses when campuses procure admin AI gateways, SOC tools, or ERP AI modules.
Governance
Who approves, reviews and stays accountable for outcomes?
Build notice-and-comment or labor-management review into AI procurement timelines; document decision-maker knowledge before deployment; treat pilots as high-leverage intervention points.
Security and privacy
What data, permissions and controls need testing?
Playbook elevates PII/public-service confidentiality (SEIU668 example) as bargainable constraints that can pause generative-AI pilots lacking adequate protections.
Accessibility and workforce
Who is affected, and what skills or accommodations follow?
Centers worker voice on job quality, surveillance, and service quality; aims to prevent AI-driven speedups and displacement in administrative roles.
Procurement
What should contracts, pricing and exit terms secure?
Treat RFI/RFP drafting and vendor evaluation as mandatory shared-governance touchpoints for administrative AI; pilots should not permanently evade competitive scrutiny.
Operating model
Which teams own the service once it runs?
Shifts AI introduction from IT-only purchase to staged labor-aware procurement with pause authority when PII or working-condition harms appear.
Publication history
- 2026-09-28Campus Operations · Issue 214 resources
Stable resource ID: aaup-on-the-field-ai-procurement-playbook-202609