# Jenn Simon

Jenn Simon focuses on enterprise contingent workforce strategy, including workforce planning, procurement coordination, and the use of AI in workforce programs.

- Profile: https://b2binfluencer.marketing/creators/jenn-simon/
- LinkedIn: https://www.linkedin.com/in/jenn-simon
- LinkedIn followers: 2,001
- Topics: artificial-intelligence
- Based on 17 dated posts, latest 2026-10-05

## Summary

Jenn Simon is useful for practical explanations of enterprise contingent workforce strategy, AI adoption, and procurement alignment.

- Best for: A workforce solutions or MSP company hosting a thought-leadership webinar on AI and procurement alignment.
- Not for: It is not for paid endorsement, reach-led distribution, or sponsored-content packages with rates and deliverables.
- Check first: Confirm whether they accept sponsorships and ask for rates, deliverables, and audience data.

### Takeaways

- AI in contingent workforce programs moves from automation to decision intelligence to orchestration.
- Data readiness, not technology, is the biggest barrier to AI success.
- Workforce planning and procurement orchestration have to be built together.

## Main ideas

- **AI in contingent workforce programs moves from automation to decision intelligence to orchestration**: Jenn Simon argues that most organisations use AI to automate individual contingent workforce tasks, while leading organisations use it to coordinate workforce decisions. Familiar use cases—candidate screening, sourcing, rate benchmarking, supplier performance management, compliance monitoring, and workforce analytics—deliver value today, but each covers a single step. The next stage, decision intelligence, improves talent matching, workforce planning, and supplier optimisation. After that comes orchestration, where AI connects workforce data, talent channels, suppliers, and workforce strategy across the wider ecosystem. Simon frames the question as how to improve quality, efficiency, cost, and risk outcomes—not whether AI will affect a program at all.
- **Data readiness, not the technology, is the biggest barrier to AI success**: Simon identifies the state of the underlying data, rather than the availability of tools, as the constraint on AI progress. Rate intelligence, talent matching, and workflow automation are already producing measurable business value; the limiting factor is whether a program's data can support more advanced matching and planning. In the research summary Simon attributes to SIA, that finding sits alongside an AI maturity model, a practical implementation roadmap, and an AI governance framework. Ask for the report to assess its underlying claims.
- **Workforce planning and procurement orchestration have to be built together**: Simon argues that enterprise buyers often separate workforce planning from procurement execution, and that the gap between them is where cost, speed, and compliance break down. Forecasting skills, modelling demand, and rethinking talent mix set direction, but those plans cannot survive execution if procurement remains reactive—especially as programs expand into statement of work, direct sourcing, and hybrid models. Mature buyers define decision rights and plan around capabilities instead of headcount. Simon rejects the either/or framing: organisations need both planning and orchestration, built continuously and at scale.
- **Governance, accountability, and human oversight are conditions of AI adoption, not disclaimers**: Simon treats oversight as part of the argument for AI, not a caution added at the end. Programs pursuing quality, efficiency, cost, and risk improvements must preserve governance, accountability, and human oversight as they scale. That is why an AI governance framework appears alongside the maturity and implementation material, rather than as a separate compliance topic. Automation alone is not the goal.
- **Research is distributed through Council membership and practical event orientation**: Simon’s public posts regularly direct readers to Staffing Industry Analysts articles and CWS Council membership for fuller research. The same teaching priority appears at conferences: Simon describes a pre-conference session as a practical orientation, not a research presentation, covering how to navigate the agenda, key locations and logistics, connect with peers and solution providers, and use SIA and Council membership resources throughout the year.

## Work to read

- [AI in CW Programs: From Automation to Orchestration](https://www.linkedin.com/posts/jenn-simon_ai-contingentworkforce-workforcestrategy-activity-7475194204466479104-1uZH)
- [Automation was just the beginning — the research summary](https://www.linkedin.com/posts/jenn-simon_artificialintelligence-contingentworkforce-activity-7485336369955749890-sVTZ)
- [Strong workforce plans don't guarantee strong outcomes](https://www.linkedin.com/posts/jenn-simon_workforce-planning-or-procurement-orchestration-activity-7427417028786966528-YUpN)
- [Part 2 — connecting strategy to disciplined execution](https://www.linkedin.com/posts/jenn-simon_workforce-planning-or-procurement-orchestration-activity-7432502845922349056-t3O_)
- [CWS Summit North America pre-conference session](https://www.linkedin.com/posts/jenn-simon_cwssummit-cwssummitnorthamerica-activity-7482390881040494593-UFET)

## Brand relationships

- **Staffing Industry Analysts** (employment)

## Partnerships

Across the five posts, Jenn Simon does not present sponsorship, brand-partnership, or paid-collaboration formats. The commercial activity is organizational: posts point readers to Staffing Industry Analysts (SIA) research articles and reports, CWS Council membership as the route to that research, and SIA conference programming, including a pre-conference orientation session at CWS Summit North America. The posts include no rates, deliverables, sponsored-content examples, or personal partnership terms. Before committing, ask whether they offer sponsored content, webinars, or paid speaking engagements, and request a rate card or past sponsored examples.

## Alternatives

- Josh Neuhart: Choose Josh Neuhart when the session's value is operational staffing diagnosis rather than program-level AI strategy. The two posts lay out a repeatable method: take the highest-turnover locations, pair each with a similar location performing well inside the same company, then isolate what differs — whether pay is actually competitive within a 10-mile radius; whether an 11:00 AM–7:30 PM shift and a 7:00 AM–3:30 PM shift are the same recruiting problem at the same wage; whether someone can realistically reach a 5:00 AM start without a car; how long a qualified candidate sits between submission, interview and decision; and what actually happens in someone's first week. The defense manufacturing post applies the same logic at task level: a shift can report fully staffed while one qualified and authorized inspector holds up a delivery. The review asks who can perform each critical task on the scheduled shift, who is an authorized backup, whether that backup leaves another operation uncovered, and how long it would take to prepare someone else. For an MSP or workforce solutions sponsor whose buyers run distributed sites — food service, facilities, hospitality, defense suppliers — that method gives the audience an exercise they can run on their own locations the following week, a more concrete takeaway than an AI maturity model.
- Shyo Koshy: Choose Shyo Koshy when the audience is Gulf employers or the webinar needs a regional market-and-policy angle instead of a program-design one. The posts assemble current GCC workforce signals: Saudization in selected project management professions rising to 70% from 14 February 2027; real estate recording the highest hiring growth against 2019 levels while construction, healthcare, education, transport and logistics, and administrative and support services stay above the national hiring average; the UAE ranking first globally in FinTech skills and second in attracting AI talent relative to population size; a government forecast of roughly 200,000 jobs across solar, battery and hydrogen under the Net Zero 2050 strategy; and DIFC reaching 1,933 AI, FinTech and innovation companies in the first half of 2026, up 39% year on year, against an ambition to become the world's first AI-native financial centre. The second post extends the map to Sharjah Publishing City's 1,000-plus AI companies, Oman's 24 investment agreements across ports, airports, transport, storage and smart logistics, and Qatar Development Bank's investment in Multiverse Computing. Koshy frames the shift as moving from "how many people do we need?" to "what capabilities will we need next?" — a usable hook for a capability-planning session.
- Roger Gorman: Choose Roger Gorman when the sponsor wants a technology-vendor founder's view of the same orchestration question or a co-host with a platform and convening angle. The posts argue that resourcing optimisation is becoming the control plane — the orchestration layer where people meet work, humans meet agents, and capability is deployed in real time — and describe operating that at scale, with 500,000 workers newly matched to millions of projects and tasks inside large professional services environments. Gorman also runs ProFinda Connects in Chicago, an event series deliberately kept small and under Chatham House Rule. It is built around what happens when the human workforce and the agent workforce collide. The agenda named in the post — how workforces transform, how skills and capacity get planned when the available workforce is no longer only human, where AI agents sit, what humans should keep, and how to orchestrate it without adding complexity — overlaps closely with a sponsor seeking a session on orchestration and procurement alignment. If the format becomes a panel or debate about the division of labour between people and agents, or the sponsor wants a platform-side voice alongside a practitioner, Gorman is a plausible alternative.

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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/