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Jonathan H. Westover

Exact-ORCID corpus identity

5Distinct papers

0Unique collaborators

5/5OpenAlex citation coverage

Publication span: 2026. Corpus fetch span: 2026.

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Identity provenance

Provider IDs

Openalex: A5077482961

ORCID evidence

0000-0003-0919-3286

Observed aliases (4)

Jonathan H. Westover (openalex, provider refresh)
Jonathan H. Westover (openalex, source metadata)
Jonathan Westover (openalex, provider refresh)
Jonathan Westover (openalex, source metadata)

Topics and outcomes in this view

Assessment themes

Org Design: 5 papers
Adoption: 3 papers
Governance: 3 papers
Human Ai Collab: 3 papers
Labor Markets: 3 papers
Productivity: 3 papers
Skills Training: 3 papers
Inequality: 1 paper

Claim outcomes

Organizational Efficiency: 5 papers
Governance And Regulation: 2 papers
Employment: 2 papers
Skill Acquisition: 2 papers
Inequality: 2 papers
Task Allocation: 2 papers
Adoption Rate: 1 paper
Firm Revenue: 1 paper
Fiscal And Macroeconomic: 1 paper
Job Displacement: 1 paper
Other: 1 paper
Automation Exposure: 1 paper
Training Effectiveness: 1 paper
Wages: 1 paper
Worker Satisfaction: 1 paper

Papers in the OpenAlex view

Latest stored OpenAlex author observations only. Citation counts below are from the same provider and are not combined with other services.

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Jonathan H. Westover's distinct papers under the selected provider observation surface.
Paper	Author evidence	Date
Firms that adopt AI are expanding workforces and paying more for advanced skills, PwC finds, implying AI often complements human labor; however, results are correlational and may reflect selection of better-resourced firms.openalex	Jonathan H. Westover provider id	2026-08-01
Management theory, not only software metaphors, is needed to govern multi-agent AI: concepts like decision rights and spans of control explain coordination breakdowns that orchestration patterns miss. Embedding organizational design principles into agentic systems could turn experimental agentic workflows into dependable organizational capabilities—though the recommendations are currently conceptual and require empirical validation.semantic_scholar	Jonathan H. Westover provider id	Fetched 2026-07-20
Experts see big AI capability gains but only modest near-term economic effects, while a notable minority (14%) warn of rapid-progress scenarios with strong GDP growth coupled with falling labor-force participation and widening inequality. Firms that invest in systematic retraining, transparent transition planning and adaptive organizational design can better protect workers and maintain operations amid accelerated AI-driven change.semantic_scholar	Jonathan H. Westover provider id	Fetched 2026-06-28
Firms that redesign how people and AI work together report markedly better returns: those intentionally architecting human–AI interactions are twice as likely to exceed AI investment targets and 2.5 times more likely to report superior financial performance. The result is drawn from a large Deloitte executive survey and illustrates associations, not proven causal effects.semantic_scholar	Jonathan H. Westover provider id	Fetched 2026-06-22
Emerging evidence suggests large language models reshape jobs unevenly: some occupations face substantial task-level exposure while real-world displacement remains limited and concentrated; firms that invest in transparent planning, reskilling and role redesign can both mitigate harm and capture productivity gains.semantic_scholar	Jonathan H. Westover provider id	Fetched 2026-04-29

Citation observation summary

OpenAlex supplied counts for 5 of 5 papers in this view; 0 are missing. The observed paper counts sum to 0 cumulative citations. This is a coverage summary, not an author score or h-index.