Recruit and Maintain/Upgrade a High-Tech Workforce for Emerging Technologies
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Summary
This report addresses the challenge of preparing the Michigan Department of Transportation (MDOT) workforce for the rapid integration of emerging transportation technologies. Motivated by the transformative potential of technologies such as mobile robotics, Advanced Traffic Management Systems, Intelligent Transportation Systems (ITS), and big data analytics, the study aims to develop a ten-year strategy for recruiting, maintaining, and upgrading a high-tech construction and operations workforce. The primary goal is to ensure MDOT can identify expertise gaps and implement agile recruitment and training models to keep pace with technological advancements. The research was conducted by the Center for Automotive Research (CAR) and the Workforce Intelligence Network (WIN) through five substantive tasks. Task 1 involved reviewing MDOT documents and collaborating with project managers to identify five core technology focus areas, including mobile robotics and autonomous systems. Task 2 assessed the current industry state, MDOT’s organizational structure, and best practices from other state DOTs, utilizing data from the Bureau of Labor Statistics across five occupational categories: architecture/engineering, computer/mathematics, construction/extraction, life/physical/social sciences, and management. Task 3 developed a strategic plan using a SWOT analysis based on literature reviews and surveys of MDOT leaders. Task 4 analyzed five hard-to-fill occupations identified via internal surveys, examining occupational snapshots, current training landscapes, and skill gaps. Task 5 focused on recruitment planning, analyzing survey results, conducting interviews with education experts, and reviewing regional recruitment best practices. Key findings include the identification of specific emerging skills required for roles such as civil engineers, electricians, and highway maintenance workers. The study mapped Michigan’s educational programs against these needs, highlighting gaps in the current training landscape. The SWOT analysis revealed specific strengths, weaknesses, opportunities, and threats regarding MDOT’s workforce readiness. The report provides detailed recommendations for retraining the current workforce and acquiring new talent, including comprehensive recruitment flows for the five identified hard-to-fill positions. It also outlines strategies for improving the educational pipeline and marketing transportation careers to attract skilled employees. The significance of this work lies in its provision of a consolidated, actionable framework for MDOT to manage workforce development in the face of technological change. By linking specific emerging technologies to required competencies and available educational resources, the report enables decision-makers to bridge the expertise gap. The resulting strategies offer a nimble model for continuous adaptation, ensuring that MDOT can effectively integrate new technologies into its operations while maintaining a competent and efficient workforce over the next decade.
Key finding
The study provides a consolidated strategic framework for MDOT to bridge workforce expertise gaps in emerging technologies through targeted recruitment, retraining, and organizational restructuring.
Methodology
mixed_methods
Provenance
The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed. Discovered via bulk_ingest_rosap on 2026-05-23 (6 acquisition events logged).
| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | rosap | — | — | 2 | 2026-05-23 |
| archive | success | — | — | — | 1 | 2026-05-23 |
| extract | success | cached | — | — | 2 | 2026-06-10 |
| clean | success | — | — | — | 1 | 2026-06-01 |
| chunk | success | — | — | — | 1 | 2026-06-01 |
| embed | success | — | — | — | 1 | 2026-06-02 |
| enrich | success | — | — | — | 1 | 2026-05-23 |
| promote | success | — | — | — | 1 | 2026-05-23 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 3 | 2026-06-10 |
| tag | success | vector_similarity | — | — | 24 | 2026-06-11 |
| verify | success | — | — | — | 2 | 2026-06-10 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.
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