Ross DeVol
Chairman Emeritus and Distinguished Fellow

Across the heartland, regions are increasingly competing in an AI cluster race defined by tangible, complementary assets: research capacity, large-scale adopters, talent depth and governance that enables responsible deployment. While coastal metros often dominate the national conversation, many heartland regions are quietly assembling the components necessary to emerge as durable AI hubs. In this race, success is less about a single breakthrough and more about the integration of universities, anchor firms, workforce pipelines, and public-sector leadership. As part of a series evaluating heartland metropolitans’ readiness in the AI cluster race, this piece examines the Minneapolis–St. Paul metro area, which stands out as one of the most complete AI ecosystems in the northern heartland, combining institutional strength with practical, large-scale adoption.

The Minneapolis-St. Paul metro area combines exemplary university-based research strength, large-scale anchor adopters and forward-looking AI governance, positioning the region as a leading AI center in the heartland. The University of Minnesota (UMN) is a top-tier research university and was selected by the National Science Foundation (NSF) and the United States Department of Agriculture (USDA) to serve as the lead institution for developing the AI Institute for Land, Economy, Agriculture & Forestry (AI-LEAF), a nationally significant initiative focused on leveraging AI to create more climate-smart agricultural and land-use practices. This designation reflects not only UMN’s research depth but its ability to translate AI innovation into applied economic value.

UMN also hosts Data Science & AI (DSAI), which serves as a central coordinating hub for a university-wide network of multidisciplinary collaboration, research and information-sharing initiatives. Together, these efforts anchor Minneapolis’ research-driven AI ecosystem.The University of Saint Thomas (Saint Thomas) augments the AI pipeline through its Center for Applied AI (CAAI) and training on workforce applications of AI. Complementing these university assets, Hennepin Technical College offers a suite of AI degrees and certifications, including short cycle generative AI training programs, ensuring that AI skills are accessible beyond traditional four-year pathways.

Research capacity alone, however, does not create an AI cluster. Adoption by major employers is the critical next step—and Minneapolis excels on this dimension. Major company headquarters—including Target, Best Buy, Allina Health and Optum, Cargill, Solventum and 3M—are actively deploying AI across a wide range of use cases, from generative virtual store assistants and conversational health agents to computer vision in manufacturing and advanced predictive analytics. The breadth of these applications demonstrates that AI has moved beyond experimental application in Minneapolis but is actively operational.

The presence of these firms at the forefront of AI sends a powerful message to local startups, vendors and investors that AI investments represent concrete business expansion opportunities. This demand-side pull is a defining advantage in the AI cluster race, accelerating ecosystem maturity. Another competitive edge is Minnesota’s strong emphasis on governance as demonstrated through the Transparent AI Governance Alliance (TAIGA), which develops principles and standards for AI use in the public sector. In an era of increasing concern around AI trust, this governance infrastructure enhances the region’s long-term competitiveness.

AI firms in the Minneapolis region are also attracting outside capital, and UMN plays a central role in commercializing research and spinning out new ventures.[i] Notably, UMN ranks among the top heartland universities in technology commercialization, reinforcing Minneapolis’ innovation pipeline. As a result of these combined strengths, Minneapolis ranks seventh among heartland metros based on foundational metrics in AI talent, innovation and adoption.[ii]

Talent

Talent depth remains one of Minneapolis’ most durable competitive assets. As home to Medtronic’s’ U.S. operations and major facilities operated by Boston Scientific, the region possesses a deep concentration of engineering and technical expertise in medical devices. This specialization is reinforced by other advanced manufacturing operations, including 3M, which further strengthen the region’s technical workforce base.

In Minneapolis, 47% of the population 25 years of age or older holds a bachelor’s degree, exceeding the national average by 10 percentage points and ranking the metro area among the top five with a population exceeding three million. This educational attainment translates directly into AI-relevant labor supply.The Minneapolis metro area is home to approximately 260,000 residents with a bachelor’s degree in computer science, engineering and mathematics (CSEM), surpassing the corresponding figure in Austin. When considering the percentage of advanced degree holders, Minneapolis has approximately 1,200 PhDs in the CSEM field, providing critical capacity for advanced research, commercialization and AI-focused entrepreneurial ventures.

UMN’s DSAI Hub serves as the central organizing force for AI education and training across departments and campuses, organizing workshops, seminars, seed grants and graduate fellowships.[iii] This hub-and-spoke model allows AI expertise to diffuse across disciplines rather than remain siloed in computer science alone.UMN offers a wide range of graduate-level AI courses delivered in “CoFlex” mode, with evening scheduling as well as hybrid and online options for students to expand access and accommodate working professionals. While the number of formal, standalone AI degree programs remains limited, the university compensates with a deep bench of AI-focused elective courses embedded across disciplines.

At the undergraduate level, UMN offers a B.S. in Computer Science with a specialization in AI and robotics, integrating training across multiple AI domains, including machine learning. UMN’s Carson School of Management complements these offerings with a one-year, STEM-designated M.S. in Business Analytics that weaves machine learning and AI into the curriculum. AI-related coursework includes predictive analytics, responsible AI and generative AI for business applications, ensuring graduates can translate technical capability into organizational value.

UMN also supports short-cycle AI skill development through its Generative AI & Gemini Training Series, offered to students across all disciplines. These programs focus on practical competencies such as prompt design, safe use, tool awareness and integrating AI into research and administration work. Through the DSAI Hub, UMN further provides training for faculty and staff on integrating AI into teaching, evaluating bias and managing AI-related course policies, strengthening institutional readiness alongside student preparation.

Outside of UMN, other institutions of higher learning in Minneapolis are adapting to AI, as well. For example, the University of Saint Thomas’ AI certificate programs are deliberately structured to feed into its full M.S. in AI, providing opportunities for part-time students to earn a graduate degree. Most courses are offered in “CoFlex” mode, and the M.A. in Artificial Intelligence Leadership is fully available online. The M.S. in Artificial Intelligence is a STEM-approved program with extensive technical offerings. A distinguishing feature of Saint Thomas’ approach is its applied orientation: through the Center for Applied AI, students are required to apply their knowledge at local firms through formal and informal internships, providing an opportunity for hands-on application of skill.[iv]

Beyond the Minneapolis core, the University of Wisconsin, River Falls and the University of Wisconsin, Stout offer AI programs serving local employers. Hennepin Technical College provides associate degrees and certification in AI, reinforcing workforce accessibility and mid-career upskilling. Minnesota IT Services (MNIT) offers no-cost AI training for state employees, while MnTech and the Global Twin Cities Initiative host bootcamps and tech meetups. Collectively, these efforts create a layered and inclusive AI workforce pipeline.

Innovation

AI-LEAF is one of seven new NSF-funded AI Institutes announced as part of a broader federal initiative totaling nearly half a billion dollars to bolster collaborative AI research nationwide. For Minneapolis, AI-LEAF represents a signature innovation asset. Its objective is to advance foundational AI by integrating knowledge from agriculture and forestry sciences, leveraging new AI methods to mitigate climate impacts while lifting rural economies. In effect AI-LEAF establishes a new scientific discipline and innovation ecosystem at the intersection of AI, climate science and land-use systems.

Researchers and practitioners within AI-LEAF are deploying AI-enhanced methods to estimate greenhouse gas emissions and develop specialized field-to-market decision-support tools, linking research with deployable solutions.[v] The Minnesota Robotics Institute (MnRI), also based at UMN, is another critical component the region’s AI research ecosystem. MnRI conducts research into AI-augmented robotics, sensing and automation for deployment across advanced manufacturing and many other sectors, expanding AI’s reach into physical systems.

Saint Thomas’ Institute for AI for the Common Good adds a complementary dimension by framing AI applications through the lens of ethics, human dignity, justice, public good and social impact. Its steering committee includes faculty from multiple disciplines as well as industry leaders, ensuring that innovation is informed by societal considerations. Another foundational asset is the Minnesota Supercomputing Institute (MSI), which provides high-performance computing resources to campus researchers, supporting large-scale AI model training and simulation.[vi] UMN’s leadership in advanced computing dates back decades, beginning with its deployment of a Cray supercomputer in 1981.

The Minneapolis metro area has produced 32 AI research papers published at top AI conferences, reflecting steady scholarly output. Even greater strength appears in patenting activity, with 510 AI-related patents benefitting from close ties between research and industry. One example is Smart Information Flow Technologies (SIFT), a Minneapolis-based R&D and consulting firm specializing in AI, human-automation interaction and cybersecurity, which holds a number of these patents and exemplifies industry-linked innovation.

Adoption

Minneapolis is home to several headquarters for companies that are national leaders across retail, health care, agriculture and food, logistics and manufacturing, and these firms are deploying AI at scale across multiple functional areas. Many of these integration efforts are supported by local AI consultancies, software developers and digital transformation firms that embed AI, machine learning and advanced analytics into enterprise solutions.

Target recently introduced its “Store Companion”, a generative AI tool for employees that answers process questions, assists with operations and coaches new staff.[vii] Similarly, Best Buy launched its GenAI virtual assistant for customer support and upskilled 30,000 employees using AI-enabled PCs, demonstrating both operational and workforce-focused adoption.

In health care, Allina Health announced a strategic relationship with Optum and launched “Alli,” a conversational AI agent supporting authentication and patient self-service. Allina also partnered with Ferrum Health to deploy AI-driven “second opinions” for cancer screenings and imaging interpretations, helping detect nodules that may be missed in initial readings.[viii] Solventum ranks among the national leaders in deploying AI-driven clinical documentation, while Cargill applies AI to supply-chain optimization and processing automation. Within logistics, C.H. Robinson has incorporated AI agents to automate freight and shipping tasks, underscoring AI’s cross-sector penetration.

Another positive development for Minneapolis is the recent announcement that tech leaders like Meta, Microsoft and others will build data centers totaling more than $2 billion in investment. This infrastructure investment strengthens the region’s attractiveness to hyperscalers and AI-intensive firms seeking proximity to compute resources. While Minneapolis scores below the top six heartland AI hubs on most measures of adoption, such as firm AI use, data readiness and cloud readiness, it performs comparatively well on metrics tied to workforce exposure. The region is closest to leading metros in share of jobs exposed to generative AI and exceeds Ann Arbor and Madison in job postings requiring AI skills.

The region’s startup ecosystem further reinforces adoption momentum. Flywheel, a medical imaging AI firm, raised a $54 million Series D venture capital round co-led by Novalis LifeSciences and NVentures with participation by Microsoft. Inspectorio, an AI-powered supply-chain quality and compliance firm, raised a $50 million Series B round led by Insight with participation by Techstars, and is frequently cited as one of Minnesota’s leading startups.[ix] Exosite applies AI in the platform sensor and Internet of Things field, while phData specializes in data engineering for AI pipelines and platforms. In total, Minneapolis hosts 83 startups developing AI-driven products and has recorded 113 venture capital deals, signaling sustained commercial activity.

Taken together, Minneapolis demonstrates how a heartland metro can compete effectively in the AI cluster race by aligning research excellence, applied innovation, workforce development and large-scale adoption.The region’s strength lies not in a single standout asset but in the integration of universities, anchor employers, governance and talent pipelines that translate AI capability into economic impact. As AI reshapes industries and labor markets, Minneapolis is well positioned to deepen its role as a durable, practice-oriented AI hub—one that reflects the heartland’s broader advantage in turning technology into real-world productivity and shared growth.

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[i] https://heartlandforward.org/case-study/research-to-renewal-advancing-university-tech-transfer/

[ii] Muro, M., and Methkupally, S. (2025). Mapping the AI Economy: Which Regions are Ready for the Next Technological Leap? Brookings Metro. https://www.brookings.edu/articles/mapping-the-ai-economy-which-regions-are-ready-for-the-next-technology-leap/

[iii] https://dsai-hub.umn.edu/

[iv]https://www.stthomas.edu/ai-for-common-good-institute/

[v] https://www.hpcwire.com/off-the-wire/nsf-announces-seven-new-national-artificial-intelligence-research-institutes/

[vi] https://msi.umn.edu/

[vii] https://corporate.target.com/press/release/2024/06/target-to-roll-out-transformative-genai-technology-to-its-store-team-members-chainwide

[viii]https://www.startribune.com/as-use-of-ai-grows-in-healthcare-allina-doctors-have-it-doublechecking-cancer-screenings/601321539

[ix] https://thetechtribune.com/10-best-tech-startups-in-minnesota/