Skip to content
MarketScale
‹ Back to IndustriesHealthcare

Automation adoption gap widens in US manufacturing as medtech presses ahead

Automation in US manufacturing lags, with 80% of factories lacking automation tools. In contrast, medtech manufacturers are advancing with technologies like micro-molding and ultrasonic welding. This disparity highlights a growing gap in technology adoption across different sectors.

This story was produced through MarketScale. See how Healthcare teams put it to work with Executive Thought Leadership.

By MarketScale Newsroom · AutomationManufacturingMedical DevicesMedtech
Share
Learn this in 60 seconds

Key facts, context, and what it means, in one minute.

:60
0:001:00
Automation adoption gap widens in US manufacturing as medtech presses ahead

Key takeaways

01

80% of US factories have no automation.

02

Medtech manufacturers are investing in automation technologies.

03

There's an increasing divide in technology adoption across industries.

Eighty percent of U.S. manufacturing facilities currently have zero automation. That figure, cited by Intrinsic Chief Technology Officer Brian Gerkey and reported by Manufacturing Dive in May 2026, puts a number on a gap that procurement and operations leaders across every industrial vertical have started to feel in hiring costs, throughput variability, and supply chain fragility.

The gap is not from lack of conviction. Jeff Burnstein, president of the Association for Advancing Automation, told Manufacturing Dive that interest in AI and automation is high across the board, but execution is where things get difficult. Research from his organization shows a strong majority of manufacturers believe AI will be critical to their future, while only a small percentage say it is widely deployed today.

Deloitte's 2025 Smart Manufacturing and Operations Survey reinforces the point. According to that research, 92% of manufacturers surveyed believe smart manufacturing will be the main driver of competitiveness over the next three years. The gap between that conviction and actual deployment is the central operational challenge facing manufacturing leadership right now.

Medtech is not waiting

While the broader manufacturing base stalls, the medical device sector is making concrete moves. MDDI Online's 2026 automation coverage tracks a distinct cluster of investments, each targeting a specific precision or compliance problem rather than automation for its own sake.

Cordica Medical's acquisition of RapidWerks, reported by David Hutton in MDDI Online, brings in-house micro-molding capabilities that are typically outsourced. Micro-molding for medical components demands tolerances measured in microns and full traceability, requirements that make manual or legacy processes difficult to defend to quality auditors. Bringing that capability under one roof compresses the supply chain and tightens process control.

Separately, MDDI Online's coverage of ultrasonic welding highlights how hospital care product manufacturers are replacing adhesive and mechanical joining methods with automated ultrasonic processes. The case for the switch is largely operational: ultrasonic welding produces hermetic, repeatable bonds without consumables, and the join cycle is fast enough to integrate into high-volume assembly lines.

Ranpak's collaboration with Medline, also covered by MDDI Online, illustrates a different angle. Rather than building automation into a product, the two companies are applying it to packaging and fulfillment for medical supply distribution. For Medline's procurement and distribution teams, the collaboration represents a push to reduce manual labor in a fulfillment operation that handles thousands of SKUs under tight delivery and sterility requirements.

Precision measurement closes the loop

Automation without inline measurement still leaves quality to end-of-line inspection, which finds defects after cost has already been incurred. LaserLinc's precision measurement advances, highlighted in MDDI Online's sponsored coverage, address setup time and in-process accuracy for medical tubing and similar extruded or formed components. Faster setup directly reduces changeover cost on short production runs, which is the norm in medical device manufacturing.

This cluster of activity points to a model that differs from the AI-heavy automation narrative dominating investor conversations. In medtech, automation investment tends to be narrow, traceable, and tied to a specific compliance or quality outcome. That approach is easier to validate with regulators and easier to justify in a capital approval process than a broad AI platform deployment.

Why the broad market lags

Manufacturing Dive's reporting identifies several structural reasons why most U.S. manufacturers remain at zero automation. Capital cost is the most cited barrier, particularly for small and mid-size facilities that lack the volume to amortize equipment quickly. Integration complexity is a close second: older factories were not designed for automated systems, and retrofitting them requires engineering resources many companies do not have on staff.

The contrast with medtech is partly a function of margin and regulatory pressure. Device manufacturers face FDA documentation requirements and quality system mandates that make automated, traceable processes a near-necessity at scale. That same pressure becomes a forcing function for investment that general manufacturers rarely face.

The Deloitte survey number is worth keeping in sight for operations leaders evaluating their own timelines: 92% of peers believe smart manufacturing is a competitive prerequisite within three years, yet the installed base of automation remains thin. The companies that close that distance first, through targeted acquisitions, supplier collaborations, or incremental inline technology, will set the process benchmarks others will be measured against.

Featured companies

About the author

MarketScale Newsroom
MarketScale NewsroomEditorial Team, MarketScale

The MarketScale Newsroom reports on the companies, technologies, and trends shaping 16 B2B industries. It turns primary sources and expert commentary into clear, useful coverage for the people doing the work.

Healthcare: are you visible to AI?

Before they reach out, Healthcare buyers ask AI engines which vendors to trust. See how AI describes your company today, and where competitors show up instead.

Free workspace

You just read one expert. Imagine publishing your whole team.

This article was produced through MarketScale. Create a free workspace and turn your own team's expertise into articles, video, and social posts. No credit card, no demo required.

NPS +73 · 1,000+ creators · 38+ countries

What you get, free

Your own MarketScale Studio workspace
One video edit a month, on us
AI writing, editing, and publishing tools
In-platform coaching to learn the system

More Healthcare Insights

Clinical AI, specialty pharmacy, and consolidation: what's reshaping healthcare operations right now

Clinical AI, specialty pharmacy, and consolidation: what's reshaping healthcare operations right now

The healthcare industry is being reshaped by advancements in AI, the direct involvement of companies like OpenAI with hospitals, and the increasing trend of mergers and acquisitions in specialty pharmacy. Nurses are actively participating in the design of AI tools, emphasizing the collaborative nature of these technological advancements. These changes are expected to have significant implications for health system operations.

  • 01Nurses are co-designing AI tools for healthcare.
  • 02OpenAI is engaging directly with hospitals.
  • 03Specialty pharmacy mergers and acquisitions are on the rise.

Jul 12, 2026

Healthcare's digital skills gap has a measurement problem, and new research is pushing for a fix

Healthcare's digital skills gap has a measurement problem, and new research is pushing for a fix

A recent examination of the healthcare industry's digital skills gap reveals that the majority of digital health competency tools currently available are heavily centered on nursing, indicating a lack of comprehensive tools validated for a broader interprofessional healthcare workforce. This discrepancy highlights the need for a more inclusive approach to developing digital skills competencies across various healthcare roles.

  • 01Current digital health competency tools focus mainly on nursing.
  • 02There's a recognized need for validated interprofessional tools in healthcare.
  • 03New research aims to address the digital skills gap in healthcare.

Jul 12, 2026

Healthcare AI deployments stall on data quality, not model performance

Healthcare AI deployments stall on data quality, not model performance

Healthcare AI deployments are facing challenges not with the AI models themselves, but with the data quality. Hospital CIOs report difficulties in scaling AI due to fragmented and poorly governed data. This highlights the need for better data management and governance in healthcare AI initiatives.

  • 01Data quality is a major obstacle in scaling healthcare AI deployments.
  • 02Hospital CIOs are encountering issues with fragmented data governance.
  • 03AI model performance is not the primary challenge in these initiatives.

Jul 11, 2026

Explore More Healthcare Insights

Read more expert perspectives from across Healthcare.

Browse Healthcare Hub

About the Expert

MarketScale Newsroom
MarketScale Newsroom

Editorial Team

MarketScale

The MarketScale Newsroom reports on the companies, technologies, and trends shaping 16 B2B industries. It turns primary sources and expert commentary into clear, useful coverage for the people doing the work.