News / Updates

Why Healthcare—and Sterile Processing Tech (SPT)—Is Largely “AI-Proof”

AI is racing ahead, but not all jobs are equally automatable. Healthcare—especially hands-on, safety-critical roles like Sterile Processing Technician (SPT)—sits on the resilient end of the spectrum. Here’s what the latest data and research say, plus a sober look at how AI will (and won’t) reshape the work.

The big picture: healthcare jobs are growing, not shrinking

The U.S. Bureau of Labor Statistics’ newest 2024–2034 projections show overall job growth led by healthcare and social assistance, making it the single largest driver of employment gains over the next decade. (Bureau of Labor Statistics)

Zooming in on SPTs (classified as Medical Equipment Preparers, SOC 31-9093), BLS projects employment to rise from ~76,500 to ~84,200—about 10% growth—through 2034. That’s solid expansion in a field that requires careful human judgment and tactile skill. (Bureau of Labor Statistics)

Globally, workforce demand is even clearer: the World Health Organization estimates an 11.1 million health-worker shortfall by 2030 (after updating earlier projections), reinforcing that the constraint is people, not tech. (WHO Apps)

Why SPT work resists full automation

1) Safety-critical, high-accountability tasks. Sterile processing failures are consistently flagged in patient-safety research. ECRI’s “Top 10 Health Technology Hazards” lists inadequate/onerous cleaning instructions and insufficient AI governance as real risks—underscoring how much validated human oversight still matters. (ECRI)

2) Messy, variable real-world inputs. Instruments arrive in different states of soil, with sharp/fragile parts, mixed trays, and exceptions that demand situational judgment (e.g., spotting a torn wrap or hidden bioburden). Even AI advocates in SPD frame technology as assistive—for summarizing IFUs, flagging anomalies, and streamlining documentation—not as a replacement for the human technician. (Case Medical)

3) Physical dexterity and chain-of-custody. Many SPD steps (decontam, inspection, assembly, packaging, load setup, biological/chemical indicator checks, release) blend fine motor skills with strict compliance. Partial automation is emerging (e.g., automated washers, sorting aids), but experts describe it as easing the most laborious steps while elevating the technician’s role to orchestrate, verify, and respond to edge cases. (HPN Online)

What AI will actually change

Productivity and quality, not pink slips. McKinsey estimates generative AI could lift U.S. productivity by 0.5–0.9 percentage points annually through 2030; in healthcare specifically, adoption is shifting from pilots to broader operational use (routing tasks, documentation support, process intelligence). That’s augmentation—doing more with the same people—rather than mass replacement. (McKinsey & Company)

Early labor evidence is nuanced. Recent research tracking AI exposure across the economy finds no clear, widespread job losses due to AI so far; firms tend to retrain rather than lay off. Healthcare demand and demographics remain the dominant forces. (Barron’s)

Quality and governance still need humans. Even where AI helps (e.g., reading IFUs, recommending steps), patient-safety organizations warn that poorly governed AI can introduce new hazards—again pointing to the need for trained professionals to supervise and validate. (ECRI)

Will healthcare become AI-dependent—and need fewer people?

Short answer: more AI-supported, but still human-led. Two realities pull in opposite directions:

  • Demand tide: Aging populations, chronic disease, infection-control vigilance, and backlogs keep pushing healthcare labor needs up, with notable nursing shortfalls and persistent staffing gaps. (WHO Apps)

  • Tech tide: AI/automation will remove friction and standardize parts of workflows, raising throughput and consistency—but in safety-critical settings it typically reassigns time to higher-value tasks (inspection, exception handling, quality sign-off) rather than eliminating roles. (McKinsey & Company)

In practice, expect skill shifts: more emphasis on digital fluency (e.g., using AI-enabled instrument tracking, reading analytics dashboards), IFU mastery, root-cause thinking, and regulatory quality management—paired with the same physical craft SPTs are trusted for.

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Robotic & AI-assisted surgery is rising – and it increases sterile-processing demand

Hospitals are onboarding newer robotic platforms (da Vinci/Versius/Mako, microsurgical systems like Symani, and emerging entrants such as SS Innovations’ SSi Mantra), while health systems publicly signal a step-change in adoption. In England, the NHS plans to scale from ~70,000 robot-assisted procedures a year to ~500,000 by 2035, moving robotic tech toward default for keyhole operations—an indicator of the broader global trend. (The Guardian)

Industry and market analyses echo the same direction: the global surgical robotics market is projected to grow robustly through 2030–33, propelled by AI advances and hospital adoption. (iData Research)

More robots ≠ fewer humans in SPD—here’s why

Every robotic system still uses reusable patient-contact instruments that must be cleaned and sterilized between cases according to manufacturer IFUs and AAMI standards (e.g., ST79). That includes complex, multi-part robotic end effectors, camera heads, and accessories—often harder to process than traditional tools because of lumens, joints, insulated surfaces, and sensitive components. (The ANSI Blog)

  • IFUs are explicit: Example—Stryker’s Mako: “Any Mako instrumentation that has patient contact … requires cleaning and sterilization,” with detailed disassembly and pre-clean steps before terminal processing. (Stryker)

  • Practice guidance: Steris’s robotic-instrument reprocessing guide stresses that effective cleaning is prerequisiteto sterilization and notes the challenging soils (cauterized tissue, smoke plume, biofluids, bone dust) typical in robotic cases. (STERIS)

What about “Gemini-powered” robotic arms?

AI control stacks like Gemini Robotics (a vision-language-action model for bi-arm robots) show how robots will gain finer dexterity and autonomy in the physical world. In surgery, similar AI capabilities are being explored and piloted across platforms. But whether the arm is human-guided or AI-assisted, any component that enters the sterile field must still be reprocessed to standard—the sterility burden does not go away. (Google DeepMind)

Net effect on jobs: more SPT/SPTA work, new skills

As robotic case-volume grows, SPD throughput rises (more trays per day, more complex inspections), and facilities lean on Sterile Processing Technicians and Assistants (SPT/SPTA) to execute validated cleaning, assembly, packaging, BI/CI monitoring, and release. Automation will assist (tracking, documentation, washer/disinfector cycles), but humans still handle exception-finding, IFU interpretation, and quality sign-off. In other words: augmentation, not replacement.(STERIS)

Bottom line: Robotic and AI-assisted surgery expands the pie; it doesn’t erase the sterile-processing workload. If anything, it elevates the importance—and employability—of SPTs and SPTAs who can master robotic IFUs, AAMI ST79 workflows, and quality controls in a higher-throughput OR ecosystem. (The ANSI Blog)

What this means if you’re considering SPT

  • Strong job outlook with projected U.S. growth around 10% this decade. (Bureau of Labor Statistics)

  • Rising importance, not obsolescence: hospitals invest in automation to help SPTs manage volume and complexity, not to replace them. (HPN Online)

  • Transferable credibility: the role sits at the intersection of infection prevention, patient safety, and regulated quality—areas where human accountability is non-negotiable, and where AI must be governed carefully. (ECRI)

Bottom line

Healthcare will become more AI-enabled, but the sector’s growth and safety mandates mean it won’t become human-less—especially not in sterile processing. The evidence points to augmentation over automation: AI and robotics shoulder repetitive or data-heavy steps while trained technicians safeguard quality, handle exceptions, and make the judgment calls machines shouldn’t make.

For anyone weighing careers with staying power, SPT is a pragmatic, AI-resilient path aligned with a decade of projected demand and a long horizon of human-centered safety needs. (Bureau of Labor Statistics)

Ready to Take the Next Step?

See how Milay Institute prepares students for an AI-proof, recession-resilient healthcare career.
Join our Virtual Open House Info Session — October 23, 2025 @ 6:00 PM (Pacific).

🔹 Reserve Your Seat →
🔹 Or call 855-647-8338 to register by phone.

Sources & further reading

  • U.S. Bureau of Labor Statistics, Employment projections (2024–34) and Medical Equipment Preparers (31-9093). (Bureau of Labor Statistics)

  • World Health Organization, Global health workforce shortage updates. (WHO Apps)

  • ECRI, Top 10 Health Technology Hazards & Top Patient Safety Concerns (AI governance; cleaning risks). (ECRI)

  • McKinsey Global Institute, Generative AI and the future of work in America (2023); Generative AI in healthcare (2025). (McKinsey & Company)

  • HPN Online, Automation in the Sterile Processing Department (2025). (HPN Online)

  • Barron’s summary of recent Yale/Brookings research on AI and jobs (labor effects to date are limited). (Barron’s)