The Complete Guide to Using AI in the Healthcare Industry in Sioux Falls in 2025

AI is already reshaping care in Sioux Falls by easing clinician workload, speeding data-driven decisions and extending services into rural corners of South Dakota: Sanford Health - headquartered in Sioux Falls and the largest rural health system in the U.S. with 53,000 employees and dozens of hospitals and clinics - is sharing real-world AI lessons on boosting clinician satisfaction and the patient experience (Sanford Health AI initiatives in Sioux Falls), while the state Department of Health is using AI for tasks from summarizing long reports to epidemiology analysis to better plan care for remote communities (South Dakota Department of Health AI pilot for healthcare planning).

For leaders and staff who need practical skills, upskilling options like Nucamp AI Essentials for Work bootcamp (15-week) teach prompt-writing and tool workflows that make AI useful on day one - so systems can focus more on keeping people healthy, not just fixing them.

“By using AI-enabled technology, we're boosting clinician satisfaction and enhancing the patient experience. I look forward to sharing lessons from our journey - especially the importance of building trust with both patients and care teams. At the end of the day, health care must lead the way in how technology is designed and deployed.”

Artificial intelligence in medicine began as an ambitious idea in the mid‑1950s and has evolved from rule‑based expert systems in the 1980s to today's machine learning and natural language processing tools that can sift through EHRs, flag sepsis risk, and spot subtle signs on imaging - sometimes surfacing patterns that would be like finding a needle (or an early tumor) in a stack of scans the size of a small library.

The American Hospital Association lays out how AI is an umbrella of capabilities - voice recognition, pattern detection and process automation - made possible by modern compute, sensors and unprecedented volumes of data (Understanding Artificial Intelligence in Health Care - American Hospital Association), while practical overviews show AI reshaping diagnostics, personalized treatment, administrative automation and predictive population health (with the market projected from roughly $11B in 2021 toward much larger numbers by 2030) (AI in Healthcare: Applications and Growth - ForeSeeMed).

Big‑name efforts - remember IBM's Watson for health in 2011 - helped start clinical experiments, but the path to routine use depends on careful integration with workflows, data quality, clinician trust, regulatory clarity and privacy safeguards; those considerations will determine how quickly Sioux Falls health systems move from pilots to dependable, everyday tools.

“AI is a subfield of computer science that focuses on building systems capable of performing tasks traditionally done by humans, such as understanding language or making decisions,” says Curtis Helsel, Forcura's Data Science Engineer.

AI adoption in healthcare is moving from pilot projects to enterprise‑scale initiatives in 2025, and Sioux Falls is riding that momentum: industry reporting notes as many as 90% of hospitals or systems are exploring AI tools to cut costs and relieve staffing pressure (HFMA report on AI adoption in healthcare), while local coverage highlights a regional AI growth rate of about 37.3% from 2023–2030 as businesses and institutions in the Sioux Falls area experiment with practical use cases like scheduling, personalization and workflow automation (Greater Sioux Falls Chamber AI at Work report).

Market research adds scale: the global AI market jumped to roughly $184 billion in 2024 with projections toward the high hundreds of billions by 2030, and healthcare‑specific AI growth rates well into the 30%+ range - signals that remote monitoring, ambient documentation and revenue‑cycle automation will become common tools rather than curiosities (Mezzi AI adoption and market forecasts).

The practical takeaway for Sioux Falls clinics: expect rapid opportunity but plan deliberately - prioritize data governance, measurable ROI and upskilling so automation augments staff instead of creating brittle new processes; when adoption scales this fast, the payoff can feel like gaining a fractional clinician every month if workflows and training keep pace.

“AI, like most transformative technologies, grows gradually, then arrives suddenly.”

Sioux Falls is well positioned to turn 2025's AI promise into practical wins: local health systems like Sanford Health are already scaling virtual care across 78 specialties and piloting AI that can reshape workflows, diagnostics and patient experience (Sanford Health AI initiatives in virtual care), the South Dakota Department of Health is using AI today for things as concrete as summarizing long reports and strengthening epidemiology analysis to plan rural services (South Dakota Department of Health AI pilots for epidemiology and reporting), and statewide talent and research networks - from USD's Artificial Intelligence Symposium to regional conventions - are feeding a pipeline of practical skills and partnerships that clinics can tap for projects like ambient documentation, telehealth expansion and predictive population health (USD 2025 Artificial Intelligence Symposium details and speakers).

The real opportunity for Sioux Falls is pragmatic: pick a measurable use case, protect privacy and data quality, train staff, and then scale - turning tools into steady improvements for rural access, clinician time and patient outcomes instead of one-off experiments; after all, when a system serving millions starts applying AI thoughtfully, the payoff can be felt in shorter waits, clearer care plans and more time at the bedside.

“By using AI-enabled technology, we're boosting clinician satisfaction and enhancing the patient experience. I look forward to sharing lessons from our journey - especially the importance of building trust with both patients and care teams. At the end of the day, health care must lead the way in how technology is designed and deployed.”

Building local AI talent starts with nearby universities that teach practical skills and real projects: Dakota State University (DSU) runs a campus‑and‑online pipeline from a 120‑credit BS in Artificial Intelligence and AI/ML undergraduate tracks to master's programs (MSAI and MSAA) that emphasize hands‑on labs, cybersecurity excellence and applied analytics - students train in DSU's AI Lab and can work on real organizational datasets that regional employers recruit for (DSU Artificial Intelligence BS program at Dakota State University; Dakota State University MSAI graduate program).

The University of South Dakota complements that supply with a graduate AI program focused on machine learning, vision, intelligent systems and the ethical, trustworthy use of AI - small classes, assistantships and research opportunities help produce graduates ready to lead AI projects in health settings (University of South Dakota Graduate Artificial Intelligence program).

For Sioux Falls health systems, that means a steady stream of candidates versed in health analytics, NLP and secure AI practices who can move pilots toward steady operations - imagine a local student turning a messy EHR dataset into a deployable model that shortens charting time, not just a theoretical paper.

“DSU is already a leader in cybersecurity education and research, so AI will certainly be a part of the growing curriculum regarding security and other fields. It's going to make DSU even more appealing for future Trojans,” Kooima said.

Regulatory, ethical and privacy considerations are the backbone of any AI rollout in Sioux Falls: federal HIPAA standards - summarized by South Dakota's DSS - require safeguards, limits on uses and disclosures, patient access to records, and a clear Notice of Privacy Practices that health systems must follow (South Dakota DSS HIPAA overview and resources); local hospital practice illustrates that principle in everyday care (for example, Sanford's regional policies around directory information and release choices on the day of surgery) (Sanford Health HIPAA patient privacy guidance).

From a technical standpoint, privacy‑preserving approaches - such as federated learning with NVIDIA Clara for cross‑hospital research in Minnehaha County - offer a way to improve models without wholesale sharing of patient charts, and ambient‑documentation tools can cut clinician chart time but must be integrated under HIPAA safeguards and clear operational policies (Federated learning for cross-hospital research case study).

The practical takeaway: document the minimum‑necessary data flows, update Notices of Privacy Practices and consent processes, involve privacy officers early, and keep the option to call the state HIPAA contact if questions arise - because real privacy protection happens at the intersection of law, tech choices and everyday bedside decisions.

Putting AI to work in Sioux Falls starts with the practical plumbing: reliable EHRs and urgent‑care platforms that reduce clicks, speed billing and keep walk‑ins moving - for urgent care specifically, Experity is widely used as a purpose‑built urgent care EHR and practice management system that promises streamlined operations, patient engagement and revenue‑cycle tools (Experity urgent care EHR and practice management software).

Local clinics - Sioux Falls Urgent Care (open seven days with on‑site x‑rays and lab testing) and QuickHealth Urgent Care East - depend on those workflows to turn a same‑day visit into a complete encounter without a tangle of paperwork, while telemedicine and staffing vendors such as Avel eCare provide remotely staffed APP teams that plug directly into EHR workflows for virtual coverage and continuity of care (Avel eCare telemedicine and clinical staffing platform).

At the health‑system level, Sanford's push to trim EHR clicks shows why vendor choice and thoughtful integration matter for clinician well‑being and safe AI augmentation (Sanford Health EHR efficiency initiative and clinician burnout report).

The practical takeaway for Sioux Falls leaders: pick urgent‑care and telehealth vendors that integrate cleanly with enterprise EHRs, test ambient documentation or RCM automation in a single clinic first, and protect privacy while measuring whether each tool actually frees clinicians to spend more time at the bedside.

Starting AI in a Sioux Falls clinic should follow a tight, practical checklist: adopt clear governance, begin with a narrowly scoped, measurable use case, protect privacy and train staff before scaling.

The American Medical Association's Governance for Augmented Intelligence toolkit is designed for exactly this - define terms like generative AI and machine learning, articulate risks, set permitted and prohibited uses, and require staff training and oversight (AMA Governance for Augmented Intelligence toolkit and eight-step framework).

Local practitioners should keep patient needs front and center - Sanford and Avera leaders caution that technology must reduce clicks and improve access, not add anxiety or extra screens (South Dakota biotech panel on patient-centered AI adoption).

Start in one clinic with a concrete goal (for example, a pilot that trims documentation burden), involve privacy officers early, update antidiscrimination and consent policies, and consider privacy‑preserving options such as federated learning for cross‑hospital models (Federated learning case study with NVIDIA Clara for privacy-preserving models).

Measure outcomes, invest in brief, role‑specific training, and treat the project as a quality‑improvement cycle - small, documented wins build trust and make the next phase possible.

“I am excited to join this panel at the AHA Leadership Summit to share how Sanford Health is innovating with purpose. By using AI-enabled technology, we're boosting clinician satisfaction and enhancing the patient experience. I look forward to sharing lessons from our journey - especially the importance of building trust with both patients and care teams. At the end of the day, health care must lead the way in how technology is designed and deployed.”

For anyone in Sioux Falls ready to move from curiosity to action, the University of South Dakota's week of AI events is the place to be - starting with the NSF‑backed workshops (June 23–25) and building to the 7th annual Artificial Intelligence Symposium on June 26–27, 2025, which pairs technical keynotes and hands‑on workshops with a biomedical computing day aimed squarely at health care and biotech partners; full details and registration are on the USD Artificial Intelligence Symposium details and registration (USD Artificial Intelligence Symposium details and registration).

The series - free to attend with registration through the IEEE event portal - is designed for cross‑sector networking (expect a lunch buffet + networking lounge and an evening reception with light hors d'oeuvres) and features workshops, panels on workforce development and a biomedical computation panel that includes Avera and other regional stakeholders; a useful local summary and registration links are collected in the USD AI week in Sioux Falls news and registration (USD AI week in Sioux Falls news and registration), and IEEE's event page confirms virtual access and a certificate of participation for registrants (IEEE registration for USD SDBCC AI Symposium with virtual access: IEEE registration for USD SDBCC AI Symposium with virtual access).

These gatherings are a practical way for clinicians, IT leaders and hospital administrators to meet researchers, scout pilot projects and return with concrete contacts and a certificate to show for it.

For Sioux Falls healthcare leaders ready to turn promise into progress: start local, start measurable - register a team to attend the USD Artificial Intelligence Symposium (June 26–27, 2025) to meet biomedical computation partners and scout deployable projects, pick one narrow pilot (ambient documentation, scheduling optimization or a small predictive model) with clear ROI and privacy guardrails, and invest in practical upskilling like the 15‑week Nucamp AI Essentials for Work (15-week bootcamp to learn AI tools and prompt engineering) so clinicians and admins can write reliable prompts and run tools safely; combine those steps with governance work and state conference engagement (SDAHO's fall convention) and the result can feel like gaining a fractional clinician every month when workflows and training keep pace.

Treat the first wins as quality‑improvement cycles, document outcomes, and use regional events and university partners to recruit talent and move pilots from demo to daily use.

“USD is uniquely positioned to lead South Dakota – and the broader region – into an AI-powered future,” President Sheila K. Gestring said.