How AI Is Helping Healthcare Companies in Knoxville Cut Costs and Improve Efficiency

AI matters for Knoxville healthcare because local research is already turning models into faster, more precise care - University of Tennessee teams are using AI to speed CT lung‑cancer screening, enable more precise surgeries, and train clinicians and students through the statewide AI Tennessee Initiative and industry partnership program AI TechX (which offers up to $60,000 in seed funding for applied projects) (University of Tennessee AI projects in Knoxville).

That practical focus - Tennessee's tilt toward process improvement over deep research - means hospitals can cut administrative load and shorten diagnostic timelines if staff are trained to use AI tools; targeted upskilling such as the AI Essentials for Work bootcamp syllabus (Nucamp) teaches prompts and workplace AI skills that clinical teams can apply immediately to reduce costs and free clinicians for patient care.

“Through research, workforce development, and industry partnerships, we empower students, professionals, and industries to drive innovation and shape a future of opportunity for Tennessee and the nation.”

UT Knoxville's commercial engine is powered in part by the University of Tennessee Research Foundation's Accelerate Fund, a UTRF‑managed pre‑seed/seed vehicle that launched in 2023 to move UT inventions into market‑ready companies; the fund (backed initially with $5 million through UT's Venture Launch Program) makes investments from roughly $20,000 to $150,000 and targets technologies across human health and mobility (UTRF Accelerate Fund overview).

That local capital is already translating to practical wins for Knoxville health care: the Accelerate Fund's $150,000 backing of VisualizAI helped mature ClaimsAgent into pilots that diagnose patterns of denials and underpayments - an urgent problem given CMS data showing about 19% of in‑network claims denied - so hospitals and clinics can pilot AI before committing larger budgets (UTRF investment in VisualizAI).

Startups must originate from UT tech, can submit rolling applications, and should expect an evaluation timeline that can take up to nine months, making the fund a deliberate but concrete pathway for Knoxville teams to de‑risk AI tools and attract follow‑on capital.

“VisualizAI is a great example of how UT‑driven research can lead to real‑world solutions that improve efficiency, accuracy and outcomes in critical industries like health care.” - Randy Boyd, University of Tennessee System President

Real-world AI adoption in Knoxville is already being framed around practical systems that clinics can plug into today: local brokers and carriers such as Marsh McLennan Agency Knoxville insurance services operate client portals (CSR24, Zywave) and payment/claims links that make them natural places to pilot document‑triage, intake automation, and denial‑prediction features, while claim support services like ClaimsMate public adjusters in Knoxville offer an immediate revenue‑recovery pathway - studies cited by ClaimsMate show property claimants can recover as much as 747% more than initial offers, a concrete dollar‑return that can fund modest AI pilots.

Complementing those operational partners, local training and playbooks such as Nucamp AI Essentials for Work syllabus provide practical guides on chatbots and telehealth that show how conversational AI and automated follow‑up templates can reduce wait times and lift administrative burden, making it easier for Knoxville health systems to test small, measurable automations before scaling them across billing, patient outreach, and supply workflows.

“Got a reasonable quote in a timely fashion from a friendly agent. That's an A.” - Carolyn Kincaid

University research in Knoxville is translating AI into measurable clinical improvements: UT teams are building tools to speed CT lung‑cancer screening, visualize and standardize cleft‑lip surgery landmarks, and accelerate breast‑cancer staging for faster diagnoses, while partnerships fostered by the statewide AI Tennessee Initiative research and partnerships and the new AI TechX program supply the industry links and seed support that let hospitals pilot these innovations without large upfront procurement costs - AI TechX even offers seed awards to catalyze university‑industry projects (University of Tennessee faculty AI projects in Knoxville).

The practical payoff is concrete: faster scans and cleaner surgical planning shorten diagnostic timelines and free clinicians from routine data‑wrangling so staff time shifts back to care.

“Through research, workforce development, and industry partnerships, we empower students, professionals, and industries to drive innovation and shape a future of opportunity for Tennessee and the nation.”

Knoxville health systems can capture measurable savings by automating routine workflows - AI tools that triage intake, draft notes, predict denials, and manage prior authorization sharply reduce staff hours and administrative bottlenecks, which clinicians cite as a leading cause of burnout; industry estimates place potential admin‑cost reductions between about 25% and 35% and practice‑level reports show operating costs falling up to 30% when automation is applied (Citi report on healthcare administrative costs and AI, MedicalEconomics analysis of AI and automation in healthcare economics).

Revenue‑cycle pilots are an immediate ROI play - automated revenue‑cycle management can lower cost‑to‑collect (3.74% → 3.51%) and, for a $5B system, translate to roughly $11.5M in annual savings from fewer denials and faster collections (Jorie.ai post on automating revenue cycle management).

The practical "so what" for Knoxville: start with revenue cycle and appointment/intake automations to free clinicians for billable care while seeding larger clinical pilots through local university funding pathways.

“Automation is the key differentiator when moving the needle on cost to collect and creating large scale cost savings.” - Amy Raymond, Vice President of Revenue Cycle Operations at AKASA

Regional case studies from Tennessee show how AI can cut costs and free clinician time: West Tennessee Healthcare is piloting Xsolis' Dragonfly Navigate at Jackson‑Madison County General Hospital to flag discharge barriers in real time and speed case‑management decisions, a workflow change that executives say helped the system save about $5.1 million and addresses a concrete cost driver - each unnecessary hospital day can be roughly $3,000 (Tennessee Lookout report on West Tennessee Healthcare Dragonfly Navigate pilot, Xsolis press release on expanded AI collaboration and Dragonfly Navigate).

Nearby systems are pairing operational AI with surgical and revenue‑cycle automation: Qventus' perioperative AI filled OR capacity and drove measurable service‑line growth (fourfold ROI, a 9% orthopedic increase and 61 added cases in 100 days), showing how targeted AI pilots can pay for themselves quickly (Qventus case summary on perioperative AI at West Tennessee Healthcare).

Security and integration wins (IBM QRadar via Mainline) illustrate another “so what”: tighter compliance and faster incident response let IT teams reallocate time back to clinical projects, further protecting those operational savings.

“Our models are not meant to replace the clinical determination or the clinical expertise of the people that are using our solutions.” - Joan Butters, CEO & Founder, Xsolis

Knoxville's private‑sector AI backbone centers on behavior‑focused platforms that plug into existing clinical and payer workflows - most notably Lirio, a local company whose Precision Nudging® and Intelligence Layer use behavioral science plus machine learning to personalize outreach, close gaps in care, and reduce total cost of care by automating the “right message, right time” touchpoints that lower no‑shows and late diagnoses; see Lirio Precision Nudging health systems overview for how these interventions drive sustained engagement and value‑based outcomes (Lirio Precision Nudging - Health Systems Overview).

Lirio's Knoxville office (320 Corporate Drive) has layered partnerships with population‑health vendors and platforms - examples include a value‑based care integration with Ayin Health Solutions and an ecosystem tie‑in with BrightInsight that brings nudging into patient companion apps - so hospitals can test small pilots that scale into measurable savings without reengineering core systems (Lirio and Ayin Health Solutions value-based care partnership announcement).

The practical payoff: automated, individualized outreach that moves patients to preventive care (mammograms, screenings) earlier and keeps revenue and quality metrics aligned with value‑based contracts.

“Aligning objectives, incentives and transparent use of data enables health plans to invest more resources in addressing root causes of poor health.” - Marten den Haring, Lirio CEO

Knoxville healthcare leaders must treat privacy, security, workforce readiness, and technology adoption as a single risk vector: ransomware and hacking are driving a national surge - Bradley LLP reports a 256% rise in significant hacking‑related breaches and a 264% jump in ransomware incidents to HHS OCR - so a single vendor breach can cascade into legal, financial, and care disruptions (Bradley LLP report on rise in healthcare data breaches and HHS OCR guidance).

A local example underscores the stakes: a Knoxville EHR vendor incident exposed roughly 319,778 patient records and spawned class‑action litigation that highlights delayed notification and weak controls as costly failures (QRS Knoxville data breach lawsuit overview - 319,778 records exposed).

Tennessee law adds urgency - affected residents must be notified within 45 days - so hospitals and startups piloting AI must embed vendor BAAs, multi‑factor authentication, encryption, robust audit controls, and targeted, role‑based security training before scaling models; otherwise the trust and cost savings AI promises can be erased by breach response, fines, and lost patient confidence (Tennessee data breach notification law - 45-day requirement and guidance).

Start with concrete, measurable objectives tied to an executive sponsor - pick 1–3 high‑impact pilots such as revenue‑cycle automation or intake/appointment triage so results are visible (faster collections and fewer denials are easy to quantify).

Strengthen data plumbing and governance up front: assemble EHR, imaging and scheduling feeds, lock in BAAs, multi‑factor authentication, encryption and role‑based access to meet Tennessee rules (affected residents must be notified within 45 days after a breach).

Run small, cross‑functional pilots with clinician champions, iterate for usability, and measure clinician time saved, denial rates, and patient‑experience metrics before scaling; this phased, evidence‑first approach mirrors Philips' five‑step rollout and reduces switchover risk.

Invest in staff upskilling and local partnerships - use UT resources and OIT adoption guidance to set pace and classroom‑friendly policies, and seek university seed programs to de‑risk pilots - so the first two successful automations pay for broader clinical projects and preserve trust while cutting costs (UT OIT guidance on AI adoption for teaching and learning, Philips guide: How to implement and drive adoption of AI in 5 steps).

Measure ROI in Knoxville by treating AI projects as phased operational investments: set baselines, pick 1–3 clear KPIs tied to finance and capacity (reduction in denials/time‑to‑collect, claims‑review time, OR utilization), and require an executive sponsor and cross‑functional governance to decide scale or stop.

Start with revenue‑cycle and perioperative pilots because they show rapid, auditable returns - Qventus' perioperative work with West Tennessee Healthcare produced a fourfold ROI and added 61 cases in 100 days (roughly 90% of the vendor investment recovered), while pre‑bill tools at AdventHealth cut claims review time by about 63% - concrete wins that fund broader clinical pilots and justify staff training.

Use a repeatable ROI playbook (baseline → short pilot → measured outcomes → scale), embed security/compliance in total cost calculations, and invest in targeted upskilling so clinician champions can capture value immediately (see a practical prioritization and scaling approach in Vizient's “From hype to value” guidance).

For quick team readiness, pair pilots with role‑based training like the Nucamp AI Essentials for Work syllabus to convert early savings into sustained operational capacity and measurable ROI. Healthcare IT News analysis of revenue-cycle AI tools and measurable ROI, Vizient guidance: From Hype to Value - aligning healthcare AI initiatives and ROI, Nucamp AI Essentials for Work syllabus (AI for Work, 15-week bootcamp).

“Being able to view available room time in seconds while scheduling in minutes is everything for my staff and patients.” - Dr. Keith Nord, chairman of orthopedic surgery, West Tennessee