No one can dispute that AI in healthcare has consumed most all the air in the room this year. The debate is over on will it or won’t it, should we or shouldn’t we, help or hinder? The discussion now is how and where do we use it. Practical application in clinical settings could enhance diagnostic accuracy, personalize treatment plans, optimize workflows, provide real-time insights based on patient data, assist with decision-making, and enable proactive patient monitoring, all while improving patient care and delivering it more efficiently. The train has left the station, is it full steam ahead?
We asked our experts what more they think we will see in 2025 and it looks like it will be consuming a lot of the air next year too! Here is what they had to say. And check out all our prediction posts looking to 2025.
Michael Armstrong, CTO, Authenticx
LinkedIn: Michael Armstrong
The future of healthcare AI is going to be a balance of specificity and repeatability.
Off-the-shelf AI models fine-tuned for specific industries is the future of healthcare AI. With how rapidly AI is evolving, healthcare organizations should focus on finding the right industry-specific AI models to improve processes rather than creating the technology from scratch.
Ashley Barrow, Founder and CEO, RE-Assist
LinkedIn: Ashley Barrow
In 2025, Artificial Intelligence and the T.E.A.M. (Transforming Episode-Based Accountable Management) model will redefine care coordination, creating a smarter, faster, and more equitable healthcare system.
Primary care will evolve to include more longitudinal services, emphasizing sustained patient engagement and proactive management of chronic conditions. AI-powered tools will play a key role, identifying high-risk patients, closing care gaps, addressing Social Determinants of Health (SDOH) barriers, and streamlining resource allocation across providers to optimize care delivery.
Nontraditional providers, such as community health workers and paramedics, will take on expanded roles, equipped with AI-driven workflows. This will broaden access to care and create a more inclusive network.
Betsy Castillo, RN, Director of Clinical Data Abstraction, Carta Healthcare
LinkedIn: Betsy Castillo
In 2025, AI will play a transformative role in streamlining administrative tasks within clinical settings, significantly improving patient care and outcomes. AI-powered tools will automate routine administrative processes such as scheduling, billing, documentation and data abstraction, allowing healthcare professionals to focus more on patient care. Advanced AI algorithms will enhance data accuracy and reduce errors in patient records, leading to better-informed clinical decisions. Additionally, AI will facilitate real-time data analysis, providing clinicians with instant access to patient histories, lab results, and treatment plans. This will enable more personalized and timely interventions, ultimately enhancing patient satisfaction and health outcomes.
Steven Chen, MD, MBA, Chief Medical Officer, ImpediMed
LinkedIn: Steven Chen, MD, MBA
2025 will be the year when data-driven strategies take center stage in cancer survivorship care. Healthcare organizations and physicians will increasingly adopt technologies that enable early detection of treatment-related complications to try to prevent long-term consequences. We’ll see broader implementation of protocols to detect and measure subtle changes before clinical symptoms are apparent and the development of data-driven tools and algorithms that are more patient-focused.
Joe DeVivo, President and CEO, Butterfly Network
LinkedIn: Joe DeVivo
AI as an Amplifier
In 2025 we will see AI emerge as a transformative force in healthcare, acting as an amplifier of human capabilities, rather than a replacement. The past year has been pivotal in educating the industry to the potential of AI, and we’re now poised to see real-world applications that will significantly impact patient care. AI tools will enhance clinicians’ ability to process vast amounts of data, identify trends and present anomalies, ultimately making them more productive and effective in their diagnoses. This shift will not only simplify complex tasks but also democratize access to advanced medical technologies like ultrasound imaging, enabling more healthcare professionals to use these tools with confidence. As we move forward, the integration of AI into everyday practice will drive innovation and improve patient outcomes across the board.
Rom Eizenberg, CRO, Kontakt.io
LinkedIn: Rom Eizenberg
As the RTLS industry reaches a quarter-century of maturity in healthcare, it will move beyond its traditional focal points of locating assets such as medical equipment and managing staff safety. The last domain, and major growth driver of AI-powered RTLS in healthcare, will be monitoring and optimizing the patient journey to improve wait times, identify and overcome bottlenecks, and reduce patient stays.
Bob Farrell, CEO, mPulse
LinkedIn: Robert Farrell
LLMs in Market: Large language models (LLMs) have been a hot topic in the health plan space. However, there is still hesitancy around their deployment by health payors due to the levels of risk and the significant resources required for implementation with unproven value. In 2025, LLM based- programs will be deployed by innovative health plans and the value of these programs will become better understood. However, it is unlikely that these initial forays into generative AI will power large enterprise engagement programs. Instead, they will have more limited use across bots (with limited scope of engagement topics) and to augment existing engagement strategies.
Andy Flanagan, CEO, Iris Telehealth
LinkedIn: Andrew Flanagan
The AI Risk Stratification Revolution
Forget chatbots and automated note-taking – the real AI revolution in behavioral health will be invisible but far more impactful. Machine learning algorithms will completely dismantle the antiquated first-come-first-served care delivery model, replacing it with sophisticated risk prediction systems that identify and prioritize high-risk patients before they reach crisis points. This transformation will cut emergency department visits for behavioral health issues in half and finally deliver on the promise of preventative mental healthcare. The key difference? These systems won’t try to replace human clinicians – they’ll amplify their impact by ensuring they’re seeing the right patients at the right time.
Virginia Halsey, Senior Vice President, Strategy and Product Management, FDB (First Databank, Inc.)
LinkedIn: Virginia Halsey
We have seen a surge of health systems adopting ambient listening and other generative-AI tools to assist with physician notes, which has helped improve charting and allowed clinicians additional room to focus more on patient care. The next step is to begin to take information from these notes and assist clinicians in completing other actions. In 2025, we will see the beginning of moving items from the notes into the EHR workflow to further improve clinician experience. For example, when the AI tool recognizes in the notes a patient problem and a medication that is going to be prescribed, the system will ask the physician to confirm if it should create a prescription. The prescription will then be teed up at the appropriate point in the EHR workflow for the physician to prescribe. In 2025, we are not likely to see a complete transformation of the existing workflows but more automation to improve clinician workflow. The prescriber will approve the prescription, of course, but there will also be more information in the system to validate appropriateness – we look forward to smarter clinical decision support when the indication of the drug is captured with the prescription.
Gary Hamilton, CEO, InteliChart
LinkedIn: Gary Hamilton
In 2025, the role of AI in clinical settings will shift from passive documentation to active engagement, transforming the delivery of patient care. AI tools will analyze vast amounts of patient data to detect early warning signs and recommend personalized interventions, empowering providers to act proactively. These systems will adapt to individual patient profiles, offering insights that improve treatment adherence and health outcomes. This evolution will make clinical care more precise and patient-centered, enhancing collaboration between patients and providers to achieve better overall health results.
Jason Herzog, CO-Founder and CEO, Holon Health
LinkedIn: Jason Herzog
We will continue to see AI adoption in the healthcare industry in 2025 and beyond.
Today, medical providers spend an inordinate amount of time charting and coding which reduces face-to-face patient care time. AI has the capability to handle charting and coding, freeing up medical providers to focus more on patient care and patient experience. AI will be able to reference a medical decision-making model to make suggestions and to appropriately code for treatment while avoiding coding errors.
For the patient, AI will be able to observe certain minor events that show disengagement or that a patient is straying from their care plan and provide prompts to help course correct. Digital apps can identify when patients are disengaging or straying from their care plan, and prompt them to re-engage. All of this improves patient care and outcomes, while also improving the provider experience by reducing administrative burden.
Kyle Hicok, EVP and Chief Commercial Officer, R1
LinkedIn: Kyle Hicok
In 2025, AI in clinical settings will extend beyond diagnostics to improve operational workflows and care delivery. By integrating with the revenue cycle, AI will ensure accurate charge capture and billing, directly linking clinical documentation to reimbursement. This holistic approach will align clinical and financial objectives, supporting providers in achieving both quality care and operational efficiency.
Lissy Hu, CEO, Ascend Learning
LinkedIn: Lissy Hu
As the AI hype cycle fades and healthcare organizations start to focus on deriving real value from AI, the ones who will be most successful will prioritize training the “humans in the loop.” Healthcare organizations have been talking about AI for several years now, but implementation has been a mixed bag. In 2025, healthcare organizations will prioritize deriving real value from AI. To do that, it’s critical that not only are the AI models trained properly, but the “humans in the loop,” in charge of working with AI tools, are trained properly as well. The organizations that most successfully deploy AI will be the ones who focus on developing the human capital to work with the technology.
Nir Ilani, Vice President of Product, MDClone
LinkedIn: Nir Ilani
When it comes to sensitive patient healthcare data, privacy is paramount. While GenAI technologies can expedite research and augment self-serviceability, AI developers must ensure that research/analytics algorithms do not expose patient records. Forward-thinking, world-class research and development institutions will continue using synthetic data to overcome many of the privacy concerns associated with sharing real-world patient data.
Sandra Johnson, SVP of Client Services, CliniComp
LinkedIn: Sandra Johnson
In 2025, AI and automation will revolutionize healthcare by delivering unprecedented advancements in predictive analytics, personalized medicine, and clinical decision support. These technologies will significantly enhance patient outcomes and streamline operational efficiencies. Automation will alleviate administrative burdens, allowing healthcare professionals to focus more on patient care, thereby improving clinician satisfaction and fostering a more compassionate healthcare environment. As AI continues to evolve, it will play a critical role in driving a more responsive, efficient, and patient-centered healthcare system.
Kevin Keenahan, Chief Product Officer, Net Health
LinkedIn: Kevin Keenahan
Interest in integrating AI assistants, like ambient scribes, into existing EHR solutions is rapidly growing and expected to accelerate as more options enter the market. Tools like ambient documentation hold the potential to improve accuracy and dramatically increase efficiency by capturing physician-patient conversations in real time while analyzing the transcription to generate high-quality clinical documentation. By adopting AI-assisted technology, providers can significantly reduce the time spent on clinical documentation, allowing them to dedicate more attention to patient care while improving operational efficiency and increasing revenue. As AI continues to reshape healthcare, high-quality integrations will be essential for EHR and other technology providers to drive innovation and growth across specialty care settings, ultimately improving patient outcomes.
Tom Langan, Interim CEO, Veradigm
LinkedIn: Tom Langan
As we head into 2025, I predict that AI is going to continue to make a significant impact in clinical settings. Solutions including integrated ambient scribing technologies will facilitate less screen time for providers and offer more face-to-face communication time with patients. These AI-powered solutions can also reduce cognitive stress for providers and their staff, while contributing to a more efficient healthcare ecosystem. By reducing more tedious documentation tasks, more time can be dedicated to focusing on direct patient care.
David Lareau, CEO, Medicomp Systems
LinkedIn: David Lareau
2025 will mark the end of black-box AI in clinical settings as healthcare organizations demand transparency in how AI models are trained and validated using real patient data. We’ll see the emergence of ‘validated AI networks’ where healthcare organizations share proven clinical algorithms with clear audit trails and documented outcomes. The focus will shift from deploying isolated AI tools to creating integrated clinical intelligence platforms that combine decision support, documentation improvement, and patient engagement while maintaining human oversight at the point of care.
Dr Gen Li, Founder and President, Phesi
LinkedIn: Gen Li, PhD, MBA
Interest in AI-powered digital twin solutions in clinical settings is set to surge over the next year, as education and training efforts continue and understanding of the area improves. While adoption may start gradually, it will explode once sponsors become fully familiar with the benefits. The clinical development industry needs to be ready to embrace digital twins to dramatically reduce clinical trial times and costs. Awareness is growing that delaying the deployment of digital twins delays treatments from reaching patients.
Digital twins have real potential to replace placebo or standard-of-care comparator arms, minimizing and ultimately eliminating the need to assign patients to these groups. Not only does this dramatically reduce patient burden and costs but it also tackles recruitment challenges, the ethical issues surrounding placebo or standard-of-care arms, and the impact these constraints have on cycle and approval times. Using AI-powered analysis, digital twins streamline trial planning and implementation, accelerating the clinical development process and discovery of new medicines to patients in dire needs.
As awareness increases and the necessary infrastructure takes shape, AI-powered digital twins are poised to become a cornerstone of clinical innovation, reshaping how research is conducted and care is delivered.
Eliran Malki, CEO and co-founder, Belong.Life
LinkedIn: Eliran Malki
When it comes to AI and patient engagement, I see a future where every patient has their own AI health mentor — someone who truly understands them, knows their medical history, answers their questions, and proactively supports them through their journey. This includes helping patients prepare for doctor visits, complete forms, manage their health between appointments, and answering their questions anytime — even in the middle of the night. Over the next year, we’ll see AI tools become smarter, more empathetic, and seamlessly integrated into both clinical settings and personal use, prioritizing patient safety and trust while becoming a natural part of how people manage their health.
Chris Mansi, MD, MBA, CEO and Co-founder, Viz.ai
LinkedIn: Dr Chris Mansi
In the year ahead, there will be an increased investment in AI as the healthcare industry seeks to deliver more efficient and effective patient care. One area AI can significantly impact is triage and diagnosis. Making the right decision during the first touchpoint with a patient can make all the difference. With AI, providers and healthcare systems can optimize decision making, reduce variability and speed up diagnosis and treatment, ensuring that patients get the right care at the right time, ultimately improving patient outcomes. There is tremendous potential for AI to save healthcare costs and serve as an aid to curbing physician burnout.
Caleb Manscill, President, Vyne Medical
LinkedIn: Caleb Manscill
AI in clinical settings is all about improving patient outcomes and making healthcare smarter and more efficient. As we head into 2025, AI tools are stepping up to help care teams handle rising demands and limited resources. These technologies have the power to cut down transcription times by over 90%, streamline workflows, and optimize staffing processes, giving providers more time to focus on what really matters—the patients. For patients, this means quicker diagnoses, faster treatments, and more personalized care. AI doesn’t just save time; it improves the quality of care by offering insights that help healthcare teams make better decisions. At the end of the day, it’s about making sure patients get the best outcomes possible while giving providers the tools they need to deliver that care.
Shaji Nair, CEO, Friska.AI
LinkedIn: Shaji Nair
Preventative care is undeniably essential for promoting longevity, reducing healthcare costs, and minimizing emergency room visits. However, its success hinges on the ability to design personalized healthcare plans that integrate patient data on medications, diet, and lifestyle. These data are often siloed, making it challenging for physicians—particularly those with heavy patient loads—to deliver individualized “lifestyle” care that can deliver such benefits. This is where AI in clinical settings can play a transformative role. By unifying diverse data points, AI can enable doctors to address interdependencies and optimize treatment plans tailored to each patient’s unique health conditions, family history, and environmental factors, fostering more effective preventative and lifestyle medicine.
In addition to personalized and individualized medical plans, AI can also provide:
- Early Detection: Leveraging metrics like lifestyle and health history, AI can forecast risks for chronic conditions like diabetes, enabling proactive intervention. Early detection and prevention could significantly reduce healthcare costs, appealing to both providers and payers, while incentivizing physicians to prioritize prevention.
- Patient Education: Instead of overwhelming patients with all information at once, AI can deliver personalized, actionable updates over time to promote better adherence and engagement.
- Clinical Decisions: Generative AI can automate the creation of baseline diagnostic and treatment plans from patient data, reducing doctors’ administrative burdens. In the long term, Generative AI can be instrumental in analyzing large datasets to predict risks for conditions like cancer, enhancing early detection and intervention.
David Navarro, Senior Director of Data Science, Harmony Healthcare IT
LinkedIn: David Navarro
Evolving Role of Clinicians Leveraging AI
Clinician roles will shift from manual document generation via non-intuitive document templates to AI document creation. By reducing the time spent on gathering data elements and composing clinical notes, referral letters, and other medical documentation, clinicians can allocate more time to reviewing and refining AI-generated content. This strategic approach, leveraging various input methods like speech recognition and existing clinical data, will significantly enhance both the speed and quality of patient care.
John Orosco, CEO, Red Rover Health
LinkedIn: John Orosco
AI will play a transformative role in clinical settings in 2025, supporting real-time decision-making and personalized care delivery. From ambient documentation systems to predictive analytics that flag at-risk patients, AI tools will enhance clinical precision and efficiency. As adoption accelerates, clinicians will rely on AI to augment their expertise, enabling faster, more accurate diagnoses and better patient outcomes.
Nick Orser, General Manager, Healthcare, Verato
LinkedIn: Nick Orser
Patients expect personalized, frictionless experiences with their providers, yet delivering these experiences has never been more challenging. Why? Because despite EHR consolidation, it is 10x more challenging to understand every clinical and non-clinical touchpoint a patient has with a health system — especially as health systems invest in CRM platforms, digital front doors, joint ventures, data platforms, and vertical integration with specialists, labs, home health, and surgery centers. In 2025, health systems should invest in solutions to join this data together — and then use this 360-degree view of each person’s data as the foundation for their next-generation AI, digital transformation, and data platform solutions.
Piotr Orzechowski, CEO, Infermedica
LinkedIn: Piotr Orzechowski
In 2025, the integration of large language models with clinical AI solutions will unlock a new era of healthcare innovation. These tools will deliver nuanced, context-aware insights, improving the speed, precision, and scalability of care delivery. By addressing challenges like care coordination gaps and the growing demand for personalized care, this technology will elevate outcomes across the industry.
Alvaro Pascual-Leone, MD, PhD, Chief Medical Officer and Co-Founder, Linus Health
LinkedIn: Alvaro Pascual-Leone
Nothing excites me more than seeing significant progress against a formidable disease. Dementia has long resisted efforts to prevent, diagnose and treat it, but I’m confident 2025 will see further advancements in all three areas thanks in large part to emerging healthcare tech–especially AI. The next 12 months–and beyond–will bring new hope to those affected by the disease: patients, care partners and loved ones.
Nate Perry-Thistle, Chief Product & Technology Officer, CipherHealth
LinkedIn: Nate Perry-Thistle
AI’s Role: Measured, Strategic Integration Over Hype
Despite AI’s potential, healthcare organizations remain cautious about its widespread deployment, especially for patient-facing roles. In 2025, we anticipate a “measured adoption,” aimed at demystifying AI, that will focus on supporting healthcare operations without compromising care quality. This means AI will be embraced incrementally—first to assist in data processing, workflow automation, and patient outreach—laying the groundwork for eventual clinical applications. This gradual, strategic approach helps systems build trust and confidence in AI’s role as a supportive force in healthcare.
Shobha Phansalkar, PhD, FAMIA, VP of Client Solutions and Innovation, Wolters Kluwer, Health Language
LinkedIn: Shobha Phansalkar, RPh, PhD, FAMIA
While 2024 may have been one of the biggest years of transformation in healthcare when it came to the use of AI, the same thing that held us back when EHRs were first mandated nearly 20 years ago hinders the progress of healthcare today: bad data. Amid the desire for rapid transformation, organizations can’t forget the importance of this fundamental currency that will power future discovery and insights. Without a system in place that can help assess, clean, maintain and organize data, health systems will be hindered in their ability to leverage AI effectively, make informed decisions, and unlock the full potential of technology to improve patient outcomes, operational efficiency, and innovation in care delivery.
Kel Pults, DHA, MSN, RN, NI-BC, NREMT, Chief Clinical Officer and VP Government Strategy, MediQuant
LinkedIn: Kel Pults
In 2025, artificial intelligence (AI) is poised to significantly enhance the ability to extract actionable insights from archived clinical data. By efficiently analyzing vast datasets, AI can provide clinicians with a broader and more comprehensive view of patient histories, enabling better-informed decisions. For example, AI-driven tools can quickly synthesize past lab results, diagnoses, and provider notes to suggest potential diagnoses or treatment options that may have been overlooked. This capability is particularly beneficial for new providers unfamiliar with a patient’s history, offering a holistic picture beyond the immediate visit.
However, challenges remain in 2025, especially around the variability of archived data and the need for standardization. Structured data, like lab results, is easier for AI to process, but unstructured data in provider notes requires sophisticated natural language processing and machine learning. Additionally, regulatory changes, data privacy concerns, and the need for interoperability across healthcare systems will require organizations to invest in AI solutions that can securely and accurately manage data from multiple sources. Despite these hurdles, AI holds the potential to improve clinical outcomes by making archived data more accessible, meaningful, and actionable.
Saji Rajasekharan, Chief Technology Officer, Experity
LinkedIn: Saji Rajasekharan
As AI becomes increasingly popular in clinical settings, healthcare providers are enjoying the benefits of relying on the technology to help them streamline administrative tasks. In fast-paced environments like emergency rooms and urgent care centers, AI assistants are proving invaluable for optimizing patient data processing, expediting enrollment and discharges. However, provider organizations must maintain healthy skepticism and carefully evaluate these tools to ensure they deliver on their promises of enhancing efficiency and accuracy. Equally important is ensuring these solutions safeguard sensitive patient and facility information, whether the AI is developed internally or provided by a third-party vendor.
Dr. Michael Rivers, Senior Director of Ophthalmology, ModMed
LinkedIn: Michael Rivers, MD
In recent years, we’ve seen a rise in AI-backed initiatives designed to streamline clinical workflows, but for the most part, we’ve yet to see these initiatives produce tangible and impactful results. In 2025, we can expect to see a more significant shift from development to meaningful adoption. Practices are increasingly leveraging AI to automate routine tasks such as faxing, checking insurance claims, patient scheduling, and more, but throughout the next year AI implementation will become increasingly strategic with more defined use cases.
EHR-integrated ambient listening in particular will continue to gain traction, sparing physicians from having to type up their own notes by capturing patient-doctor conversations in the examination room. Practices leveraging tools with only transcription functions, however, may not feel a significant difference. Physicians will primarily benefit from programs that can listen and turn visit notes into actionable, structured information – a key distinction that will become more apparent throughout the year. Not only will this empower physicians to spend more one-on-one time with patients, but it will also prevent them from spending a significant amount of time after hours navigating a heap of notes to find the right information. These innovative technologies, designed to specifically cut down on administrative burden, are where we’ll see measurable impacts.
Cindy Roark, DMD, SVP & Chief Clinical Officer, Sage Dental
LinkedIn: Cindy Roark, DMD
Advances in diagnostic technology are transforming dentistry, enabling faster and more precise assessments that streamline patient care. In recent years, dental practices have increasingly adopted AI-powered tools designed to enhance diagnostic accuracy, early detection, and more personalized treatment planning, and in turn, maximize operational efficiency and drive practice growth. In 2025, however, we will see this technology continue to take center stage, but with deeper significance behind its adoption. Dental practices will place a greater emphasis on leveraging technology to drive empathy and strengthen the patient-clinician connection. For example, patients often find traditional black-and-white x-rays difficult to comprehend, leading to uneasiness during dental visits, but AI-driven imaging software can analyze x-rays in real-time, quickly annotating them in a visual manner that makes it easier for patients to comprehend. This empowers patients to better understand their oral health, reducing anxiety and making them more engaged in the treatment process. Additionally, virtual treatment planning tools will allow patients to visualize procedures in advance, further easing their concerns.
Bryant Robinson, Principle Consultant, Sendero
LinkedIn: Bryant Robinson
I anticipate that AI solutions will play a growing role in patient engagement, particularly in education. Tools like medication reminders, rehabilitation guidance and home-based care support will be leveraged in primary care clinics, behavioral health facilities, specialty practices and chronic disease management centers. As home healthcare and telehealth expand, these technologies will allow patients to play an active role in their care.
AI chatbots will continue to gain traction in care coordination and patient navigation, assisting with tasks such as finding specialists, scheduling appointments, confirming eligibility and connecting patients to appropriate providers. These tools also enhance patient education by supporting discharge processes and advocating for patients which ultimately helps them better understand their care options and readily access services.
Karie Ryan, DNP, MS, RN, CENP, Chief Nursing Officer, Artisight
LinkedIn: Karie Ryan, DNP, MS, RN, CENP
By 2025, successful healthcare organizations will be defined by their ability to implement AI solutions that simplify rather than complicate the care environment. The focus will shift from adding new technologies to integrating intelligent systems that reduce cognitive load and automatically handle routine tasks. Nurse leaders will be an integral part of this integration, and their inclusion in discussion, implementation and adoption of these tools will be paramount.
Greg Samios, President & CEO of Clinical Effectiveness, Wolters Kluwer Health
LinkedIn: Greg Samios
Generative AI (GenAI) is positioned to play a role in improving patient care in 2025, but more work needs to be done to improve consistency and ensure that patients receive the highest quality care. This starts by defining responsible GenAI so that we can enhance efficiency and reach our destination of superior patient outcomes. When thinking about the year ahead, I believe we can’t lose sight of the human touch, or the quality interactions and trusted data that help push us forward. I look forward to collaborating with the healthcare ecosystem to foster a culture of continuous learning, for a safer future.
Jeff Schar, Managing Director, Sendero
LinkedIn: Jeff Schar
As M&A activity continues over the next year, larger health systems will be able to leverage enterprise-wide AI solutions to ensure that patients have consistent experiences across clinics, surgical centers, specialty providers, pharmacies, self-service tools, etc. At the same time, AI solutions can enable smaller, independent health systems to remain competitive by offloading administrative tasks, giving clinicians time back to build meaningful relationships with their patients.
Jonathan Shoemaker, CEO, ABOUT Healthcare
LinkedIn: Jonathan Shoemaker
In 2025, AI technology focused on patient flow will transform clinical settings, shifting from passive documentation to active engagement. These tools will analyze patient data to detect early warning signs, recommend interventions, and ensure patients progress seamlessly through their acute care journey. By delivering real-time insights tailored to individual needs, enhanced patient throughput will improve adherence, enhance outcomes, and strengthen collaboration between patients and providers.
John Theobald, Founder & CEO, Healthcasts
LinkedIn: John Theobald
Gen AI unlocking the power of virtual provider networks
Online physician communities provide virtual spaces for providers to come together from across the country to engage, consult and learn from each other. Historically, clinicians have engaged in virtual communities outside of office hours based on their interest and educational needs, but in 2025 we will see more providers accessing these platforms in the clinical setting to help them make informed treatment decisions at the point of care.
The acceleration of AI has supercharged the traditional physician networks. New Generative AI technologies can comb through massive databases of physician insights, patient cases and other treatment guidelines to create powerful clinician-generated research and consultation tools to deliver actionable real-world guidance to users in real time. As these technologies continue to mature, we expect patient care to improve through expedited diagnostic and treatment decisions at the point of care.
Karen Thomas, Vice President, Clinical Solutions, CorVel Corporation
LinkedIn: Karen Thomas
As we approach 2025, the integration of AI will significantly enhance the clinical landscape, not just for triage, case management, utilization management, and coding. Importantly, AI will not replace clinicians; instead, it will alleviate administrative burdens, enabling them to focus on what truly matters—engaging with injured workers and their support teams. Additionally, the expansion of mental health virtual care will ensure that injured workers can access the support they need, no matter where they are.
Salvatore Viscomi, CEO & Co-Founder, Carna Health
LinkedIn: Salvatore G. Viscomi MD
The use of artificial intelligence (AI) in clinical settings is transforming patient care. Looking toward 2025, we anticipate significant advancements in AI’s impact on chronic disease management. This is particularly true in specialties like nephrology, where AI is poised to significantly enhance the diagnosis, prevention, and treatment of kidney-related conditions, including chronic kidney disease (CKD).
These advancements come at a critical time when healthcare systems face increasing pressure to meet the growing demand for kidney care. Limited resources and a global shortage of specialists have led to provider burnout and challenges in adequately addressing this rising need. With kidney disease projected to become the 5th leading cause of death worldwide, the need for scalable solution is more pressing than ever.
In the coming year, we anticipate that predictive machine learning (ML) will play a greater role in upskilling the workforce and identifying kidney-related diseases early, shifting the focus from treatment to prevention and significantly reducing costs. By utilizing AI to upskill frontline healthcare professionals like nurses, pharmacists, and primary care doctors, we can alleviate physician burnout and address the shortage of specialists. By equipping providers with tools to streamline workflows and better understand patient needs, much of the workload is taken off healthcare professionals and conducted at other points of care. Additionally, ML-driven personalization will facilitate the development of patient-centric treatments tailored to individual needs. These innovations expand beyond diagnosing kidney-related diseases; they allow us to support patients in their journey toward a better life.
Dave Wessinger, Co-Founder & CEO, PointClickCare
LinkedIn: Dave Wessinger
Healthcare at a Crossroads: Trust, Mistrust, and the Future of AI
I believe the healthcare industry as it stands today is unsustainable. Providers may fear AI will further entrench systemic biases, or be apprehensive about the training and re-skilling that might be required, given the cost and complexity of care have escalated. Looking ahead to 2025, a measured approach to AI implementation will hold the key to driving sustainable change across the care continuum, defined by thoughtful adoption within operational and clinical settings. To address specific pain points without forcing new technology on a risk-averse workforce, we – as healthcare technology vendors – should continue to support embracing responsible AI principles and training up providers on how to integrate them as part of their workflow and further embrace AI as a collaborative partner in patient care.