The Centers for Disease Control and Prevention (CDC) started using AI to help improve public health work. One big use of AI at the CDC is watching infections in real time. This helps officials find outbreaks sooner and act faster.
AI systems at the CDC mix machine learning with human checks to look at lots of data from many places. For example, these systems study emergency room symptom reports almost right away using the National Syndromic Surveillance Program. This program uses AI to find odd groups of symptoms that could show a new infectious disease. That way, healthcare workers can step in quickly.
Also, AI tools help sort through a huge amount of information fast. The CDC uses AI software to organize about 8,000 news articles daily about disease outbreaks automatically. This process helps health experts follow disease patterns without getting overloaded by data.
Another example is AI that analyzes satellite images to find cooling towers during Legionnaires’ disease outbreaks. By automating this, the CDC saved over 280 hours a year on investigations. This precise data helps track diseases better and gives quicker, safer responses during health threats.
Because diseases can change quickly, timely monitoring and data checking are very important. AI helps predict outbreaks and understand how diseases spread. This benefits healthcare places that must adjust staff and resources to changing needs.
Medical research and clinical trials help make new drugs, vaccines, and medical tools. But managing trials means handling lots of data, like patient history, who can join, and study results. This can slow things down.
AI agents can make clinical trials faster by doing routine tasks and helping researchers. Salesforce Agentforce AI shows how this works. It connects real-time study data and helps check trial sites, making work smoother for researchers.
AI helps with patient recruitment, tracks study progress, checks data accuracy, and gives care coordinators summaries of patient information, such as medical history and missed care. This lowers mistakes and makes management easier. With AI help, researchers can focus on tough decisions instead of paperwork.
Using AI in trials helps healthcare groups finish studies faster and get new treatments to patients sooner. For admins and IT workers, this tech can improve resource use and keep data safe and private.
Healthcare workers spend a lot of time doing paperwork and data entry. According to Salesforce, about 87% of them work late to finish these tasks, causing frustration and tiredness.
AI agents can cut down this work a lot. Salesforce’s Agentforce AI tools save healthcare teams up to 10 hours a week. Doctors reduce paperwork by about 30%, nurses by 39%, and admin staff by 28%. These saved hours let clinicians spend more time with patients instead of on forms.
Healthcare groups like Rush University System for Health use AI assistants to handle appointment booking, insurance checks, approvals, and patient guidance. Jeff Gautney, CIO of Rush University, said AI lets human agents focus on harder patient questions by taking care of simple, repeated requests all day and night.
Taking away some admin pressure can make healthcare jobs better. About 61% of workers think AI will improve their work life. This also helps patients by speeding up responses and cutting wait times.
Healthcare admins and IT managers get practical help by adding AI to daily work beyond just infection tracking and clinical trials. AI automation supports many front-office roles like patient contact, checking eligibility, and verifying insurance.
Working with platforms like athenahealth and Availity, AI agents improve communication among healthcare providers, payers, and patients. For instance, AI can schedule appointments by finding the right in-network specialist and arranging times that fit patients and doctors. This is very helpful when there are many patient calls and fewer canceled or missed visits due to admin errors.
AI also speeds up eligibility checks and insurance approvals, giving results in seconds through automated talks with payer systems. These features meet and go beyond government rules like the Centers for Medicare & Medicaid Services (CMS) standards, cutting delays that trouble many providers.
Admins in charge of several facilities can use AI to watch referral trends, notice care gaps, and summarize patient medical info. This helps care coordinators give timely and personal care, which leads to better patient involvement and treatment follow-up.
Also, AI automation lowers human mistakes from typing data by hand, speeds billing and claims, and improves money flow for healthcare groups. AI phone systems handle common patient questions so office staff can focus on harder tasks.
The CDC’s Public Health Data Strategy uses AI to handle big and complex health data sets, making data sharing faster and more accurate. Using machine learning, the CDC finds links in data that older methods miss. This helps with better public health actions.
This approach helps local health systems too. When public health workers use AI to predict flu patterns, find outbreak spots, or watch vaccination rates, hospitals and clinics can plan staff and resources better. This planning lowers disruptions during busy times.
CDC training programs like the AI Accelerator and AI Community of Practice teach healthcare workers about AI safely and well. Working with state and local agencies also promotes responsible AI use and gives healthcare groups good, reliable data tools.
Healthcare groups thinking about using AI should keep three things in mind:
Using AI for infection tracking, clinical trial help, and workflow automation can lead to better patient care, save money, and improve job satisfaction. Medical practice admins and IT leaders in the US should think about these points when planning to handle admin tasks and public health needs in the long run.
By adding AI agents to daily healthcare work, medical practices can react faster to infection risks, support research, and improve patient care and access. These are practical changes that balance technology and the needs of both healthcare workers and patients.
Agentforce for Health is a new library of pre-built AI agent skills and actions created by Salesforce in 2025 to address time-consuming administrative healthcare tasks like eligibility checks, scheduling, insurance verification, and prior authorization.
The AI agents handle patient inquiries, eligibility checks, insurance benefit verifications, prior authorizations, scheduling appointments, monitoring infection spread, and supporting clinical trial site analysis and innovation.
AI agents reduce administrative burdens, saving healthcare teams up to 10 hours weekly, with estimated workload reductions of 30% for doctors, 39% for nurses, and 28% for administrative staff, thereby improving job satisfaction.
The agents chat directly with patients to match them with in-network providers and specialists and intelligently schedule appointments via integration with electronic health record systems like athenahealth.
Salesforce partners with athenahealth for scheduling, Availity for direct payer communication and eligibility checks, and Infinitus.ai for electronic benefits verification to streamline prior authorization and insurance validation processes.
Agentforce supports compliance with Centers for Medicare & Medicaid Services interoperability mandates by enabling real-time submissions and receipt of prior authorization decisions within seconds, reducing administrative delays.
AI monitors the spread of infections by auto-classifying cases and accelerates drug and medical device innovation via real-time integrated study data and intelligent clinical trial support.
Agentforce provides care coordinators with patient summaries including medical history, referrals, care gaps, and benefits, enhancing patient access and personalized care management prior to appointments.
Organizations like Rush University System for Health use AI to automate administrative tasks and provide 24/7 patient support, freeing human staff to focus on complex issues and improving the patient experience.
Salesforce executives anticipate a modest revenue contribution from Agentforce in fiscal year 2026, with a more meaningful financial impact expected in the following year, reflecting gradual market adoption.
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