5 ways AI has impacted the healthcare industry

Compared to other industries, healthcare is below average in AI adoption at scale, according to the World Economic Forum. But teams working in healthcare have already found innovative and useful ways to incorporate AI to augment the skills of humans and dramatically speed up the work of caring for patients and solving big problems. 

AI can analyze massive datasets, recognize patterns, automate repeatable workflows, and make predictions, all of which make it a fit for healthcare. It can also help healthcare IT teams alleviate legacy system integrations, resource constraints, interoperability barriers, and more. Here are the top five ways AI in healthcare is making an impact now.

1. Disease diagnostics with AI exceed human capacity 

Using AI to identify diseases has been effective at very early stages, such as with PathAI’s use of machine learning for pathology diagnoses. It analyzes tissue samples more accurately and efficiently, outperforming traditional methods in finding breast cancer biomarkers. This AI use case reduces human error and improves outcomes for very early-stage patients.

And in the U.K., the National Institute for Health and Care Excellence found that AI tools could diagnose fractures better than just a professional review in urgent care settings without increasing the risk of incorrect diagnoses.

2. Drug research and development moves at incredible speed

The lifecycle to develop a single drug can take more than a decade and cost billions of dollars. It’s ripe for transformation by AI, which excels at crunching through massive amounts of data quickly and making predictions accordingly. AI has already shown incredible progress in speeding up this process to bring new, life-changing drugs to market. 

AlphaFold and its Protein Structure Database, developed by Google’s DeepMind AI research lab, predicts individual protein structures that researchers need to know as they’re creating a new drug. Each protein structure previously required years to figure out, but AlphaFold can do it in just minutes with a remarkable degree of accuracy. It’s already predicted more than 200 million protein structures. More than three million global users have accessed the freely available database, and researchers use it regularly to save huge amounts of time and money.

And research company Deep Genomics used its own AI drug discovery platform to identify a candidate molecule to treat genetic disorders, likely years faster than the typical, non-AI research process. 

3. AI agents relieve human workloads

AI agents can serve as a digital workforce within healthcare to automate repetitive, time-sensitive tasks to free up teams for more complex work. Agentic AI solutions are transformative when it comes to medical efficiency, accuracy, and decision-making, and can help tackle common issues like data overload, system fragmentation, and helping providers and patients follow care plans.

Agents can work autonomously, as they orchestrate LLMs with tools and APIs to perceive state, decide, and act. So AI agents in healthcare are often embedded into administrative and clinical workflows for tasks like filling out forms, correctly coding visits for insurance companies, pre-briefing care providers before a patient meeting, taking notes during appointments, and helping doctors quickly search through clinical knowledge for diagnoses. Duke Health reduced patient call wait times by 64% with help from conversational AI tools.  

4. IT teams can solve issues faster

IT teams in healthcare face the unique challenges of ensuring that all patient management systems and electronic health records meet strict compliance standards like HIPAA, HITECH, and others. Patient privacy protections are first and foremost for healthcare IT teams, who have to manage sensitive data and also continually improve operational efficiency and cybersecurity. 

AlixaRx, an institutional pharmacy company, chose Atera’s AI Copilot to update the 24/7 support it offers to its customer facilities. The company had lacked an internal employee ticketing system, but with AI capabilities is now able to resolve tickets faster, optimize their workforce, and improve reporting and device monitoring. AlixaRx has also optimized operations and improved medication accessibility, while more easily adhering to standards like HIPAA’s stringent Privacy Rule.   

5. Predictive analytics and maintenance stay ahead of problems

The medical equipment used in hospitals and clinics everywhere has to be consistently maintained and updated — a manual job that can take up entire teams’ time. AI helps to ensure minimal downtime for medical equipment maintenance, which also helps providers improve continuity of care. Agentic AI in particular can help predict when maintenance problems might occur, and monitor equipment usage.

Phillips uses remote sensing with AI to monitor and analyze hundreds of parameters for an imaging machine, so users can see ahead of time when hardware might need to be fixed or replaced. They’ve resolved 30% of service cases before downtime even happens to prevent downtime and delays.

The sky’s the limit for AI in healthcare 

The use of AI in healthcare has already improved patient care, sped up repetitive tasks, discovered new research approaches, and added efficiency. As generative AI and agentic AI both continue to mature, there are lots more opportunities to add efficiency and speed to an industry that’s struggled with workforce shortages and fragmented legacy IT systems.  

Better IT translates to better healthcare, so IT teams capturing the opportunity of AI are automating routine tasks and centralizing control with technology that’s also compliant with regulations. 

Atera’s comprehensive IT management system provides the AI Copilot advanced assistant for IT technicians to help with managing devices, resolving tickets, and handling alerts, along with monitoring and predictive analytics to anticipate issues. And Atera’s Robin is an AI agent that serves as a step between the end user and IT department, working to solve user issues through multiple channels, only escalating as needed through the ticketing system to IT. It can install tools, reset passwords, and learn specific information over time to better answer user questions. Robin resolves about 40% of the IT workload autonomously, with 80% of tier 1 tickets resolved. With resources in healthcare IT often scarce, that time saved is time spent on more impactful projects.
With all that’s possible with AI in healthcare, how will you get started? Try Atera’s purpose-built systems to add automation and efficiency for improved patient outcomes.