As more and more industries adopt AI into their technology ecosystem, it's becoming increasingly important for enterprise companies to consider how AI can best be implemented. Healthcare’s history with the technology may indicate how AI can streamline process and improve efficiency on a large scale, irrespective of industry.
Having once been a staple of science fiction, Artificial Intelligence has exited the realm of fiction and is now part of our daily lives. While many might only think of AI use cases in social media and chatbots, the technology actually has a much wider spread; 34% of businesses surveyed already use AI to give consumers highly personalised web experiences, but few are deploying AI solutions in-house to increase their business efficiency, cut administration costs and time, and boost worker productivity.
The healthcare industry is one that has had particular interest in AI, having extensively experimented with the technology in the past few years to help resolve issues around the burden of administrative work and the complex nature of the industry. With 35% of healthcare organisations to employ advanced applications of AI within the next two years and 50% to do it in the next five; it is an industry enterprise can learn from when seeking areas where AI could improve productivity and efficiency.
Despite the complex and demanding nature of healthcare, AI excels at handling a variety of tasks ranging from surgery to providing courses of treatment, and it is set to have a significant impact in upcoming years. Here are some of the use cases of AI found in healthcare which enterprise businesses can learn from.
Supporting employee efficiency
Healthcare staff now spend up to two thirds of their time doing administrative tasks and paperwork. Patient interaction and bedside manner are crucial aspects of our experience of healthcare but increased admin work cutting into doctors’ patient time is not only impacting patient care but is also affecting employee morale.
One of the key strengths of AI is its ability to complement other emerging technologies, such as voice or augmented reality (AR). As such, AI is able to take over administrative tasks that plague healthcare staff by recording consultations through voice systems and displaying relevant information for doctors using AR.
Nuance, a pioneer in voice and natural language understanding, have released studies indicating that the implementation of AI assistants cut down the time spent on administrative tasks by up to 45%. Using AI also decreased administrative errors by 30% and improved documentation of cases by up to 36%.
Augmedix is another innovator helping healthcare staff with Google’s Glass augmented reality glasses. Using the glasses to record both audio and video of consultations, Augmedix has remote scribes write down the necessary information, thus allowing healthcare staff to focus entirely on their patients. Soon AI will be taking the place of these scribes, and with the rapid evolution of AR, healthcare staff could soon see all the necessary information live to help them offer patients more personalised and optimised care.
These time-saving applications of AI and its integration with other technologies are well placed to answer some of the most demanding challenges for enterprise businesses around efficiency, efficacy, and reducing errors. For example, finding inventory in a warehouse could become as simple as asking an AI and having it show you the directions to what you are looking for on AR glasses; sales meetings could have an AI which recognises questions and brings up relevant information to a screen; or monthly maintenance checks and documentation could be completed by AI without the risk of human error. Enterprise businesses seeking ways to increase efficiency need to have an indepth look at where AI could help achieve their goals, much in the same way as the healthcare industry has tackled their administrative problem.
A diagnostic genius
AI excels at analysing vast amounts of data in seconds before delivering an answer to a query. Alexa or Google Assistant are able to answer simple questions in a matter of seconds. When it comes to much more powerful AI such as IBM’s artificial intelligence Watson, the databases the AI pulls from and the speed at which it processes the information are considerably improved, making it an ideal candidate in the healthcare industry to deliver diagnoses by analysing millions of previous cases and research papers.
In 2015, a machine-learning algorithm developed at Stanford correctly identified melanomas as benign, malignant, or non-cancerous with 72% accuracy - 6% more than board-certified dermatologists taking the same test.
In 2016, IBM’s Watson diagnosed a rare form of leukemia and recommended the correct course of treatment in under 10 minutes. By comparing the patient’s case notes with 20 million cancer research papers in Watson’s database, it accomplished what human doctors had been unable to achieve with weeks of effort.
Enterprise businesses face similar challenges around big data. Many large scale companies hold more data than is possible to analyse effectively, whether it be for marketing and sales purposes or just finding ways to increase productivity. The use of AI in healthcare has shown that AI is able to “think” faster and better than humans when working around highly complex and niche topics. While the healthcare industry has used AI to identify cancer and diagnose diseases, businesses should look to explore how AI could handle equally complex analyses based on data, such as the analysis of financial projections and market trends, undertaking quality assurance, or identifying opportunities to increase the efficiency of a manufacturing pipeline.
Giving AI a body
Robots have been used in the medical field for well over a decade, with a steadily increasing success rate. In 2008 a study showed patients operated on by machines for critical heart surgery recovered in less than half the time compared to traditional means.
Robots and AI are closely interlinked: both are introduced to replace a human aspect of a task; physical in the case of robotics, mental in the case of AI. A robot needs a human to be its brain, telling it what to do and how. Conversely, an AI needs a human to act upon its results but does not require instruction on how to achieve a task. It seems only natural then that the two be combined, and with hospitals now experimenting with remote robotic surgery, AI is becoming an increasingly crucial part of automated surgical systems helping meet or exceed the same standards of care humans deliver.
In 2016, an AI robot named the Smart Tissue Autonomous Robot (STAR) did a better job than human surgeons both in terms of time efficiency and surgical effectiveness when sewing together two segments of pig intestine. While STAR did require minimal ‘supervised autonomy’ in 40% of trials, in 60% of trials the AI completed the surgery completely autonomously. Such improvements are driving surgeons to explore more use cases in which AI could help optimise and improve surgeries, such as using AI’s analytical capability to recognise the total surface area of severe burns with pinpoint accuracy or using its precise surgical capabilities for complex surgeries such as hand transplants.
AI is more than just a tool to analyse data banks and provide users with an answer; when combined with robotics, as has been done in healthcare, AI allows robots to perform highly complex and demanding manual tasks completely independently. Robotics have been a part of enterprise businesses for decades, and integrating the technology with AI could for example help optimise manufacturing lines in various industries. Companies such as Amazon have already started experimenting with these ideas, having robots help workers get what they need from warehouses faster by having the robots deliver necessary items to employees for the delivery of a package; in the near future, we are sure to see AI-enhanced robots handle every part of this journey.
A golden age of industry AI?
The healthcare industry’s investment and experimentation with artificial intelligence has allowed it to not only improve the quality of care for patients, but also improve the morale and quality of life of doctors across every area of healthcare; all while reducing the number of errors made in the industry both administrative and medical.
If enterprise businesses are willing to invest time and resources into experimenting with AI as the healthcare industry has, they could begin to see the same drastic changes and benefit from them in the years to come. The businesses that have already embarked upon this journey will be the ones to pave the way for innovation and will gain an edge on their competitors, one that will take years to overcome.
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Scott
Senior UX Planner