There is a lot of excitement about the role that artificial intelligence (AI) will play in the healthcare space. The opportunity to not only engage with people in more personalized ways, but the ability to tailor a unique treatment plan for an individual is at the forefront of this excitement.

Despite the enthusiasm, implementing AI methods in healthcare settings is still a rarity. In 2017 the overwhelming majority of healthcare delivered in the US had little to no AI involvement. However, 85% of US health executives believe AI will have a central role in healthcare within the next three years. So when it does arrive, it’s going to happen fast.

The same applies to using AI in health engagement. Improving health engagement is a top priority for many healthcare organizations. Many believe that AI will play a pivotal role in disrupting the current model and it will influence engagement in a major way. While some of this has already started, what can we expect AI in health plan member engagement to look like in the coming years?

Personalization Driven by Data

It’s clear many peoples’ lives could be transformed if they visited the doctor more regularly or took action to ease a chronic health problem. Even though we know people like this are out there, it can sometimes be challenging to identify who they are. When we can find them the engagement process can be difficult and communication attempts may go unanswered. Whether we are trying to connect with someone to visit their doctor for a cancer screening, annual visit, flu shot, or something else—if people aren’t taking action, they likely aren’t getting the care they need.

AI can help empower people to take action. AI can help healthcare organizations move away from traditional methods and embrace a data driven approach, one that is unique to the individual based on their preferences. People are used to this type of personalized engagement in other aspects of their life, so introducing it to healthcare is nothing new.

When we can apply data to drive engagement, we’ll be able to target people more effectively. Machine learning helps to achieve this. Machine learning is a software subset of AI that becomes smarter as it is fed more data. As the system learns, it can help determine which channels and messages to best reach specific people. If something in this process isn’t working, machine learning can quickly fine tune the process and find a better way to engage. Being able to communicate how and when someone prefers to be reached adds a human element to engagement. This feels much more personal than traditional methods and typically leads to action.

AI Enables the Audience of One Approach

Beyond being able to find the right time and place to communicate with people, AI can help further personalize the engagement process. Many healthcare organizations haven’t embraced new communication channels, sticking with tradition rather than trying a more modern approach. But with AI, we can do more.

Targeting is one thing, but being able to tailor a message specific to one individual based on their unique health history, risk factors, gender, and location—all while communicating through their preferred channel at the optimal time? That’s something entirely different. This precision method isn’t just a pipe dream, it’s entirely possible with the use of AI.

Consider the impact. When done right, health engagement could transform someone’s life. A message delivered at the right time through the right channel could be the difference between lives lost and those saved. That’s humanizing healthcare—creating an experience that empowers people to take action based on a personalized engagement strategy.

It might seem ironic that AI will help healthcare organizations drive more humanized and personalized engagement to ultimately reach people more effectively. With the help of machine learning, healthcare organizations can spend more time making people healthier, rather than spending countless hours on unsuccessful engagement efforts. The partnership between people and AI is a powerful one that will drive personalized engagement and make improve overall health outcomes in the near future.