Typical data privacy and cybersecurity practices in health care are not known for being agile or adapting to change quickly. These groups should be integrated into pilot efforts run by nontraditional departments within the organization so they can benefit from insights and learnings that could make their people, process, technology, and data capabilities more agile and forward-looking. Doing so can not only help cyber adapt to fast-moving change, but also enable more successful digital health–related innovation within their organizations.

Across many industries, by 2023, organizations that are part of a connected digital business ecosystem will have 40% of their customer service cases initiated by business partners in that ecosystem. A challenge for health care organizations will be trusting the devices and data they generate, which may often be outside their control. Securing these ecosystems is integral to their achievements and those of the digitally powered and virtual health care services they provide.

The number of devices will significantly increase in the future of health care, as will their value in the health care ecosystem. The challenge for health care organizations will be trusting the devices and data they generate, which may often be outside their control. From wearables and home-based telemetry devices, managing the security and privacy risks for these types of devices and the data they produce will be a front-and-center priority.

The future of health will be characterized by lots of devices, lots of data, and lots of sharing—which will make radically interoperable data and open platforms key enablers of the innovative services and delivery models on the health care horizon. These same forces will also make digital privacy a high priority. Health care organizations will need to account for privacy, ethics, and other considerations when designing and creating data flows.

During this pandemic, AI projects have accelerated in health care, bioscience, and health-related sectors such as manufacturing, financial services, and supply chain. Proactive threat analysis on AI applications and protection of AI source data and algorithms are just a few of the strategies organizations should be prepared to use to enable the ethical design and governance of this powerful technology. Adapting a holistic framework for trustworthy AI and AI ethics can help organizations mold their cybersecurity capabilities to address emerging threats and ethical risks from the application of AI- and machine-based decisions.

As the future of health takes shape and consumers assert more control over their health decisions, cybersecurity and data privacy solutions should be easy to consume if they are to be viable. Having a 15-character password that must be changed every 30 to 60 days may not be an effective way to engage consumers seeking access to health services from their personal devices. And if individuals don’t have visibility into their personal data and how it is being used, they may be reluctant to share it with organizations.