e360

“One of the AI tools that really excites me about healthcare is ambient listening between a patient and a physician.”
— Jim Davis, Vice President & Chief Technology Officer, PeaceHealth

Some of the most impactful AI innovations aren't replacing human interaction. They're creating more space for it.

Jim highlights the potential of ambient listening technology to transform the patient experience by capturing conversations, generating clinical documentation, and translating complex medical terminology into language patients can understand.

The result is less time spent behind a keyboard and more time focused on care.

Just as important, Jim emphasizes the need for governance and oversight. In healthcare, trust is essential, which means AI outputs must be reviewed, validated, and used responsibly.

The most valuable AI solutions don't remove the human element. They strengthen it.

“Anybody can sell products, but very few can help create vision, secure that vision, create use cases, and ultimately deliver things that actually change companies.”
— Mike Strohl, CEO, e360

AI success doesn't start with technology. It starts with strategy.

Organizations today are navigating a complex journey: securing their data, identifying meaningful use cases, deploying AI responsibly, and ultimately creating measurable business value.

According to Mike Strohl, the companies that realize the greatest impact from AI won't be the ones with access to the most tools. They'll be the ones that align vision, security, infrastructure, and ex*****on.

As demand for compute, power, and AI resources continues to grow, access alone won't be enough. Organizations will need the right foundation, the right expertise, and the ability to turn opportunity into action.

The future belongs to organizations that move beyond experimentation and focus on building AI capabilities that drive lasting transformation.

“Maybe those are the rules that we should break.”
— Ted Harrington, Ethical Hacking Expert and Bestselling Author

When most people look at a process, they focus on following the established path.

Hackers take a different approach.

Ted Harrington explains that one of the most misunderstood aspects of the hacker mindset is rule breaking, not for the sake of disruption, but to challenge assumptions that everyone else accepts as fact.

As new technologies like AI continue to reshape industries, many of the constraints we've historically accepted may no longer apply. The organizations that create the greatest advantage won't simply adapt to change. They'll question long-held assumptions about how business operates, how value is delivered, and what is truly possible.

Innovation rarely comes from following the expected path.

It comes from asking whether the rules we've always followed still make sense.

“The impact of healthcare IT goes far beyond technology.”
— Jim Davis, Vice President & Chief Technology Officer, PeaceHealth

Technology in healthcare is never just about technology. It's about the people and outcomes it supports.

Jim Davis shares how working in healthcare IT transformed his perspective, from supporting critical care environments to enabling care across entire regions.

When every system, application, and infrastructure decision can impact patient care, success isn't measured by the technology itself. It's measured by the outcomes it helps deliver.

The most effective technology partnerships don't start with solutions. They start with understanding the challenges and working together to solve them.

“The singularity is here now.”
— Jim Grubb, Chief Technology Evangelist, Cisco

For years, AI singularity has been framed as a future event. Jim Grubb argues it may already be here.

In this video, Jim shares a personal example of how AI has expanded his ability to communicate ideas. While the insights were always there, AI helped bridge the gap between expertise and ex*****on.

The technology didn't replace his thinking. It amplified it.

The most valuable AI use cases aren't about replacing people. They're about combining human creativity, judgment, and experience with machine efficiency to achieve outcomes neither could deliver alone.

The future of AI may not be human versus machine. It may be human and machine.