Turning AI into Positive Impact with “Actionable” Intelligence

By Kelly Phillips, Director, Product Management, Value-Based Care Solutions

Everyone’s talking about artificial intelligence, but how many healthcare teams are actually experiencing it as something that makes their work easier, faster, or better? We are seeing AI come to life in demos, on dashboards, in email crafting, and even in hypothetical use cases, but what we all long to see is proof that it reduces technical burdens on clinicians, providers, and administrators.

In healthcare, innovation is critical (and inevitable), but it’s easy to get lost in the theoretical or conceptual side of technology. To many, AI is a buzzword bubbling up in conversations and brewing in the shadows, but care delivery continues running into the same challenges. Healthcare providers need AI that is actionable when decisions are made, tasks are executed, and patients benefit in real time. Otherwise, it’s just noise without any real meaningful impact, and the technology becomes just another ‘shiny new toy’ that looks great in a demo and mysteriously disappears in real workflows. So, what does it mean to shift our thinking about artificial intelligence to actionable intelligence?

AI Should Enable, Not Distract

As a leader in the healthcare product space, my job is simple: solve the right problems and make the right thing, the easy thing to execute. The introduction of AI in healthcare has also forced product teams to think differently and ensure AI isn’t just a great idea or a quick way to collect requirements and write user stories (we’ve all seen how that movie ends…), but rather a pragmatic tool that becomes an extension of a high performing clinician and helps care teams improve patient care efficiently and effectively with clear and obvious results.

In the product realm, that means we must stop obsessing over what these AI tools can technically do and start obsessing over what the user actually needs them to do. 

What “Actionable” Intelligence Really Means

Being actionable isn’t about creating another new workflow that requires retraining and learning curves and comes with a side of a 45-minute walk through no one has time for; it’s about propelling the user to the next step in an already defined workflow and equipping them to make data-driven decisions that positively impact patient care. 

Here’s how we think about that in product development.

1. User-Centered Design: The first principle of actionable AI is that it must be designed with the user in mind. When building with AI tools in healthcare, we can’t afford to let the technology drive the decisions. Instead, we should start with understanding the daily challenges and needs of our users, whether they are administrators, physicians, nurses, or therapists. Our job is to ensure AI can fit naturally into your workflow without requiring a radical shift in how you work. This is also why it’s important for users to engage in opportunities to work alongside product leaders in focus groups, betas, and more – we are here and want to hear from you.
2. Immediate Impact: Actionable AI should be immediately useful. It can’t be something that requires long training sessions, complex integrations, or steep learning curves that kill speed to value. Speed to value is about helping your organization realize benefits faster with less manual effort, less disruption, and quicker access to actionable insights. When a clinician logs into a system, any AI tool should already understand the context of their work and present them with real-time, relevant suggestions. This could be anything from showing the user what matters most to them in their role, recommending the next best steps towards improved outcomes, or highlighting risk factors the user may not be aware of.  The value becomes unmistakable when every user receives insights tailored to their role without having to go on a scavenger hunt.
3. Focus on the Next Action, Not the Insight: We often talk about AI as a tool that can generate insightful reports or predictive models, but too often, these insights don’t drive action.  Actionable AI doesn’t just point out what’s important; it should highlight the next step that the user needs to take. Whether it’s a suggested action, follow-up task, or alert to a critical risk, AI should help bring clarity to what the user should do right now.
4. Seamless Integration: Actionable AI must be embedded in the tools that users are already familiar with rather than creating disparate systems that force users to switch between platforms with the burden of login/logout workflows.  

Bottom line: if you have to think about AI instead of the patient, something has gone wrong.

Why This Matters to You (and Your Team)

Healthcare is already complex. Your workflows are full. Your decisions carry weight for your patients. The last thing you need is another ‘exciting new tool’ that’s hard to use or adds more to your already overflowing plate.

You deserve tools that:

• Save time without sacrificing quality and causing distractions
• Fit naturally into how you already work
• Support decisions with clarity, not confusion
• Help you take meaningful action that positively impacts patient care

We are well past “what if AI could…” and are now asking “how does this thing help me do my job better, easier, faster, and with less friction?”

Why Does Actionable Intelligence Matter?

For the end user, actionable AI is a game-changer. Instead of navigating through complex systems or data overload, healthcare providers can rely on AI to give them focused, timely, and relevant information that enhances their decision-making in real time.

The future of AI in healthcare technology won’t be defined by what it can do, but by what it actually helps clinicians do and how it impacts patient care.  That responsibility belongs to product leaders, and getting it right is how we turn innovation into real impact at the point of care.  AI doesn’t change healthcare; action does.  And it’s up to product leaders to make sure the “A” delivers in an actionable way.