Welcome to the AI Swamp - AI Doesn't Create Complexity.Leadership Does.

EXECUTIVE EDITORIAL

Healthcare is about to spend billions of dollars on AI while missing the one capability AI cannot create: accountability.

Healthcare is about to make its most expensive mistake. We’ve invested poorly before not this one could be the biggest.

Over the past twenty years, health plans, provider organizations, ACOs, MSOs, and medical groups have invested billions of dollars in technology platforms, data warehouses, interoperability initiatives, analytics solutions, and digital transformation programs.

Yet most organizations still struggle to answer one fundamental question:

Who owns the outcome?

Now we are repeating the same behavior with artificial intelligence. Every department wants an AI strategy. Every vendor has an AI solution. Every executive team is discussing productivity gains. Every conference is filled with AI success stories.

Yet few organizations have established enterprise accountability for what happens after implementation. Healthcare is rapidly moving from data silos to AI silos.

That should make every CEO nervous.

Today, care management is deploying AI. Risk adjustment is deploying AI.
Customer service is deploying AI. Clinical operations is deploying AI.
Network management is deploying AI. Population health is deploying AI.
Payment Integrity is deploying AI. Everyone is implementing AI.
Few are aligning it across the enterprise.
The result is an emerging AI swamp built on disconnected workflows, fragmented ownership, competing priorities, and multiple versions of the truth.

Let’s be honest. Healthcare has had a technology problem, but now even worse healthcare has an accountability problem.

The scale of investment should concern every board member.

UnitedHealth Group has committed approximately $3 billion toward AI investments across 2026 and 2027, including $1.5 billion this year alone. More than 22,000 engineers are supporting initiatives spanning revenue cycle management, prior authorization, pharmacy operations, clinical decision support, fraud detection, consumer engagement, and enterprise software modernization.

Notice what United is not doing. They are not launching random pilots. They are building a disciplined operating model. Each investment supports a defined business objective. Each investment has executive sponsorship. Each investment has accountability. Each investment has a pathway to scale.

Elevance Health is pursuing a similar strategy, investing more than $1 billion across AI and digital capabilities. Its Health OS platform reportedly reduced prior authorization denials by nearly 70%, while more than 60,000 employees have access to AI-powered productivity tools. This is not experimentation.

This is enterprise execution.

Yet many organizations continue to approach AI as a collection of projects rather than an enterprise strategy.

That is where the danger begins. Most healthcare organizations can tell you how much they spent on AI.

Far fewer can tell you:

How much medical expense AI reduced.
How much provider abrasion AI eliminated.
How much member retention AI improved.
How much Stars performance AI influenced.
How much risk adjustment accuracy AI increased.
How much clinician burnout AI prevented.
How much revenue AI generated.

And if you cannot prove the outcome, you cannot claim the impact.

The most dangerous metric in healthcare today may be AI adoption.

— Adoption is not value.

— Usage is not value.

— Automation is not value.

Value occurs when measurable business, clinical, provider, member, or financial outcomes improvement.

Anything else is activity.

Healthcare should take a lesson from IKEA. IKEA implemented AI to handle routine customer interactions while enabling employees to focus on higher-value customer needs. The objective was not simply efficiency. The objective was a better customer experience supported by measurable operational performance.

Healthcare continues to frame AI as a workforce conversation.
It should be framed as an efficiency and outcome conversation.

The future will not belong to the organizations with the most AI tools.
It will belong to the organizations with the most disciplined enterprise wide, aligned and clear accountability.

My prediction is straightforward.
Within the next three years, healthcare organizations will discover that many AI investments generated productivity gains but failed to create measurable enterprise value.

The winners will not be determined by who spent the most.

They will be determined by who connected strategy, workflow, data, accountability, human oversight, reporting, and outcomes from beginning to end.

The question every health plan CEO, provider CEO, Chief Medical Officer, Chief Operating Officer, Chief Information Officer, and Chief Data Officer should be asking today is not:

Do we have an AI strategy?

The real question is:

Who owns the result when the algorithm is wrong, the workflow breaks, the member is dissatisfied, the provider is frustrated, and the ROI never materializes?

Because if nobody owns the answer, you do not have an AI strategy.

You have an AI swamp.

THE NUMBERS

$3 Billion	UnitedHealth AI investment (2026–2027)
22,000	Engineers supporting AI transformation
$1 Billion	Elevance AI & digital investment
70%	Reduction in prior authorization denials
Unknown	Enterprise AI ROI demonstrated
Consistent Question	Who owns the outcome?

BOARDROOM QUESTION

If every department owns an AI strategy, who owns the enterprise?

MY PREDICTION

The organizations that win with AI will not be the first adopters.

They will be those with agile, accountable, enterprise-aligned visions, strategies, governance models, and execution blueprints.

AI scales processes.
Leadership scales outcomes