If you spent seven figures on an AI solution last year, you might already be behind. And that’s not a failure—it’s a feature of the era we’ve entered.

AI isn’t just another enterprise software wave. It’s a seismic shift, accelerating at a pace that outstrips traditional procurement cycles, IT infrastructure planning, and even most executive briefings. But amid the churn of tools and hype, one truth remains: your smartest investment isn’t in any single AI product—it’s in your team’s capacity to adapt.

The Pace of Obsolescence: Why AI Breaks the Traditional ROI Model

According to a recent Gartner report, over 80% of AI projects in healthcare fail, with 30% of generative AI initiatives abandoned before they even move past proof-of-concept [1]. The reasons? Familiar ones: poor data quality, vague goals, and vendor promises that dissolve upon deployment.

The situation isn’t exclusive to small-scale experimentation. In 2023, Recursion Pharmaceuticals spent $40 million to acquire Cyclica, an AI drug discovery platform. Within months, the platform struggled to deliver impact at scale, stalling amid integration issues and mismatched expectations [2].

For healthcare systems, associations, and professional organizations, this is a flashing red signal. Investing in AI like it’s an MRI machine—expecting it to deliver over a decade—is misaligned with how fast AI capabilities and user needs evolve.

What Actually Endures: Mindset, Literacy, and Organizational Agility

In a volatile landscape, your most valuable asset is not a model or vendor—it’s team fluency.

The best AI strategies in 2025 prioritize people-first enablement:

• Building basic AI literacy across departments
• Upskilling through free or low-cost training
• Encouraging experimentation with low-stakes tools

Companies like Johnson & Johnson have made generative AI training mandatory for over 56,000 employees, teaching prompt writing, responsible AI use, and system evaluation [7]. Likewise, Rutgers University now offers programs tailored to non-technical professionals to help them integrate AI into real-world workflows [8].

“AI is not a destination—it’s a capability. Our responsibility as leaders is to build teams who can navigate change, not just survive it,” said Lise Puckorius, CAE, CEO of OLC.

The takeaway? AI isn’t a department. It’s a competency.

Spam vs. Substance: How to Spot Real Value For Your Organization in an AI Flood

Every inbox in healthcare and professional services is overflowing with vendors claiming to offer “AI-powered” solutions. But not all of them are built on trustworthy foundations.

Red flags to watch for in AI vendor pitches include:

• Vague or opaque model descriptions
• Lack of transparency about training data
• No mention of bias mitigation or security protocols

Cybersecurity leaders now recommend aligning AI vendors with frameworks like NIST’s AI Risk Management Framework to ensure you’re not buying snake oil [5].

Meanwhile, even the Federal Trade Commission (FTC) has warned of rampant “AI washing,” where companies exaggerate AI capabilities to drive sales or investor interest [6]. It’s a new version of the dot-com bubble—except this time, the jargon is machine-learned.

The bottom line: Be as skeptical of AI claims as you are of miracle cures.

A New Strategy for AI Investment

Don’t buy big. Build smart.

Whether you’re a healthcare system, a professional association, or a conference leader, the smartest AI strategy right now isn’t about locking in long-term platforms—it’s about creating the conditions for continuous adaptation.

At OLC, this principle isn’t theoretical. For years, the organization has integrated AI-powered systems into surgical training environments, with a particular focus on orthopaedic education. Rather than betting on any single tool, OLC has prioritized flexible, evolving applications that enhance how clinicians learn, engage, and improve outcomes.

It’s a model worth following: empower your team with foundational training, experiment on the margins, and stay agile with quarterly re-evaluation of tools—not annual vendor contracts. In today’s environment, resilience and responsiveness are more valuable than fixed infrastructure.

Real Resources, Zero Cost: Where to Start If Your Team Is New to AI

The good news? Many of the best AI tools and trainings are free and already available. You just need to know where to look.

• OpenAI Academy launched in April 2025 to provide non-technical professionals with AI fundamentals, prompt-writing exercises, and hands-on guidance from GPT-5 tutors. It’s built for accessibility and designed to evolve with your team [3].
• Amazon’s “AI Ready” initiative has pledged to train over 2 million people worldwide by 2025 with self-paced courses in foundational AI, ethical use, and practical applications in healthcare and business [4].

If your team has an hour a week to spare, these resources can transform passive users into capable AI collaborators.

Is AI Still Worth The Investment?

Absolutely—but not in the way many organizations think. The mistake isn’t investing in AI. It’s assuming today’s tool will meet tomorrow’s need.

Across industries, the most future-ready teams aren’t locking themselves into decade-long contracts; they’re layering AI into existing programs and workflows, piece by piece. Their approach reflects a broader principle: don’t try to future-proof the tool—future-proof your team.

At the OLC, that’s already in motion—integrating AI into its surgical training infrastructure gradually, intentionally, and with a clear goal: to raise the bar in orthopaedic education without chasing hype. The next big model may drop next quarter. Today’s interface could be obsolete by year’s end. But the core capability—to adapt, to assess, to apply wisely—will never go out of date.

And in the world of AI, that’s your real competitive edge.