Bridging the AI Chasm Between Hype and Promise

It seems that each day media and social media headlines are trumpeting the transformative power of artificial intelligence (AI).

And clearly for good reason as generative AI models are crafting content on a daily basis and more and more agentic systems are automating complex workflows on a daily basis.

In other words, the public narrative suggests we're on the cusp of an AI-driven utopia.

And we are.

I think.

And yet, as someone deeply entrenched in the AI landscape, I have observed a stark disconnect between the hype and the promised adoption of AI tools, especially among adults in the United States, both professionally and personally.

The CHRO Conundrum: A Korn Ferry Report

"The Vital Role of CHROs" — a Korn Ferry report released earlier this month — sheds light on this disconnect.

The study reveals that while 42% of Chief Human Resources Officers (CHROs) are prioritizing investments in AI for HR usage, only 5% of HR teams feel fully prepared to implement it effectively.

Only 5%?!?!?! That's insane!!!

Just as startling is the fact that this Korn Ferry report explains that 58% of CHROs are not prioritizing AI investments at all.

What?!?!?! That's nutso!!!

Such data underscores a significant gap between leadership's recognition of AI's potential and the readiness of teams to harness it.

From my perspective, such data enforces the fact that these CHROs represent a microcosm of the broader challenges organizations face in integrating AI into their operations, here in the United States and abroad.

The Reality of AI Adoption Among Adults

Despite the omnipresence of "Artificial Intelligence this" and "AI that" found in media narratives, actual adoption rates tell a different story ... especially in the U.S.

For example, as reported last week by All About AI, AI adoption on a global basis has more than doubled to 47% in 2024/2025, up from 20% in 2020.

Nevertheless, as highlighted in the bar chart below, AI adoption at the corporate / organizational level in the U.S. has shown relatively flat adoption percentages of 22–25% over the past five years.

Additionally, while 39% of U.S. adults aged 18–64 have used at least one GenAI platform, apparently only 9% utilize it daily for professional purposes.

That figure is just shocking to me because it suggests that although exposure to the various AI tools is quite high, consistent and effective usage remains seriously constrained.

In reality, such findings line-up with the preliminary data we have uncovered at WGU Labs as well.

Categorizing AI Users: From Neophytes to Experts

As we have dived deeply into the AI landscape, we at WGU Labs separate AI users into five categories:

• Neophytes: Individuals who have never used AI or tried who it once or twice and then stopped using it;
• Beginners: Occasional users, individuals using AI tools / platforms once or twice a week;
• Intermediate Users: Near-daily users who are still exploring AI's full capabilities, particularly at the GenAI level;
• Advanced Users: Individuals with multiple interactions with AI per day, both professionally and personally; and then last of all,
• Experts: Daily users who have progressed to using, developing and/or deploying various AI-related tools and platforms all the time, including Agentic AI applications.

What WGU Labs has found is that the vast majority of users fall into the Neophyte and Beginner categories, highlighting a vast untapped potential for deeper AI integration.

Additionally, we're also seeing that even for those who use GenAI platforms semi-regularly, the understanding and application of "Prompt Engineering" skill sets is uneven at best.

My Personal Journey: Embracing AI's Potential

Since I began using GenAI tools some 2+ years ago, I have witnessed firsthand their transformative impact.

After joining WGU Labs three-ish months ago, my exploration into generative and agentic AI systems has accelerated significantly.

So much so that my GenAI-empowered productivity gains have been nothing short of astounding, ranging anywhere from 2X to 10X faster, with deeper, broader and more insightful AI-empowered results generated in hours versus days.

For example, I now regularly use GenAI tools — like my "go-to," ChatGPT — to initiate and complete

• Deep-dive Research (across wide and diverse industries);
• Marketing Plan and Report generation;
• Product Development ideation, research, and preliminary coding;
• Developing AI Workshops for "live" presentations;
• Creating Customized Visuals and Presentations;
• Developing initial Agentic AI Solutions; and yes,
• I even Use GenAI tools to Replace Traditional Search Engines.

{NOTE: That last point might surprise some readers, but it shouldn’t.}

As it turns out, a growing contingent of GenAI users (myself included) are increasingly turning to AI platforms like ChatGPT as a first stop for internet search instead of defaulting to Google, Bing, or DuckDuckGo.

Why? Because conversational AI can synthesize, prioritize, and summarize information far faster than traditional search engine result pages.

So instead of combing through a dozen blue links, I get contextual answers, tailored follow-ups, and even citations — all in seconds.

To be clear, using ChatGPT is NOT a perfect search substitute.

Yet.

And at times I still triangulate with standard search tools.

But for research, analysis, and exploration? ChatGPT has become my search engine of choice.

The Disconnect: Hype vs. The Promise of Integrated Implementation

Now ... back to the point of this OpEd ...

In spite of the evident benefits, a significant disconnect still persists too often between the most common AI narrative and the promise of the practical implementation of artificial intelligence among the general populace.

Many organizations (especially in the U.S.), acknowledge AI's potential, yet struggle with integration and implementation, typically due to factors such as

• Lack of training,
• Resistance to change, and
• Infrastructural challenges.

This is evident in the above-noted Korn Ferry report, where a vast majority of HR teams feel unprepared to implement AI effectively or they've decided to not budget for even an attempt at deployment.

But it's not just Korn Ferry reporting this.

In fact, a recent global survey of 48,000 individuals discovered similar findings.

Specifically, in their global 2025 report "Trust, attitudes and use of artificial intelligence" released last month, the University of Melbourne and KPMG found (among other data points), that although

"Two in three (66%) intentionally use AI on a regular basis and three in five say they can use AI effectively (yet) ... most (61%) have no AI training and half report limited knowledge (of basic Prompt Engineering skills)."

The KPMG report further uncovered

"(A general) public ... ambivalence towards AI ... with divided opinion on whether the benefits outweigh the risks in advanced economies."

The Path Forward: Bridging the AI Gaps

To bridge this chasm between AI's promise and its hype, I believe several steps are essential:

1. Invest in AI Literacy: Organizations must prioritize access to resources that not only demystify AI, but provide hands-on, practical trainings to make it accessible to all employees.
2. Leadership Commitment: Leaders should champion AI implementation and integration, setting a clear vision for AI adoption, while also allocating resources to leverage its usage throughout their organizations.
3. Foster a Culture of Experimentation: Based upon personal experience, encouraging teams to explore AI tools without fear of failure can lead to innovative applications, increased comfort with AI toolsets, as well as transformational productivity gains.
4. Collaborate Across Departments: As I experienced firsthand just last week at a multi-day "AI Hackathon" at WGU Labs, cross-functional teams can identify unique AI use cases, while helping ensuring both broader organizational buy-in (and usage) in the process.
5. Monitor and Evaluate: Regular assessments will also help track AI adoption progress, identify challenges, and allow executives and employees to adjust strategies accordingly.

Conclusion: Embracing the AI Evolution

To me the evidence is clear:

Artificial Intelligence has become the next big thing in the society, much as the deployments of the personal computer, Internet/World Wide Web, smartphones, and broadband connectivity equally revolutionized us before the actual advent of AI for the masses.

Nevertheless, I feel that AI holds immense potential to revolutionize industries, enhance productivity, and drive innovation.

And honestly, great change is already being seen by the Innovators and Early Adopters of society, both in the U.S. and abroad.

Yet significant gaps still exist when it comes to the understanding, deployment, and leveraging of AI tools and platforms.

It's why we at WGU Labs are in the earliest phases of crafting a variety of tools and services designed to help leaders understand and implement transformational AI strategies, tactics and tools to help their organizations and employees to thrive in the years ahead.

Hence, if such an approach to AI sounds interesting to you, or if you feel your team might benefit from outside counsel, feel free to reach out.

You can ping me at David.Politis@WGU.edu or (if you found this OpEd on a social media platform), you can also send me a DM.

Thanks.

An Author's Postscript

As a long-time subscriber/reader of Utah Money Watch, you might be thinking to yourself:

"I don't get it, David. Why are you writing about Artificial Intelligence? This OpEd's got nothing to do with 'money' or financial matters?"

And in response I'd merely suggest that AI is all about money — both from the perspective of Utah-based organizations who are focused on AI and have raised lots of money to take advantage of the AI Chasm (or are making lots of money selling their products/services), to those organizations taking advantage of AI to see outsized gains with their teams, products, and services."

So, yeah. This OpEd is ALL about Utah and how firms are spending and making money with and through AI.

A Second Author's Postscript

Yes, I did guide the first draft of this OpEd using ChatGPT. How could I not?

That said, the version you have before you went through significant review and edits by yours truly before it was published.

DLP

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