Are We in an Artificial Intelligence Bubble?

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Hi readers,

This week I attended SOVRA’s first customer summit to get a sense for what is happening in procurement technology in the US public sector.

The words that came up most often from public procurement leaders at all levels?

Complexity, transparency, trust and value.

Everyone there, without exception, was proud of and devoted to their craft. This was refreshing considering what you could be led to believe if all you do is watch TV…

But, of course, AI was also on everyone’s lips…

So tonight I wanted to explore the possibility that we are in an “AI bubble” right now…

That’s useful information regardless of where you’re doing procurement.

Onwards!

📰 In this week’s edition:

• 📋 5 procurement jobs that caught my eye

• 🏆 The Road to the ProcureTech Cup : Episode 24

• 🌙 Are We in an Artificial Intelligence Bubble?

Note: Some of the content listed above is only available in the email version of this newsletter. Don’t miss out! Sign up for free to get the next edition.

👀 In Case You Missed It…
My Best Linkedin post this week:

Wait, WHAT?! I thought 2025 was supposed to be the "Year of AI Agents" for procurement...

The Journey Continues…

This Friday SpendHQ comes on the show to demo their Procurement intelligence platform.

Don’t miss episode 2025-24:

Last Episode

ProcurementIQ was on the show last Friday to give the world an *exclusive* first look at their new revamped platform.

If you missed it, I’ve made ALL the replays available for you on YouTube:

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Are We in an Artificial Intelligence Bubble?

The parallels are undeniable: massive capital injection, soaring valuations, and a gold rush mentality that feels eerily familiar to those who lived through the dot-com era...

But here's what's interesting: while artificial intelligence has been around for decades, with mature branches like machine learning, natural language processing, and computer vision driving real business value, it's specifically generative AI that's creating today's bubble dynamics.

Before we dismiss this as just another tech bubble though, let's dive deeper into what's really happening in the world of AI, particularly in procurement and enterprise software.

The Promise vs. Reality

Today's Generative AI agents are genuinely revolutionary. They can draft contracts, analyze spend data, and even negotiate with suppliers (with human oversight, of course). They do all this in conversational form, becoming a powerful assistant.

The productivity gains can be significant, particularly in specific task areas, procurement teams using AI assistants can, as examples:

• Automate parts of contract review that previously took hours

• Draft initial supplier communications in minutes instead of hours

• Process hundreds of invoices for irregularities in the time it would take a human to review a dozen.

However, it's important to note that Generative AI is powered by statistics and not pure mathematics. What does that mean?

A sizeable percentage of the time, it will be WRONG.

If we oversimplify how Gen AI works, we should understand it as a “most likely next word guessing machine…” That means it has a very hard time producing anything truly unique and novel.

But that doesn’t mean it can’t be useful…

When used carefully, these tools are more than just advanced chatbots; they are changing the way procurement teams work.

But, here's where things get interesting…

Despite these impressive capabilities, most AI companies are burning through cash at an alarming rate. OpenAI, despite its $157 billion+ valuation, reportedly spends around $700,000 daily just on operating costs.

In 2026, it is projected to generate loses of $14B!

When you break down the economics of large language model queries - costing anywhere from $0.002 to $0.06 per query - the path to profitability looks increasingly challenging.

The Internet Parallel

This situation mirrors the early internet era in fascinating ways.

In 1999, Amazon was hemorrhaging money, and skeptics questioned if online retail would ever be profitable.

We all know how that turned out… 😅

The internet truly was revolutionary - but not every dot-com company survived the bubble's burst.

Similarly, Generative AI is driving a fundamental technological shift that will reshape business. But that doesn't mean every AI startup will succeed, or that current valuations make sense.

The Bubble Question

So, are we in an AI bubble? Yes and no.

Yes, there's certainly bubble-like behavior in AI valuations and funding. When early-stage AI companies with no revenue command nine-figure valuations, it's hard to argue otherwise.

But no, AI itself isn't a bubble - it's a fundamental technology shift like the internet, electricity, or the steam engine. The challenge for procurement leaders is separating the signal from the noise.

What This Means for Procurement Teams

• Be selectively aggressive. Don't avoid AI tools out of bubble fears, but be strategic about adoption. Create environments where you can test potential in your particular context. Focus on proven use cases with clear ROI. Go “All in” when testing is conclusive.

• Watch the economics. As AI query costs evolve and new models emerge, the economics of AI tools will change dramatically. Stay informed and flexible in the models being used in the background.

  (Most ProcureTech software providers see this coming… They are building their tools to be “model agnostic” meaning you can switch out the model being used in the back and the process supported by the tool still works.

• Build internal expertise. This is where the role of Digital Procurement Lead becomes crucial. Rather than fully outsourcing AI functionality to vendors, organizations need dedicated experts who understand both procurement and technology. These digital leaders can bridge the gap between traditional procurement processes and digital capabilities (including AI), ensuring thoughtful implementation and adoption.

  They're not just tech enthusiasts - they're procurement professionals who can translate business needs into realistic technological roadmaps.

The Future of AI Models

The next frontier in AI isn't about building increasingly massive, resource-hungry models that burn through computing power and capital. Instead, I believe the winners will be those who can build and deploy specialized, efficient, fit-for-purpose LLMs that solve specific business problems.

Think of it like this: we don't need a super intelligent AI to process invoices or analyze supplier risk…

We need focused, cost-effective models that do one thing extremely well.

This shift towards specialized LLMs will likely lead to commoditization of the base technology over time. The real value won't be in having the biggest, baddest model, but in having the most comprehensive library of efficient, purpose-built models that solve specific procurement challenges.

Looking Ahead

The AI revolution is real, but like the internet revolution before it, it will take longer than optimists expect and unfold differently than anyone predicts. Some of today's AI darlings will fail, valuations will likely correct, and the technology will probably take longer to mature than current hype suggests.

But just as the internet bubble's burst didn't negate the internet's importance, any potential AI bubble won't change the technology's fundamental value. The key is maintaining perspective: embracing AI's genuine benefits while staying grounded about its limitations.

For procurement teams, this means continuing to explore and adopt AI tools, but doing so thoughtfully and with clear eyes about both the potential and the pitfalls. It’s about tying AI initiatives back to business outcomes and understanding that you can’t let Gen AI operate freely without qualified business experts overseeing it.

The future of procurement is AI-enhanced, not AI-replaced.

Understanding this distinction will be crucial for navigating whatever market turbulence lies ahead.

What do you think? Am I overrating the role of AI going forward? Am I underrating it?

Let me know in the comments 👇

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