The big promise
Last week, someone told me, “AI is going to transform the world.”
Maybe it’s my inner skeptic, but my immediate reaction was: really…? Quickly followed up by: when, how, and for whom? Because the data I’ve seen suggests a different reality.
Gartner reported that only 1 in 50 AI initiatives delivers truly transformative value, and only about 20% show any measurable ROI at all. Some might say it’s too early on, but I still think it’s fair to ask: has anyone actually seen worthwhile results yet? Ideba President David Sly touched on this disconnect and similar sentiments in a previous post, “A Unique Perspective on AI.”
To be clear, AI does work in certain areas. No argument there. Tasks like summarizing documents, meetings, and cases, drafting first‑pass content, triaging chats, and debugging support. But do those gains justify the significant, ongoing spend, especially when much of the output still requires human review?
And there are real risks when AI goes unchecked. We’ve all seen cascading bugs caused by AI-generated code pushed into production without oversight, and confident but incorrect conclusions drawn from misinterpreted or hallucinated data. The old saying “garbage in, garbage out” still applies, but now you can add: data in, confident fantasy out.
The hype is outpacing value
Even a few years in, there’s no shortage of AI hype. Each headline seems crazier than the last. So, I’ll admit that I rolled my eyes when I saw the recent headlines about Allbirds, like this one, “Shoemaker Allbirds Suddenly Says It’s An AI Company—And Stock Jumps 800%.” In the words of Gen Z, have we lost the plot? Without a clear, logical strategy, moments like this confuse consumers and weaken trust.
According to the Stanford 2026 AI Index, global AI investment more than doubled in 2025, with generative AI capturing nearly half of all private funding. But Deloitte (among others) notes a growing gap between investment size and realized value, with nearly 80% of companies struggling with AI adoption despite seven‑figure annual spend.
This gap raises another question: Is the hype actually justified?
Where’s the data proving this is worth tens, or hundreds, of millions of dollars in investment? The hype can’t climb forever, and neither can market caps, especially without underlying value. And whether AI will justify its current valuation curve remains to be seen.
Amid all the hype and speculation around an AI bubble, it’s critical that companies focus on building real, durable value, rather than chasing momentum.
The question most teams aren’t answering
For SaaS and tech companies, the challenge is real. If a shoe company can move into the AI realm, how does anyone stand out?
The answer isn’t more AI. It’s better understanding.
The companies that rise above the noise will be the ones that can answer the question few are answering well right now:
How can we prove we help?
With the endless possibilities of generative and agentic AI, the companies that rise to the top won’t be the ones adding AI because it’s popular, where every other company is, or where they think customers might want it. They’ll be the ones investing where customers actually need help.
The way forward: Innovation led by research
That kind of clarity doesn’t come from a board meeting or an offsite. It comes from deep product research: learning directly from customers, observing real workflows, and uncovering the pain points and expectations that shape adoption.
Product research allows teams to be prescriptive, not performative. It’s the difference between an AI feature that looks impressive in demos and one that customers actually use.
Why AI alone isn’t the answer
From the perspective of a SaaS company, there are two sides to AI: how it’s internally and how it shows up in their product. Embedding AI where customers want it matters, but figuring that out requires more than letting AI sift through data and spit out recommendations.
AI only amplifies whatever understanding you already have…and can hallucinate insights that feel convincing but aren’t grounded in reality.
Innovation has always mattered. That hasn’t changed. But knowing where to innovate still requires human judgment, human interaction, and thoughtful research.
The jury’s still out on how transformative AI will be. What’s clear is that hype alone won’t deliver results. At Ideba, our researchers specialize in AI-focused product research, helping SaaS companies dig in with their customers to identify meaningful use cases, uncover where AI can deliver real value, and define success metrics. To explore how product research can guide more informed, customer-led investment decisions, contact David Sly at davids@idebamarketing.com.
Kristen Higgins – Research Manager
