By Joshua Reynolds
July 22, 2025
Persuasive Storytelling and
Hype Cycles: Breaking Through the White Noise
Gartner’s latest hype cycles are rolling in, and if you’re in analyst relations or tech marketing, you may be about to miss a huge storytelling opportunity. Hype cycles are typically used by B2B tech buyers and investors to understand the risks, benefits and maturity levels of the latest technologies. But for technology vendors, hype cycles can inform and inspire thought leadership narratives that help position their company as a trusted voice of reason in a sea of hype, and the ones who can help customers avoid the pitfalls and accelerate their learning curve around the latest technologies.
You may remember the five phases of a hype cycle: Innovation Trigger, Peak of Inflated Expectations, Trough of Disillusionment, Slope of Enlightenment, and Plateau of Productivity. But what’s often overlooked is that this curve isn’t just about technology maturity. It also offers insight into the emotional arc of how markets and individuals respond to new ideas.
It’s this emotional arc that makes the hype cycle such an interesting input for persuasive storytelling.
The natural flow is charted in the stages themselves. At the start, excitement builds around early breakthroughs. As exposure and speculation grow, expectations begin to outpace reality. Eventually, that gap leads to disappointment, retrenchment, and skepticism until understanding deepens and practical use cases emerge. With time, the technology stabilizes, delivers sustained value, and fades into the background of our systems and processes.
Gartner publishes more than 130 hype cycles annually, and each one is designed to help people understand the learning curves associated with each technology category. But the deeper merit of the hype cycle isn’t in seeing where technology is placed, it’s in the ability to help you reframe expectations, sidestep common traps, and shape smarter conversations. It’s not a map of technologies. It’s a map of the expectations and experiences with those technologies. One that, when used thoughtfully, becomes a communications compass for any company trying to navigate an innovation landscape that doesn’t stand still. We call this approach Hype Cycle Storytelling, and it flips the script on thought leadership. In essence, it’s about identifying where the crowd is emotionally, not just technologically, and then deciding what story to tell from there.
It’s a pattern we’ve seen play out again and again, regardless of the category. Your audience is living through these stages, trying to understand both what it is and what it will be. Your insight needs to be more than stating the basics. To simply know the stages isn’t enough because every stage calls for a different tone, a different strategy, and a different kind of leadership. That context changes everything about how you show up.
Take, for example, a technology that’s reaching unprecedented levels of hype—artificial intelligence. Gartner’s 2025 Hype Cycle for AI Technologies plots multiple AI-related technologies along its curve. It gives us a great example of the kinds of storytelling angles and techniques people can leverage when discussing any new innovation, not just AI.
1. Innovation Trigger
When a technology is in the Innovation Trigger phase, your audience may have only heard whispers of it. It’s veiled in mystery and intrigue, and people are curious—possibly even nervous about not being in the know. In this phase, the storyteller’s job is to teach. Be the visionary that helps people begin to think through why this technology is important, and what future impact it may have on their other technology investments—or their business. Offering a thoughtful take positions you as forward-looking without being reckless. It’s where companies can explore scenarios, ask what-ifs, and align themselves with the cutting edge of innovation, even if they don’t have a marketable product in this area yet. This is a great place to call out the open questions and future developments that are most worth tracking.
Consider neurosymbolic AI. It’s gaining traction as a number of high-profile technology vendors announce the integration of symbolic reasoning into their various AI platforms. These developments suggest a path toward more trustworthy and explainable AI systems. But its real-world applications are still niche, and many vendors aren’t yet ready to bet big. That makes it an ideal moment for AR professionals to ask thoughtful questions about what this could become, and what guardrails it may need to succeed.
2. Peak of Inflated Expectations
When any given innovation is at the Peak of Inflated Expectations, people tend to be in a frenzy of FOMO around it. Tech vendors are hyping this new thing up, often times way over-simplifying context and over-promising results. This new technology is the greatest thing since sliced bread. It does EVERYTHING. It’s a floor wax AND a dessert topping! That means many first-movers are rushing to embrace this new technology without really thinking it through.
The storytelling opportunity here is to be the trusted voice of reason in a sea of hype. Be the realist while everyone else is starry-eyed. You don’t need to be a contrarian, but you should be a clarifier. This is the moment to ask uncomfortable questions, highlight implementation friction, and temper expectations before the inevitable slide. Talk about the top five questions to ask yourself to avoid costly mistakes. Talk about the hidden technology risks and how to avoid them. This kind of rhetoric doesn’t kill momentum. It builds credibility. The key is not to sound dismissive, but discerning. Use this time to explore customer-centric risk narratives and flag the areas where outcomes are being exaggerated.
For example, AI agents are experiencing the massive reorientation and gravity that lots of technologies that move through this section undergo. While they’re already deployed across automation and virtual assistant roles, the rhetoric surrounding fully autonomous, reasoning-rich agents far outpaces what most enterprise environments can reliably support. Analyst relations teams can stand out here by framing a more grounded view—where these agents work well today, what’s aspirational but premature, and what it will take to get there.
3. Trough of Disillusionment
After a peak of hype comes the hangover. People actually buy this new technology and realize, “Oh, crap. This doesn’t do what it says on the label!” People who bought the technology face damage to their credibility. Vendors get swapped out. Pilots hit dead-ends. Sales cycles suddenly get a lot longer. In this phase, smart storytellers acknowledge the frustration and failures and help people recover their ROI. Explain why it’s worth it to get this new technology right. Accentuate the realistic benefits and ways to overcome the shortcomings. This is about accelerating people's learning curves. Don’t sugarcoat the failures. But don’t walk away from the value either. Storytelling here is all about lessons learned. Don’t tell success stories. Tell FAILURE stories that TURNED into successes at the end. Point to companies who figured it out, maybe slowly, maybe messily, but those who stuck with it and saw returns.
Generative AI is now sliding into disillusionment. That’s not failure. It doesn’t mean it’s overhyped or useless. It means the market is digesting the implications. After the explosive promise of 2023, real-world challenges like hallucination, governance, and misuse have tempered expectations. But the technology is still deeply embedded in content creation, automation, and customer engagement. The job now is to show how forward-thinking organizations are working through the friction, tightening use cases, and designing for responsible value creation.
4. Slope of Enlightenment
If the technology you’re discussing has reached the slope of enlightenment, that means many early adopters are already reaping the benefits while fast followers start experimenting. So be the guide for those fast followers. There are tangible, proven benefits to be realized from the technology, but some buyers may still be nervous. Celebrate the successes of first movers and use their examples to inspire and reassure more risk-averse organizations. Customer hero stories, milestones, benchmarks, and adoption roadmaps all work beautifully. This is also the phase where thought leadership becomes less about prediction and more about proven best practices.
Model distillation is a strong example of something in the slope. After years as a niche technique in academic circles, it’s now being adopted by enterprises looking to scale AI without the overhead of massive foundational models. Its technical foundation is solid, and adoption is growing rapidly as more companies seek smaller, faster, and cheaper models for production. For AR professionals, this is the moment to highlight distilled models as practical enablers of utility, not just technical curiosities.
5. Plateau of Productivity
Storytelling in the Plateau of Productivity is a lot harder. This is where most people are already using the technology in question, and even the laggards have started to adopt it. This is the phase of industry consolidation, M&A, and things that are ripe for new disruption from something in the Technology Trigger phase. So if you’re talking about a technology that’s in this phase, don’t focus on innovation. Focus on the maturation of bigger ecosystems and the consequences of industry consolidation. Unless you have some specific need to focus storytelling on technologies in this phase, it’s not typically an area that yields good innovation stories. The story here is about how old technologies are morphing into new ones.
Chatbots are the quintessential example. They’re not on this year’s hype cycle but would be on the plateau if they were charted. They’ve hit their stride in use cases, and are embedded across industries like telecom, retail, and banking. But now they’re being supplanted in many cases by AI Agents who do more than talk—they execute. For tech storytellers, the question is when do you NEED a ChatBot vs. an AI agent? What are the pros and cons? New does not always equal better. It’s all about customer, context, cost and complexity. Frame the choices that buyers have, and offer a point of view as to the ultimate longevity of ChatBots and strategies for knowing when to upgrade to Agentic AI—and when not to. Regardless, find some way to connect what’s old with what’s new, and what that means for customers.
The main takeaway is this: hype cycles aren’t just for tech buyers or investors. For those who still remember high school math, it’s like a derivative. The data points tell one story, but their trajectory charts even deeper insight. By looking at the facts behind the facts, you can predict what points any function will move towards. The best equipped, those who recognize the true merit of hype cycles, will shift tone before others even realize they should. But most of all, they’ll be ready when the next cycle begins.
Ultimately, hype cycles are about people and their felt experience with technology, more than the technology itself. They show how we, collectively, fall in love with ideas, expect too much from them, experience heartbreak, and eventually learn how to make the most of them. If you learn to read that pattern, you can lead your customers’ evolution, rather than sprint to catch up. You don’t need big news to have something smart to say. You just need perspective and authenticity. So while the rest of the industry is participating in the hype and copying all the same talking points, being the trusted voice of reason with something useful and honest to say is the best differentiator you have.
Joshua Reynolds is the Founder and CEO of Rob Roy Consulting, Inc.