What CEOs say on stages and at events
Dylan Field from Figma and Yamini Rangan from HubSpot have been showing up frequently at conferences, interviews, and tech industry events to talk about artificial intelligence. The tone both of them strike is consistent and pretty well aligned: AI Agents are a natural evolution of the market, not an existential threat. Field tends to emphasize that Figma is ready to incorporate autonomous agents into its design ecosystem, treating the technology as a partner rather than a competitor. Rangan, on her end, highlights how HubSpot already uses intelligent automation across multiple fronts and that AI agents simply extend what the platform already does well. In both cases, the public narrative is one of confidence, control, and opportunity.
This stance makes strategic sense when you look at it from a corporate communications angle. CEOs of publicly listed companies or those that depend on investors and financial markets need to project stability. Speaking openly about vulnerabilities can trigger stock volatility, scare off business partners, and create insecurity among their own employees. So when Field and Rangan take the stage and say everything is under control, they are fulfilling an expected role. The problem starts when there is too wide a gap between what is said into the microphone and what is written in the regulatory documents these same companies are required to publish.
It is not uncommon to see leaders of major software companies downplaying competitive threats during moments of technological transformation. It has happened before with the rise of cloud computing, with the SaaS subscription model replacing perpetual licenses, and more recently with the arrival of low-code and no-code. The pattern repeats itself: while the public message is calm and collected, behind the scenes there is an intense race to adapt before the window of opportunity closes. With AI Agents, the dynamic seems to be exactly the same.
What the official documents actually say
Figma and HubSpot are required to disclose risk factors in their regulatory filings, whether in annual forms submitted to the SEC in HubSpot’s case as a publicly traded company, or in equivalent documentation for Figma’s fundraising and governance processes. And it is precisely in these documents that the conversation shifts in tone. The risks associated with autonomous AI agents are mentioned directly, using language that leaves no room for optimistic interpretations. Terms like potential disruption to the revenue model, partial replacement of core functionalities, and competitive pressure from generative AI-based solutions appear in sections that deserve attention from anyone following the industry.
In HubSpot’s case, the risk is quite specific. The platform built its empire by offering CRM, marketing automation, sales, and customer service tools. These are areas where AI Agents have already demonstrated the ability to operate autonomously, from lead qualification to sending personalized campaigns and managing support tickets. If an AI agent can execute these tasks without needing a traditional software interface, the value proposition of a platform like HubSpot starts to come into question. This does not mean the company is going to disappear tomorrow, but the per-seat and per-feature pricing model could face significant erosion as agents become more sophisticated and accessible.
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Figma, on the other hand, faces a different but equally challenging scenario. The tool has established itself as the industry standard for interface design and creative collaboration across product teams. With the evolution of design-focused AI Agents, solutions are emerging that can generate layouts, prototypes, and even complete design systems from natural language instructions. Tools that turn a text prompt into a functional interface already exist and are improving at a rapid pace. If an autonomous agent can produce in minutes what a designer takes hours to create inside Figma, the platform’s role as the central hub for creative work could be gradually diminished. The company’s documents acknowledge this possibility, albeit in careful and legalistic terms.
Contradiction as a strategy and its limits
There is a logic behind the decision by CEOs to downplay the risks of AI Agents in public. Maintaining market confidence is essential for companies that depend on recurring revenue and an active base of users and developers. Both Figma and HubSpot operate on subscription models, which means any sign of weakness can accelerate customer migration to alternatives. On top of that, both are investing heavily in AI features within their own products, and it would be counterproductive to publicly admit that the very technology they are adopting could ultimately make parts of their offerings expendable. The contradiction, in this sense, works as a kind of temporary shield.
However, this strategy has an expiration date. The tech market is made up of an attentive, curious audience that reads between the lines. Institutional investors, analysts, and even the developers and designers who use these platforms daily can access regulatory filings and compare what is in them with the official messaging. When the discrepancy becomes too obvious, the effect can be the opposite of what was intended: instead of projecting security, the minimization generates distrust. And distrust, in the SaaS ecosystem, is a fast track to churn — that metric measuring the percentage of customers who cancel their service.
The most realistic scenario is that both Figma and HubSpot are racing against the clock to reinvent themselves internally while maintaining a facade of normalcy on the outside. It is a risky bet, but not an unprecedented one. Companies like Adobe and Salesforce have gone through similar moments and managed to adapt, although the process required deep changes in product, business model, and organizational culture. The big difference now is the speed. AI Agents are evolving at a pace that makes long-term planning much more uncertain. What works today as a competitive advantage can be commoditized in a matter of months, and that puts enormous pressure on CEOs to balance transparency with perception management.
Autonomous agents and the new software value chain
To understand why the regulatory documents from Figma and HubSpot treat AI Agents with such seriousness, it is worth stepping back and looking at how the software value chain is being redesigned. For decades, the logic was relatively straightforward: a company built a tool, charged for the license or subscription, and delivered value through an interface that the user needed to learn how to operate. The competitive edge lay in the quality of that interface, the depth of features, and the ability to integrate different workflows into a single environment.
With autonomous AI agents, that equation is starting to shift in a structural way. A well-trained AI Agent can interact directly with APIs, databases, and third-party services without needing a visual interface as a middleman. This means that the value that used to live in the software’s user experience migrates to the agent’s ability to execute the task end to end. The user goes from being someone who clicks buttons and fills out forms to someone who gives instructions and reviews results. In this new model, the graphical interface loses the spotlight and the agent takes on the role of orchestrator.
For HubSpot, this is especially sensitive because a big part of its perceived value lies in the integrated user experience. The platform brings together CRM, marketing, sales, and support in a unified dashboard that makes customer relationship management easier. If an AI agent can do all of that invisibly, accessing data and executing actions behind the scenes, the need for a visual dashboard starts to shrink. And when the dashboard loses relevance, the pricing model based on access to visual features weakens along with it.
In Figma’s case, the question is even more philosophical. Interface design is, by definition, a visual and creative activity. The idea that an agent could replace a designer’s creative process is being debated intensely within the community. But the point is not necessarily about total replacement. It is enough for AI Agents to automate the more repetitive and structural steps of design — like creating wireframes, defining grids, and applying pre-configured design systems — for the amount of time spent inside Figma to drop significantly. Less time inside the tool can translate to fewer active subscriptions and, consequently, less revenue.
The role of transparency in the age of AI agents
One of the big lessons the tech industry could take from this situation involves the value of transparency. Companies that manage to communicate risks honestly — without catastrophizing but also without denial — tend to build stronger relationships with investors, customers, and developer communities. When a CEO acknowledges that a given technology represents both an opportunity and a challenge, it demonstrates strategic maturity and situational awareness. That earns respect and, paradoxically, can reinforce market confidence rather than undermine it.
The opposite is also true. When the gap between the public messaging and the official documents becomes glaring, the market starts to question not just the company’s strategy but the credibility of its leadership. And in the SaaS world, where the customer relationship is ongoing and based on periodic renewals, leadership credibility matters a lot. Enterprise customers choose platforms not just for their current functionality but for the confidence that the company will continue to evolve and deliver value in the years ahead. If that confidence is shaken by a perception of insincerity, migration to competitors can happen at an accelerated pace.
It is worth noting that the ecosystem around AI Agents is growing fast. Startups focused on autonomous agents for marketing, design, sales, and customer support are raising significant funding and shipping increasingly mature products. Platforms like Relevance AI, CrewAI, and several others are building infrastructure so that companies can deploy custom agents without relying on traditional tools. This movement creates additional competitive pressure that makes the downplay strategy even riskier for established companies like Figma and HubSpot.
What this means for the future of the software market
The situation involving Figma and HubSpot is not an isolated case. It reflects a broader pattern forming across the entire software industry. Companies that built their businesses around graphical interfaces, manual workflows, and per-user pricing models are being confronted with a reality in which AI Agents can execute complex tasks autonomously without depending on those same interfaces. This does not mean the end of these platforms, but it certainly demands a deep reassessment of how they deliver value. Software as we know it is at an inflection point, and the risks documented by these companies are a clear indicator that the market’s own protagonists know it.
Some questions that tech, design, and marketing professionals should be asking themselves right now:
- How could AI Agents impact the tools I use in my day-to-day work?
- Which tasks that currently depend on a visual interface could be automated by an autonomous agent?
- Are the platforms my company uses genuinely adapting, or are they just tacking on superficial AI features?
- What is my plan B if the main tool in my workflow loses relevance in the next few years?
For anyone working in tech, design, or digital marketing, it is worth paying attention not just to what CEOs say at events but also to what companies put on record in their official documents. That dual reading offers a much more complete picture of the real landscape. Autonomous AI agents are advancing fast, and the coming months will be decisive for understanding which companies will manage to genuinely adapt and which will remain stuck between optimistic talking points and a reality that demands structural change. At the end of the day, transparency with the market tends to be more sustainable than any narrative-control strategy 🧐.
