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The AI Perception-Reality Gap

Artificial Intelligence, HubSpot POV
June 1, 2026/by
The AI Perception-Reality Gap There’s a widening gap between what the market says about AI and what we actually hear from customers. The media, the VCs, the AI labs, and influencers have all talked about AI replacing humans, ripping out trusted software, and token-maxxing as ends worth pursuing. But the leaders running real businesses are increasingly asking the right questions. How do I make my people better with AI? Which systems can I trust? How can I measure the ROI of this spend? We hear these questions every day. After three and a half years of building, shipping, and watching many of our growing customers put AI to work, the AI perspectives we are most certain of at HubSpot are the things almost no one else is saying out loud. Here are six of them. AI activity is not AI outcomes. The industry has confused motion for progress. Drafting emails, generating summaries, doing research. These are activities that AI has made much easier. They are useful capabilities, and we ship them at HubSpot. But activity is the input, not the result. Activity without outcomes is theater. The companies winning with AI are the ones working backwards from a business problem, not forward from a model demo. For example, customers using Customer Agent are responding to tickets 25% faster, while those using Prospecting Agent are generating 76% more leads. This is why we moved Customer Agent and Prospecting Agent to outcome-based pricing in April. AI outcomes are what matter....
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AI search behavior: What it means for your marketing strategy in 2026

Artificial Intelligence
June 1, 2026/by
AI search behavior: What it means for your marketing strategy in 2026 AI search behavior may be causing a dip in your traffic, but it’s also sending higher-quality leads your way. For marketers, that second part is a massive win. AI search was the number one predictor of purchase intent for CRM software buyers, according to HubSpot’s State of AEO 2026 report. And there are more findings from the report that every go-to-market team needs to know. In this article, I’ll share the latest findings on AI search behavior, its impact on brand discovery, an answer engine optimization (AEO) strategy you can implement today, and much more. Table of Contents What is AI search behavior, and why should marketers care? How AI Search Behavior Creates New High-Intent Discovery Paths The Impact of AI Search on Brand Discovery How to Plan Content Around AI Search Behaviors Why Track AI-Driven Search Engines and How to Start How AI Model Updates Impact Search Optimization What AI Search Behavior Means for Sales and Service An AEO Playbook You Can Run Today Frequently Asked Questions About AI Search Behavior What is AI search behavior, and why should marketers care? AI search behavior refers to the actions people take when they’re seeking answers using artificial intelligence, whether that’s asking ChatGPT or consulting Google AI Overviews. In the past, traditional search consisted of a user entering keywords into a search engine like Google, getting...
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Introducing the HubSpot Agent CLI

AI Transformation, Artificial Intelligence
May 27, 2026/by
Introducing the HubSpot Agent CLI A few weeks ago, I wrote about our vision for the agent era: agents should be able to run on HubSpot, and to run HubSpot. I want to go a level deeper on what “run HubSpot” actually means, and our latest step in bringing this vision to life. Businesses aren’t just sending employees into HubSpot to do work. They’re sending agents. And those agents need to be able to act as effectively as possible on your behalf, wherever they’re operating. That last part is important. An agent isn’t always running in one place, on one infrastructure. With AI Connectors, HubSpot context and actions are already available in Claude, ChatGPT, and other environments where teams work. Now, we’re adding another agent infrastructure: Command Line Interface (CLI). Introducing the HubSpot Agent CLI The HubSpot Agent CLI brings HubSpot’s data and intelligence into the environments where GTM and ops teams are composing their own workflows – Codex, Claude Cowork, and Claude Code – and allows agents to automate repetitive, bulk, and scheduled work. The simplest way to think about it: take the questions you’ve been asking or the tasks you’ve been completing repeatedly in chat, and automate them. Build automations in Codex or schedule them in Cowork, and the work happens on its own before you even get to your desk. It’s built on the same foundation as our public APIs and MCP server that already power our AI Connectors — and it’s designed to complement them,...
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Our Vision for Building an Open Ecosystem for the Agent Era

ai-hidden, Artificial Intelligence
May 5, 2026/by
Our Vision for Building an Open Ecosystem for the Agent Era For years, HubSpot invested in making our platform the best place for marketing, sales, and service teams to do their work. With AI, we’ve been building it to do the work for them – through agents that qualify leads, resolve tickets, save deals, and drive outcomes across the business. That’s why we call HubSpot an agentic customer platform. But agents don’t click through dashboards or navigate interfaces; they call APIs, read structured outputs, and take action. Software built for humans has to evolve to be genuinely accessible to agents, too. Access alone isn’t enough, though. Agents also need substance. An agent reasoning over raw records has no way to know what’s normal for a specific business, or what’s worked for hundreds of thousands of companies like it. As we recently wrote, the real AI race isn’t about models or data; it’s about context. That conviction shapes everything we build. It’s why we were among the first to ship an MCP server, and why we’ve kept expanding what agents can read, write, and act on since. That was only the beginning. The vision we are working toward is bigger: Agents can run on HubSpot. And agents can run HubSpot. Running on HubSpot means any agent – ours or anyone else’s – can plug into HubSpot’s data, context, and capabilities as a building block. Running HubSpot means agents can operate the platform end-to-end through our APIs, MCP server, CLI, and whatever...
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The Real AI Race Isn’t About Models or Data. It’s About Context.

ai-hidden, Artificial Intelligence
April 9, 2026/by
The Real AI Race Isn't About Models or Data. It's About Context. Every company I talk to right now is convinced they have an AI problem. Their AI writes emails nobody responds to. It researches accounts and surfaces leads the sales team already closed six months ago. Finger-numbing sessions copying and pasting between tools generate content that sounds exactly like what every competitor is publishing. Leaders invest in tool after tool, run training session after training session, and still find themselves staring at the same question: why isn’t AI actually moving the needle? Here’s what you’re not being told. The problem is not your model. The problem is not your data. The problem is context: the specific knowledge of your business, your customers and what they need right now, and how your team actually works. It is also the hardest problem to solve, and the one the industry has been slowest to address. Context is the Infrastructure, Not the Feature Here is the distinction that I think is getting lost. Data is what happened. Context provides meaning around real events, what they mean, why they matter, and what to do about it. Context is not a feature; it is necessary infrastructure. Your CRM has a record that a deal closed eighteen months ago. That is data. Context is knowing the deal closed because your champion switched companies, the pricing had to be adjusted three times before it landed, and that customer now refers several new deals a year and hates...
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Knowing About AI Isn’t Enough. Here’s How to Actually Use It.

ai-hidden, Artificial Intelligence
April 8, 2026/by
Knowing About AI Isn't Enough. Here's How to Actually Use It. Maybe you’ve opened ChatGPT a handful of times, gotten subpar results, and moved on. Maybe you’ve sat through an AI training or two and thought, “Cool, but how does this actually apply to my job?” Or maybe you’ve bookmarked a dozen AI tools you saw recommended on LinkedIn and haven’t tried a single one. You’re not alone. That gap between knowing AI and using AI is where many of us are right now. And it doesn’t help that everyone’s telling you to use it. I know because this is pretty much my job: I manage a writing team on the HubSpot Blog, and a big part of my work is enabling them with AI. Not in the abstract, inspirational keynote sense, but in the here’s how to get your actual work done better sense. What I’ve learned is that the problem is almost never motivation. People want to learn. It’s that information about AI is everywhere, but genuine enablement — what actually changes how you work — is surprisingly rare. That’s what this post is about. In this guide, I’ll share a practical framework for integrating AI into your work in a way that advances your skills, impact, and career. Table of Contents Why Being AI-Enabled Helps Your Career Why is AI so hard to adopt? What does AI enablement look like? How Teams Can Move From AI Experimentation to Execution Where...
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Where to Start with AI: A Practical Guide for GTM Teams

Artificial Intelligence
March 4, 2026/by
Where to Start with AI: A Practical Guide for GTM Teams Over the past year, I‘ve had hundreds of conversations with business leaders about AI. The pattern is always the same. They’re not short on tools or ambition. They're struggling with where to get started and how to get value. The pressure to adopt AI is real. But pressure without direction leads to experiments that don‘t stick, tools that don’t get used, and teams that grow more skeptical. Why? Because AI output didn't lead to actual outcomes. Here‘s what I’ve learned from watching teams that succeed with AI: they don't start with AI. They start with a problem. A specific, painful, time-consuming part of their work that they want to fix. Then, they find the right AI use case to achieve that goal. As they see results, their confidence grows, and they explore other AI capabilities – again, tied to a clear goal. That‘s the approach I want to share. Not an exhaustive list of everything AI can do, but a practical guide to where marketing, sales, and service teams can get started and see real value with AI. For transparency, we’ve organized use cases by how ready the technology is today. At HubSpot, we are building and improving these capabilities every day. Let’s start with simple definitions: Established: These are use cases where AI works reliably. Implementation is straightforward. Results are repeatable. If you're wondering where to start, it’s here! Emerging: These use cases are...
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Claude vs. ChatGPT: A marketer’s guide to choosing AI

Artificial Intelligence
March 2, 2026/by
Claude vs. ChatGPT: A marketer’s guide to choosing AI “What’s better: Claude or ChatGPT?” is the mind-boggling question every marketer is asking right now. As AI tools become essential to content workflows, understanding the differences between Claude and ChatGPT for marketing can mean the difference between a streamlined operation and a frustrating bottleneck. In my opinion, both tools have legitimate strengths. ChatGPT – which you can train on your specific needs – excels at rapid ideation, email copy, and social content. However, Claude shines at long-form editing, brand voice consistency, and handling large context windows. The question isn't really “is Claude better than ChatGPT?” It’s about which LLM you should use for each specific task. In this guide, I’ll break down everything you need to know, including: Claude AI versus ChatGPT for writing ChatGPT versus Claude for email Claude versus ChatGPT pricing Claude versus ChatGPT integrations with your existing stack Plus, my (very smart) colleagues have tested writing blog posts with ChatGPT, explored ChatGPT for SEO, evaluated ChatGPT alternatives, including Claude, and even used both for AI-powered spreadsheet tasks. Now I’m putting in my two cents, sharing what I’ve learned so you can make confident decisions about ChatGPT versus Claude for coding, content creation, and everything in between. Let’s get into the good stuff. Table of contents: Claude vs. ChatGPT: Which is better? Which is better for common marketing workflows, Claude or ChatGPT? Claude vs. ChatGPT for SEO briefs...
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AI marketing predictions that will shape 2026

Artificial Intelligence
March 2, 2026/by
AI marketing predictions that will shape 2026 Marketing is set for its most transformative year in decades, according to major AI predictions for 2026. Currently, marketers struggle with fragmented customer journeys, declining attention spans, rising acquisition costs, and failed campaigns. Using AI in marketing will redefine how brands connect with consumers by using real-time data processing and predictive analytics. According to the HubSpot 2026 State of Marketing report, over 64% of organizations currently use AI. The growth of AI in marketing is predicted to increase drastically over the next year, given the rise of AI-driven content, AI agents, hyperpersonalized campaigns, and more. Marketers will need to evolve to take on more strategic and analytical roles while delegating routine tasks to AI tools. This article will cover the top AI predictions for 2026 and the AI marketing predictions beyond 2026. For teams looking to stay ahead and implement AI, the HubSpot AI Agent Playbook provides step-by-step frameworks for automating marketing workflows and deploying AI agents across campaigns. Table of Contents AI Marketing Predictions for 2026 How Marketers Should Prepare for 2026 AI Predictions AI Predictions Beyond 2026 Frequently Asked Questions About AI Predictions Current AI Capabilities Future AI Capabilities Basic AI summaries AI search engine-powered conversational answers ...
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Answer engine optimization trends in 2026: How AEO is transforming the landscape

ai-hidden, Artificial Intelligence
January 7, 2026/by
Answer engine optimization trends in 2026: How AEO is transforming the landscape Emerging trends in answer engine optimization are reshaping how brands earn visibility, trust, and demand in AI-powered search. Answer engines like ChatGPT, Google AI Overviews, Perplexity, and Gemini now deliver fully synthesized answers directly to users, compressing the traditional customer journey. According to HubSpot's Consumer Trends Report, 72% of consumers plan to use AI-powered search for shopping more frequently. If your content isn’t structured for or easily parsed by answer engines, your brand won’t appear. Competitors will. Or worse, inaccurate narratives about your company, pulled from sources you don’t associate with, may surface prominently in AI-driven results. That’s a visibility risk no business can afford. In this post, I break down the emerging trends in answer engine optimization, why they matter for revenue, and how to integrate AEO with traditional SEO strategies to drive full-funnel growth. Table of Contents Why Emerging Trends in Answer Engine Optimization Matter Now 6 Emerging Trends in Answer Engine Optimization You Should Act On How to Integrate AEO Strategies With SEO for Full-Funnel Growth How to Measure AEO Beyond Rankings and Clicks Frequently Asked Questions About Emerging Trends in Answer Engine Optimization Why Emerging Trends in Answer Engine Optimization Matter Now Answer engine optimization matters because search behavior is fundamentally changing: AI Overviews reduce organic clicks but increase the value of citations, and conversational assistants are becoming preferred search options for consumers. HubSpot's Consumer...
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