Positioning AI products: what it looks like in 2026

Products are getting easier to build

A small team can now build in a weekend what used to take months of domain-specific engineering, using the same foundation models everyone else has. Foundation Capital found that a legal ops system now looks like a claims processor, and a RevOps copilot looks like an underwriting assistant. Products have converged, and the language has followed.

At the same time, competitors started showing up from directions nobody planned for. A startup with 18 months of history enters your category. A buyer prompts ChatGPT and gets 80% of what your product does. A product manager builds an internal tool with Lovable over a weekend.

April Dunford compares this moment to the COVID-19 years. When the product, the competitors and the market all change at once, positioning that worked last year can stop fitting almost overnight.

When a new player enters a mature category, AI is a selling point

When you enter a category with an established leader, you need two things at once: the category name so the buyer can place you, and a reason to switch. AI is often that reason right now.

Attio’s homepage puts both side by side. The headline, “Welcome to agentic revenue,” tells the buyer why it’s worth a look next to Salesforce. The line under it, “Attio is the CRM that builds pipeline, advances deals, and grows accounts around the clock,” tells them which budget line it belongs in. Remove either one and the pitch stops working.

Other challengers follow the same structure. Gamma enters presentations with “Effortless AI design for presentations, websites, and more.” Decagon enters customer support as “the AI concierge for every customer.” Lemlist claims the next generation of outbound with “the AI Outbound Platform,” taking ground Outreach defined. Cursor (“your coding agent for building ambitious software”) forked VS Code and made AI-native architecture the reason to switch editors.

AI here is the answer to “why now?” It gives the buyer a reason to revisit a decision they already made.

The problem is shelf life. HubSpot, Salesforce, and Outreach have all added AI branding in the past 18 months. Once the incumbent makes the same claim, the challenger needs a new differentiator.

When the buyer isn’t shopping a category

Some products don’t fit a category the buyer already knows. There’s no budget line for “AI music tools.” No evaluation framework for “AI app builders.” The buyer isn’t comparing options on a grid. They’re describing a result they want, and they find the product that names it.

Suno (“Make any song you can imagine”) doesn’t mention AI. Lovable (“Build something Lovable”) doesn’t either. Both assume the buyer already knows AI is involved, the same way a streaming service assumes you know it runs on cloud infrastructure. The headline names the outcome.

The same holds when every competitor in a space is AI-based. If saying “AI” doesn’t separate you from anyone, it’s describing table stakes.

Market leaders use the AI label to defend their dominance

For a large established company, the bigger positioning threat right now is often the buyer deciding the category no longer matters. If CRM becomes a data layer that agents query, Salesforce’s position in CRM stops being relevant.

That’s why incumbents lead with AI even though AI isn’t what sets them apart from each other.

Salesforce saying “AI CRM” is Salesforce insisting that CRM is still the right frame. If buyers keep shopping for CRMs, the incumbent keeps winning. Dreamforce 2026’s theme was “Becoming an Agentic Enterprise,” an argument aimed at investors and analysts as much as customers.

Each incumbent tells a story about where AI is headed, and every story points back to what they already own. Microsoft says models are commoditizing and context is what matters (Microsoft owns the documents and inboxes where context lives). ServiceNow says workflows and governance are the ballgame (ServiceNow owns the workflows). HubSpot introduced “Growth Context,” arguing AI needs their customer data to work, which makes HubSpot the prerequisite rather than the thing that gets replaced.

Zendesk (“AI-powered customer service platform”) takes the same stance as Salesforce. Notion (“Where teams and agents think together”) claims AI as native to productivity. Grammarly (“Free AI Writing Assistance”) faces a different version of the threat: generalist LLMs now handle basic writing help, so Grammarly has to signal that its AI goes deeper than what ChatGPT offers out of the box.

For an established company, not mentioning AI signals it has fallen behind, and mentioning it costs almost nothing because buyers already expect it. That alone explains a lot of the AI on incumbents’ homepages.

When the move is to create a new category

Some companies don’t enter or defend an existing category. They leave it.

Gong built its name in conversation intelligence. Instead of defending that space as it filled with AI-powered call-recording startups, Gong repositioned as “#1 AI OS for Revenue Teams,” a category that didn’t exist before Gong named it. The new label redraws the competitive map around a claim only Gong is positioned to make.

Salesloft (“Create. Convert. Grow.”) made the same kind of move from the same crowded space but landed differently. Its headline doesn’t mention AI at all. The new category Salesloft is building, the predictive revenue system, isn’t an AI category, so the label doesn’t appear.

Whether AI belongs in the headline still follows the same logic. If the new category is an AI category, AI goes in the name. If it isn’t, it doesn’t.

What calling your product AI actually costs you

There’s a cost to the AI label that many teams don’t account for until they’re in the buying cycle. Forrester found that when a purchase includes AI features, the buying group roughly doubles, from about seven to fourteen. More than 60% buy some form of trial before committing, and only about a third then plan to buy the full version from the vendor whose trial they ran.

Labeling a product as AI changes who shows up to evaluate it. For a challenger entering a mature category, like Attio, that cost is unavoidable, because AI is why the buyer is reconsidering. For a company whose buyers aren’t shopping a category, like Suno or Lovable, the same label brings more people into the room without strengthening the argument.

Every position here is basically a bet

Suno bets the outcome matters more than the mechanism. Attio bets the CRM category still organizes how buyers shop. Salesforce bets its category survives as the dominant frame. Gong bets it can define and own a category that doesn’t exist yet.

Some of those bets hold for years. Others break with the next model release. The difference usually comes down to whether the position is anchored in what the product does today or in what the buyer gets out of it. Features change every quarter. Value moves more slowly.

These aren’t clean boxes. A company can sit in more than one depending on which segment it’s talking to. But they’re a starting point for the question many teams are working through: what role should AI play in how we position our product?

Whether AI belongs in your positioning depends less on how much AI is in the product and more on who you’d lose the deal to. To help teams work through that question, I took what I’ve learned from client engagements and from this research and turned it into a positioning guide for AI products. If you’d like an outside view on where your product stands, that’s the work I do in product positioning engagements.