As online discovery moves from internet searches to AI answers, it’s redefining how companies market, communicate, and sell. It’s the beginning of a fundamental shift in how brands and consumers interact.
McKinsey reports that half of consumers already use AI systems like ChatGPT and Perplexity for discovery, and predicts that $750 billion in consumer spending will flow through AI search by 2028. Suddenly, optimizing for keywords and search rankings isn’t enough. Brands need a plan for AI answers too. Without one, they stand to lose 20% to 50% of their web traffic.
But optimizing for AI answers is no easy task. McKinsey estimates that content on a brand’s website represents just 5% to 10% of the sources AI engines reference. The rest comes from places brands can’t fully control like Reddit threads, news coverage, Wikipedia entries, or YouTube videos.
James Cadwallader and Dylan Babbs saw the shift early. As ChatGPT, Perplexity, and other AI chatbots gained traction, they noticed companies scrambling to find a new playbook to optimize for AI answers. So they launched Profound to track how AI models surface brand mentions and optimize for success. The LIFT Labs portfolio company runs 15 million+ prompts per day across major AI engines, analyzing how models reference brands, where they pull information from, and if responses are positive, neutral, or negative. A lightweight script on client websites tracks when AI crawlers visit and which pages or content formats they favor. Profound even supplements its data by licensing conversations from hundreds of millions of prompts per month from millions of active users.
Combining response analysis, crawler behavior, and real search intent produces a detailed visibility map showing how AI engines perceive and prioritize a brand compared to competitors.
From Analysis to Action with Profound’s AI Agents
Insights alone aren’t enough, and can leave brands with plenty of legwork to optimize for AI searches. So Profound built AI agents that act on their recommendations. Work that might have taken weeks can now be finished in days or hours.
“This turns us from an analytics platform into a workbench,” said Babbs. “The agents can write content, publish it, even update site code. The tech now exists to automate workflows end-to-end.”
Profound also delivers a dashboard allowing users to run specific searches to determine how search results change by demographic data or how AI systems rank the trustworthiness of their websites. For example, Profound might show a car manufacturer data about the best SUVs in the industry and show a wireless phone provider data about the best coverage in a particular region. Profound even analyzes return on investment data based on traffic and web conversions.
How Profound Became a Go-To Tool for Enterprise Marketers
Profound’s timing and technology has fueled extraordinary traction. Founded in 2024, the company closed a $35 million Series B by August 2025 led by Sequoia Capital, bringing Profound’s total funding to $58.5 million. Today, it serves enterprise clients like Figma, Ramp, MongoDB, Plaid, Clay, Chime, Indeed, U.S. Bank, DocuSign, HeyGen, and Wayfair.
Smaller teams opt for Profound’s self-serve plan to track visibility trends.
Client results have been impressive. For example, finance platform Ramp grew AI visibility 7x, doubled citations vs. all previous content, and rose from the 19th to 8th most visible fintech brand in the Accounts Payable sector platform on AI engines. Cybersecurity firm One Identity increased visibility 30% in a single quarter and doubled its share of non-branded citations.
Overall, Profound leaders say that by Day 80 of using the platform, clients get a 97% increase in citation growth from AI engines.
How AI Will Reshape Marketing Beyond Discovery
Babbs believes AI models will soon become full commerce environments where product discovery, recommendations, and transactions happen inside a single interface.
As AI takes over the full funnel, attribution could break. Brands won’t see the behavioral data they’ve relied on for decades. Profound is betting the coming paradigm shift creates demand for a new measurement layer revealing how models perceive products, rank trustworthiness, and make decisions.
Longer term, Babbs envisions Profound expanding beyond answer-engine optimization. Its measurement-plus-agent model could also automate traditional SEO, boost product marketing, or improve social media performance. He sees Profound data helping marketers optimize every domain where content, visibility, and decision-making intersect.
“We don’t have to stop at answer engines,” he said. “The same system can apply across marketing. We want to become the AI-native layer for marketers.”
