Artificial Intelligence is reshaping online dating, from recommending matches onwards Tinder to Help users break the ice On the hinge. Love seekers now navigate platforms where algorithms increasingly guide their decisions. If implemented well, these tools can improve the experience and lead to better matches; If implemented poorly, they risk drowning out real human connection.
At Match Group — the parent company of Tinder, Hinge, Match.com and several other dating apps — CEO Spencer Rascoff and CFO Stephen Bailey are working to accelerate the adoption of in-house AI. The company gave all of its 2,300 employees access to tools like Claude and hosted an “AI Day,” where employees trained on the technology and built their own tools as part of a competition.
“We want to become an AI-driven company as quickly as possible,” Bailey told the Observer.
A longtime Match Group executive, Billy has held leadership positions across the company since 2012, including senior vice president of financial planning and business operations and CFO of Match Group Americas.
Across the technology industry, companies are rapidly increasing spending on artificial intelligence. Executives are pushing engineers to take full advantage of these tools, fueling a phenomenon known as “tokenmaxxing.” For example, Uber reportedly exhausted its AI budget in just four months, while NVIDIA CEO Jensen Huang said he wouldn’t be surprised if a senior engineer spent the equivalent of half his salary on codes.
In Match, early use of AI came without strict limits. Now, the company is entering what Bailey calls the “ROI phase,” with a focus on efficiency. “We do not want to restrict the use of artificial intelligence, but we have to ensure that it is used in an efficient and effective way,” he said. “I have to find a way to pay for all of this.”
To manage costs, Match introduced “speed bumps,” or token limits, across the organization. A single threshold has been set for professional staff and a minimum for non-technical staff. Employees who have reached the limit should request additional codes from their managers.
Bailey said 100% of engineers now use AI to write code, with most code being generated by AI and reviewed by humans. Engineers at Tinder are producing and shipping nearly twice the amount of code they were a few quarters ago. The average engineer spends about $600 a month on AI tools, compared to about $50 for non-engineers, Bailey said. However, senior engineers can spend up to $3,000 per month.
The spending comes as Match pushes artificial intelligence to improve user experience and reduce “scrolling fatigue.” Two-thirds of Tinder’s improvements this year focused on its algorithms, while Hinge’s AI-driven matching system, which rolled out a few quarters ago, increased matches by 15 percent.
Hinge also introduced Quick Comments, a feature that helps users improve answers to profile questions like “What’s your favorite beach?” Or “What’s your favorite vacation?”
Bailey said that men, in particular, often find it difficult to write quick answers that are attractive or distinctive. The tool does not generate direct responses but encourages users to expand and improve their answers.
However, the shift to AI comes with some trade-offs. To offset rising AI costs, Match has slowed its hiring process. Bailey said the move aims to fund AI investments and re-evaluate hiring needs as the company grows.
“The roles we will need will be different once we become AI specialists than we needed even just six months ago,” he said.
However, the shift to native AI is not without challenges. As part of the company’s efforts to pay for the transformation, Match’s leadership decided to slow down the hiring process. Bailey adds that the reason is to pay for the increasing cost of AI tools and gain a better understanding of headcount needs as Match becomes an AI-enabled organization.
“The roles we will need will be different once we become AI specialists than we needed even just six months ago,” Bailey said.
