Ticketmaster is reshaping its technology leadership around artificial intelligence, data science and product development, with a stated focus on a problem that has long frustrated people trying to buy high-demand event tickets: bots.
Jim Freeman has joined the company as chief technology officer. He is joined by Rachel Smith, Ticketmaster’s first senior vice president of data science and machine learning, and Chuck Mortimore, its incoming senior vice president of product. Ticketmaster has also added the team from Raige.ai, an AI startup it acquired in July, to help develop AI infrastructure and broaden the company’s use of AI tools.
The personnel moves do not amount to a detailed public roadmap for new customer-facing features, nor do they establish that AI will solve bot activity on its own. They do, however, show where Ticketmaster is concentrating its technical effort: connecting data work to product decisions, improving account and ticket access, and building systems intended to identify or limit automated abuse.
A CTO mandate centered on AI
Freeman takes over the CTO role after it had been vacant since February, when Carlos Alvarez-Coch departed. Freeman most recently served as a senior adviser at Permira. His earlier experience includes serving as a vice president at Amazon, where he worked on building and launching Prime Video as well as its device and distribution partnerships.
At Ticketmaster, Freeman’s responsibilities span creating AI tools, using AI to support fan experiences and driving its adoption throughout the organization. That is a broader remit than simply adding a chatbot or a recommendation widget to a ticketing page. It suggests the company is treating AI as infrastructure and operational capability: technology that can be used across teams and embedded into the processes that support a ticketing platform.
AI infrastructure generally means the technical foundations needed to put AI systems into regular use. In practical terms, that can involve the systems that organize data, run models, connect those models to internal tools, monitor their results and make them available to employees or products. Ticketmaster has said the Raige.ai team will work on this infrastructure as well as accelerate adoption of AI tools across the business.
That distinction matters. A visible AI feature is only one possible outcome of an AI initiative. The same technology can instead operate behind the scenes, helping teams interpret patterns, prioritize work or support decisions. Ticketmaster has not specified which individual AI products consumers will see, so it would be premature to infer a particular checkout tool, fraud-control feature or personalized service from these appointments alone.
Why bot resistance is central to the changes
Ticketmaster’s new product leadership is explicitly connected to its bot problem. Mortimore, whose background includes roles at Disney and Stripe, will help guide product strategy around countering bots and making it easier for fans to access their accounts and tickets.
A bot is automated software that carries out tasks online faster and at far greater scale than an individual person can. In ticketing, bot activity can be relevant wherever demand, speed and limited inventory collide. Automated traffic can attempt to enter sales, interact with ticketing flows or create account-related pressure. The practical effect for a fan can be a more difficult path to completing routine steps, especially when interest in an event is intense.
Bot mitigation is not simply a matter of blocking every automated interaction. Platforms need to distinguish harmful activity from legitimate users and normal services while maintaining a functional experience for customers. That makes it both a security issue and a product issue. Security systems may look for suspicious patterns, while product design determines how customers recover accounts, receive tickets and move through the platform when verification or other safeguards are involved.
Mortimore’s assignment therefore sits at an important intersection. A measure that is effective at disrupting bots but makes legitimate account access more difficult is not a complete success from a customer standpoint. Equally, a frictionless flow that is easy for malicious automation to exploit leaves the platform exposed. The stated goal is not only bot combat but easier access to accounts and tickets, which recognizes those two sides of the problem.
Data science moves closer to product work
Smith arrives as Ticketmaster’s first senior vice president of data science and machine learning. She previously worked at Block, the owner of music service Tidal. Her remit includes an expanded emphasis on data science and analytics, with a particular focus on closer integration between data work and the company’s broader product development.
Data science is the practice of using data to find patterns, develop predictions or generate useful insights. Analytics is the related process of examining information to understand what is happening and support decisions. Machine learning is a branch of AI in which systems learn patterns from examples in data rather than relying exclusively on hand-written rules.
For a large ticketing operation, the relevance is straightforward even when specific implementations are not public. Decisions about a digital product depend on understanding how people use it: where account access goes wrong, which parts of a process create difficulty and how traffic behaves. Integrating data specialists with product development can make that information more directly available to the people deciding what to build or change.
But data-driven design has limits. A model or analysis can surface a pattern; it does not automatically determine the right response. Product leaders must decide whether an observed change actually improves the experience and whether it is safe, reliable and fair in the context where it is being used. The new structure places Freeman, Smith and Mortimore in roles that collectively cover those layers: technical systems, data and machine learning, and the product choices users ultimately encounter.
The Raige.ai team and Ticketmaster’s wider AI effort
Ticketmaster acquired Raige.ai in July and is now bringing its team into the organization as part of the AI push. The company says that team will help expand the use of AI tools and build out its AI infrastructure. That makes the acquisition team a notable part of the strategy rather than a separate or isolated transaction.
The company’s language emphasizes speed, tools and outcomes across several groups: fans, artists, venues and clients. Saumil Mehta, Ticketmaster’s global president, framed the initiative around the ability to use technology and data effectively.
“Reliable, secure and personalized experiences depend on how effectively we use technology and data,” Mehta said. “Jim, Rachel, Chuck and the Raige.ai team will help us move faster, build better tools and deliver better outcomes for fans, artists, venues and clients.”
Reliability, security and personalization are distinct goals, even if they can be informed by the same underlying technical investment. Reliability concerns whether systems work consistently. Security concerns protecting systems, accounts and access from misuse. Personalization refers to adapting experiences or information to a user. Ticketmaster has grouped all three under its technology and data strategy, but it has not explained how it will balance them in particular products.
That is worth keeping in view as more companies assign AI a central role in their operations. The technology’s value depends on the real-world problem being addressed, the quality and appropriate use of data, and whether the resulting system makes a task more dependable rather than merely more automated. Similar questions are increasingly shaping technology debates elsewhere, including in the games business, as explored in this look at an AI flashpoint in game development.
What the changes mean for ticket buyers right now
For now, the immediate development is organizational. Ticketmaster has named leaders, expanded its AI capability through the Raige.ai team and tied those appointments to bot mitigation, data integration and account-and-ticket access. It has not detailed a rollout schedule, named a specific new fan feature or described a particular technical method for dealing with automated attacks.
That means consumers should separate the stated direction from confirmed product changes. The direction is clear: Ticketmaster is making AI and data central to its technology leadership and connecting that work to the experience of accessing tickets. The unconfirmed part is exactly what customers will notice, when they will notice it and how much any eventual change will improve the process.
The structure of the hires nonetheless explains the company’s priorities. Freeman is tasked with organization-wide AI tools and adoption. Smith is responsible for data science, machine learning and tighter links to product development. Mortimore is assigned product strategy with an explicit bot and access focus. Alongside the Raige.ai team, those roles put the company’s core ticketing challenges at the center of its AI investment rather than treating the technology as a side project.
Whether that investment delivers better outcomes will depend on execution: systems need to be secure without becoming obstructive, data insights need to turn into useful product decisions, and efforts to resist automation need to leave legitimate fans with dependable access to their accounts and tickets. Those are the practical standards by which this AI push will be judged.
