The same digital infrastructure that enables sports organisations to analyse athlete performance, personalise fan experiences, and optimise commercial operations is also expanding their exposure to cyber threats. As AI-assisted software becomes embedded in how clubs, leagues, and governing bodies operate, the question for senior leaders is no longer whether to adopt these tools, but how to do so without creating security vulnerabilities that outpace the benefits.
How AI Is Reshaping Sports Operations
The pace at which AI has entered professional sport over the past three years is significant. Deloitte’s 2026 Sports Industry Outlook notes that AI is now actively reshaping back-office efficiency, scheduling, fan engagement, and media production across major leagues. The NBA has invested in AI-powered scheduling tools. The NFL has deployed AI across multiple operational functions. The Premier League is using AI to transform the fan experience. What was once the domain of well-resourced elite clubs is rapidly becoming an expectation at every level of the industry.
For senior management, this shift carries strategic weight. AI-assisted software in sports is not limited to performance analytics. It now spans ticketing systems, broadcast infrastructure, athlete health monitoring, contract and salary modelling, anti-doping compliance, and commercial partnership analysis. Each of these functions generates and processes sensitive data, and each represents a point of potential vulnerability if the underlying systems are not secured appropriately.
The Commercial Value Being Put at Risk
The scale of investment in sports AI software development reflects the commercial opportunity at stake. PwC’s Sports Industry Outlook 2026 highlights that generative AI is accelerating hyper-personalised fan experiences, predictive insights, and sponsorship modelling at scale. For organisations deriving substantial revenue from media rights, ticketing, and merchandise, the integrity of the digital systems underpinning these revenue streams is a direct business concern, not a purely technical one.
When those systems are compromised, the consequences are not abstract. They include operational disruption, reputational damage, regulatory exposure under data protection law, and loss of stakeholder confidence. Executives who treat cybersecurity as a function separate from their AI adoption strategy are, in practice, accepting risk they may not have formally approved.
The Cybersecurity Exposure Facing Sports Organisations
Sports organisations have become high-value targets for cybercriminals, and the data reflects this clearly. Research published in 2025 found that 70 per cent of sports organisations in the United Kingdom had experienced at least one cyber incident or harmful cyber activity in the previous year, compared to 32 per cent of non-sport-related businesses over the same period. The cost of individual attacks ranged from an average of £10,000 per incident up to £4 million. In Europe, a breach of the French Football Federation in 2025 exposed data on an estimated 2.3 million amateur players, illustrating that even non-elite organisations are not exempt.
The threat landscape is also shifting in character. According to IBM’s 2025 findings, one in six data breaches now involves AI-driven attacks, as adversaries use generative AI to craft more convincing phishing campaigns, remove the grammatical errors that once gave them away, and synthesise voice and visual content to impersonate athletes, sponsors, or event organisers. The same tools that sports organisations are adopting to gain a competitive advantage are being used against them.
Why AI Systems Create New Attack Surfaces
Every new system connected to a sports organisation’s infrastructure introduces a potential entry point. AI platforms used for performance tracking pull data from wearable sensors, medical records, and training management systems. Fan engagement platforms handle payment data, account credentials, and behavioural profiles at scale. Broadcast and streaming infrastructure, increasingly reliant on AI for real-time production, carries both reputational and financial exposure if disrupted.
The interconnected nature of modern sports software development means that a vulnerability in one system can cascade across an organisation’s entire digital environment. During Euro 2024, a DDoS attack linked to a Russia-affiliated group disrupted the online broadcast of Poland’s match against the Netherlands, freezing access for a large number of viewers and demonstrating that even broadcast infrastructure is a credible target. As organisations adopt more AI-assisted software, the surface area that needs to be defended grows proportionally.
What a Mature Security Posture Looks Like for Sports Organisations
Organisations that approach this challenge effectively tend to share certain characteristics. They treat cybersecurity as a board-level concern rather than an IT department matter. They conduct regular risk assessments across all digital systems, including third-party platforms and integration partners. And they invest in security infrastructure that scales alongside their AI adoption, rather than treating the two as separate workstreams.
Internationally recognised frameworks such as ISO 27001 provide a structured foundation for this work, covering information security management, access controls, incident response, and supplier risk. For organisations handling large volumes of personal data, including athlete health records and fan payment information, alignment with GDPR and equivalent regulations is not optional. The reputational and financial cost of non-compliance has risen sharply as regulators have become more active in the sports and entertainment sector.
Organisations that lack in-house expertise to build and maintain these frameworks typically benefit from engaging external support early. Whether through sports software development partners who build security considerations into the architecture from the outset, or through dedicated cybersecurity consulting services that assess existing systems and establish governance structures, the principle is consistent: security is considerably less costly to design in than to retrofit after an incident.
Practical Priorities for Senior Leaders
For executives who are not deeply technical but are accountable for the decisions that shape their organisation’s risk exposure, a small number of priorities tend to have the most material impact.
First, ensure that any new AI platform or software system undergoes a formal security assessment before deployment, not after. Third-party vendors and integration partners should be subject to the same scrutiny as internal systems, given that 30 per cent of data breaches in 2025 involved a third-party element, according to Verizon’s 2025 Data Breach Investigations Report.
Second, treat athlete and fan data as a regulated asset. The organisations that have suffered the most damaging breaches are frequently those that did not classify their data accurately or apply proportionate controls to their most sensitive records.
Third, connect AI investment decisions to security investment decisions in the same planning cycle. The organisations best positioned to realise the long-term value of AI-assisted software in sport are those that have built the security infrastructure to protect it. The two are not competing budget priorities; they are the same strategic conversation viewed from different angles.
