AI maturity in media, leisure and entertainment

Artificial intelligence and unstructured data is transforming the media, leisure and entertainment sector, unlocking new opportunities for personalised content creation, user engagement and operational efficiency. Due to the nature of the sector, organisations interact with unstructured data such as video, audio, images and social media daily, making it a natural fit for AI applications. However, despite consistent use of unstructured data, many seem to overlook the strategic impact it can have on organisational success.

Findings are based on research conducted by Iron Mountain alongside independent market research specialist Vanson Bourne. Data in this report is based on 200 IT and data decision-makers in the media, leisure and entertainment sector, who have knowledge or involvement in their AI strategy.

Three key takeaways:

• The media, leisure and entertainment sector have more organisations later in their AI journey than the surveyed average (50% vs a global average of 40%)
• Daily interactions with unstructured data mean that the average portion of AI use cases leveraging unstructured data is higher than other sectors (63% vs an average of 60%), with many of the foundational aspects of preparation already in place
  • In fact, 34% report being highly effective at managing unstructured data at scale, and 33% say they’ve already made significant progress in preparing high-quality unstructured data for AI use
• Despite the widespread use of AI and unstructured data, fewer than average say that unstructured data is extremely important to the success of their AI strategy (42% vs an average of 49%)

Iron Mountain commissioned independent market research specialist Vanson Bourne to conduct this piece of research. The study included surveying 1,400 IT and data decision makers who have knowledge of or responsibility for AI strategy at their organisation. Respondents’ organisations had to have 250 employees or more across the following countries: US, UK, France, Germany, India and Australia.

Organisations are from several public and private sectors but there was a strong focus in banking and financial services, insurance, healthcare and life sciences, media and entertainment, the public sector (excluding healthcare) and energy. This summary is based on 200 decision-makers in the media, leisure and entertainment sector.

Current AI adoption

The media, leisure and entertainment sector is more advanced in their AI adoption journey when compared to the global average. In fact, half of the organisations within this sector fell into the advanced AI maturity group, while only 17% reported being in the early AI maturity group.

These higher AI maturity levels likely stem from being part of a highly competitive and fast-paced sector where personalisation, content curation and user engagement are critical to success. Generative AI can play a key role here by enabling organisations to rapidly produce new and engaging content at scale, whether that’s personalised product recommendations, dynamic media assets or real-time customer communications. In fact, research from Statista in 2024, reports that almost two-thirds of businesses who use generative AI within their organisation can increase the speed of content and media production.

The customer is clearly at the center of the sector and organisations are using AI to their advantage. Our research found that more than the average are using AI for customer service areas (61% vs an average of 53%) or customer-facing products and solutions (57% vs a global average 47%). Many organisations in the sector are choosing to adopt emerging technologies to stay relevant and meet evolving customer expectations; an area where AI can demonstrate clear value.

In addition to customer-centric areas, AI is more commonly used within legal areas in the media, leisure, and entertainment sectors than in other industries (28% vs. 21% globally). This sector frequently manages complex legal issues such as copyright, licensing, and intellectual property, areas where AI can streamline processes. However, the increased use of AI in legal functions may also stem from a wider organisational confidence in applying AI across multiple domains. This reflects a cycle of trust and familiarity with AI tools: the more they use AI effectively in one area, the more likely they are to explore its potential elsewhere. As legal considerations within the industry grow more complex with global content distribution and emerging digital platforms, AI will remain a strategic asset for maintaining legal precision and operational scalability.

Higher AI adoption also reflects the sector’s broader demand for operational efficiency, risk mitigation and scalability, especially when content is rapidly shared, created and monetised across platforms. In line with this, 59% of sector respondents cited cost reduction as a key use case for AI, reinforcing its role as a practical enabler.

Continuing this theme, our research finds that the media, leisure and entertainment sector believe sourcing and preparing relevant and high-quality data for AI training and analysis is the best way to accelerate adoption and increase the value of AI initiatives. This is more than the surveyed average (52% in the sector, 48% globally) and suggests that organisations in the sector understand the foundational role data quality plays in unlocking AI’s full potential. Given the heavy reliance on unstructured, content-rich data formats the sector interacts with daily, it’s even more important and highlights the mindset that investment in data readiness is essential to driving meaningful and scalable AI outcomes.

When it comes to business outcomes, organizations in this sector are focused on driving revenue growth (49%), employee productivity (48%), improving process efficiency (47%), and enhancing customer acquisition and retention (47%). Interestingly, gaining a competitive advantage is less of a stated priority in this sector (39% vs. a global average of 51%), suggesting a more inward focus on operational effectiveness and customer value over market differentiation.