Key takeaways
Profitability
AI transformation
Technology investment
Workforce readiness
Content distribution
Key challenges in the media industry
As audiences migrate from traditional television toward increasingly AI-enabled and fragmented media experiences, established business models are facing pressure to adapt faster. Declining advertising revenues, rapid AI deployment, infrastructure investment, skills shortages, and more complex content distribution are collectively reshaping how media organisations create, monetise, and deliver content.
Traditional advertising revenue squeezes margins
Traditional advertising and audience monetisation are facing increasing pressure as viewing patterns shift toward streaming and legacy TV revenues weaken. STV Group’s H1 2026 revenue fell 27% to £66.1 million, while adjusted operating profit declined 12% to £5.9 million, highlighting the impact of weaker market conditions on earnings. MFE-MediaForEurope reported a 6.1% decline in first-half revenue to €2.95 billion despite improved net profit, while Disney’s planned television-business restructuring and reported job cuts further illustrate the profitability challenges facing traditional media models.
AI deployment reshapes media workflows
AI adoption is moving rapidly from experimentation toward large-scale deployment, increasing the need for modern workflows, stronger data infrastructure, and effective governance. In September 2026, only 10% of media workers qualified as “Frontier Professionals” compared with 16% across industries, although 51% of media-sector AI users said AI enabled work they could not have created a year earlier. While 79% of media organisations had invested in shared customer data platforms for generative AI, only 47% had a unified customer data foundation and 54% reported strong AI governance policies. Adoption is also widespread among professional editors, with 79% using AI and 60% using speech-to-text and transcription, increasing the need for operational readiness as AI becomes embedded in media production.
AI infrastructure raises technology investment needs
Technology modernization is accelerating as AI and cloud infrastructure become increasingly central to media operations. Akamai’s US$11.6 billion, seven-year cloud services deal with Anthropic highlights the scale of investment required to support expanding AI infrastructure. These developments are increasing the need for media organizations to modernize core infrastructure and integrate AI into production workflows.
Workforce skills become a growth constraint
Rapid AI adoption is reshaping the skills required across creative and media roles, increasing demand for qualified talent and targeted workforce development. UK creative-industry employment is projected to grow 27% by 2035, requiring 416,000 additional workers and 493,000 replacements, or around 909,000 workers in total, with 81% of projected new jobs in priority creative occupations requiring qualifications at Level 4 or above. Yet 43% of creative employers report skills shortages or gaps, 70% of employers facing skills challenges say these hinder operations or growth, and nearly 40% cannot afford staff training. These pressures make reskilling, AI training, and accessible workforce development increasingly important for sustaining capacity and growth.
Content distribution struggles with growing complexity
Content supply chains are becoming more complex as media organisations manage expanding platforms, workflows, and distribution requirements. In September 2026, 98% of 486 video-industry professionals reported using AI or machine learning, with 46% using AI daily, while 36% identified low-latency live streaming as their biggest challenge, followed by cost control at 35% and monitoring and analytics at 28%. Consumer behaviour is adding further complexity, with audiences engaging with six media types across common entertainment scenarios, up from two in 2022, increasing the need for integrated content management and distribution.
Next steps
Media organisations should prioritize profitable digital monetisation while modernising AI, cloud, data, and content-distribution infrastructure to support increasingly complex workflows. Targeted reskilling, stronger AI governance, and integrated content-management capabilities will be essential to address workforce shortages and convert technology adoption into sustainable operational and commercial value.
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