Skip to main content

Artificial intelligence is slowly but surely revolutionizing the media industry from the inside out. A few companies are already championing this technology, but there is still room for growth.

In this article, we look at the state of AI adoption in media today, what the challenges are and how media companies can use AI tools to drive company growth.

The state of adoption of AI in the media sector

The adoption of AI in the media sector is rapidly increasing. In a 2022 global survey, 75% of publishers said that AI would be crucial to their future business success. Indeed, AI technologies offer huge promises for the industry, with the ability to revolutionize every stage of the media value chain.

But, while the use of AI in media is on the increase, the reality is that it’s only by the pioneering few. In that same survey, 50% of respondents said they had not yet adopted AI, and only 11% said that they had fully implemented one case. This reveals a disparity between the desire for future investment and the state of adoption in the present day.

Challenges to AI adoption

AI adoption varies by company size and media type, and it isn’t as simple as handing over the keys. There are several challenges preventing media businesses from embracing AI technology, the top three most widely felt being:

  • Understanding how AI tools improve workflows
  • Understanding how to integrate AI with business operations
  • A lack of relevant skills in media professionals and personnel

These challenges may reflect why digital-native media outlets and larger companies with higher budgets are more likely to adopt AI technologies than smaller companies or ones that have had to rely on legacy infrastructure.

AI developers have also been faced with challenges when developing technology for the media sector, the two most prominent being a lack of real-world data to train and test their algorithms, and the media industry’s reluctance to share its data to accelerate research. (Watch this space for forthcoming AI integrations and enhancements in Adpoint, Lineup’s media sales management system.)

The use of AI in media industry 2023

Of the media companies that have embraced AI, very few are using it to its full potential. Today, AI technologies are predominantly used in back-end processes, such as content creation and data analysis, rather than in front-end consumer-facing applications.

There is a learning curve publishers will have to face if they want to share in the future benefits of AI. While the use of analytics to analyze operations and audiences has been championed by many media companies, to move forward they need to harness the power of more sophisticated tools, like deep learning algorithms.

To achieve this, media companies must prioritize a data-first approach and implement clearly defined strategies to gather data at scale. This will benefit publishers in several ways:

  • Gathers more data on operations and audiences
  • Enables effective, AI-powered decision making
  • Improves responsiveness to market changes
  • Increases overall return on investment

This is what industry giants like Netflix are already doing, and to succeed with it, media companies need a clear roadmap that prioritizes AI initiatives.

In a 2020 survey, 58% of media professionals said that their company had no AI strategy in place. Of those that had an AI strategy, only 13% said that it included specific KPIs that measure the impact of AI tools on the organization. This feeds directly into the challenges media companies face in understanding the value of AI and how to implement its tools.

There needs to be a much higher, much quicker adoption of AI in the media industry. For publishers to drive growth and reap the rewards that AI promises, they must develop clear AI strategies that prioritize a data-first approach.

How AI can drive media company growth

When used at its full capacity, AI can transform every part of the media value chain. It will drive media company growth by allowing publishers to harness the power of data in order to deliver the right value proposition to the right audience at the right time.

Using AI for automation is the biggest way in which publishers can drive growth. Automating and optimizing manual tasks, from financial reporting to content creation, is one of the main promises of AI to the media industry, with the overarching goals being to attract and engage subscribers, cut overhead costs, and boost sales.

Here are five key areas where AI will help to drive growth in media companies:

1. Content creation

The insatiable demand for new content is difficult to keep up with, and negatively affects the productivity and creativity of media professionals. AI tools can actually assist in generating
written content, such as news articles and blog posts, freeing up time for human writers to focus on more creative tasks.

The automated synthesis of new content based on existing data analytics also means publishers can keep audiences engaged for longer with valuable content that meets their needs.

2. Personalization

Media companies are constantly vying with their competitors to gain their audience’s interest with the best content and services. AI can analyze reader data to provide personalized content recommendations and improve the overall reading experience.

It can also create a better user experience through personalization of products, services, and even value propositions. This is achieved through enhanced user profiling, allowing consumer data to be leveraged in more powerful ways.

3. Editing and proofreading

AI tools can help detect grammar and spelling errors, allowing for faster and more efficient editing and proofreading processes. AI can even be used to automate video editing, like creating shortened versions of longer videos for social media use.

Automating tedious tasks like these saves valuable resources and increases team productivity by allowing them to focus on more important areas of the business.

4. Trend analysis

AI can analyze data on reading patterns, popular topics, and social media engagement to inform publishing decisions and content strategy.

For example, AI assistants are valuable to journalists because they’re able to use trend analysis to suggest story topics that their audience is engaging with at that moment.

5. Ad targeting

AI can analyze reader data and browsing patterns to serve more relevant and targeted ads to readers at the optimum times.

This system of audience analysis gives better insights on audience needs, empowering media companies to optimize their monetization strategy by delivering ads more effectively to specific audience segments.

There’s still time for media companies to champion AI tools and drive business growth. AI is constantly evolving and creating new opportunities for publishers.

To learn more, read our articles on the challenges and benefits of AI in media, and the future of AI in publishing.

Lineup is currently working on AI integrations and enhancements in Adpoint, our media sales management system. Contact us today to book a free demo and see how we can help you develop your AI strategy.


Lineup Systems is the world's leading provider of media sales technology, representing over 6,800 media brands globally, including Gannett/USA Today, New York Times and News Corp. Amplio is Lineup's multi- channel audience monetization solution that helps media companies realize their full reader revenue potential, using data-driven intelligence to engage, nurture and monetize readers with personalized offers that increase reader revenue and reduce churn. Adpoint is Lineup's end-to-end multi-channel media advertising sales solution that helps media companies streamline operations, make better use of data, increase efficiency and boost revenue.