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The use of AI in publishing creates new opportunities to drive growth and success. From data-driven customer journeys and improved ad targeting to enhanced automation, AI technologies bring many benefits to the media industry.

But the rapid advancement of artificial intelligence also comes with a unique set of obstacles. For media and AI to work effectively together and enable a future of responsible media technology, it’s important to address these drawbacks. In this article, we list the top challenges and benefits of AI that media companies should be aware of.

7 challenges of adopting AI in publishing

While AI has made significant advances in areas like natural language processing, machine learning and computer vision, there are still challenges in terms of accuracy, biases, data-quality, integrations and more that need to be addressed.

1. Ethical concerns of AI and media

There are several ethical concerns around the use of AI and media, particularly around issues of privacy, transparency, and accountability.

AI privacy concerns

AI algorithms rely on tracking consumer behavior to analyze their interests, dislikes and even their general routine. While this capability is useful to publishers, it has raised privacy concerns and been criticized as intrusive and exploitative.

Transparency of AI tools

Algorithms are flooding the online media world and play a huge role in influencing peoples’ decisions and thinking. The issue is that the transparency of AI tools and how they make decisions is murky at best.

As artificial intelligence becomes more ubiquitous, it’s crucial to make the public aware of how their information is being used. Organizations deploying AI technologies must be held accountable for ensuring that their systems function responsibly.

2. Data quality

High-quality data is essential for AI algorithms to function correctly, but media companies may struggle to gather and maintain sufficient amounts of accurate data.

Data quality can be compromised in a number of ways, from human error to technology failings, and bad data directly affects AI processes. Media companies should regularly audit their databases to ensure there are no risks of breaches or inaccuracies.

3. AI integration with existing systems

Integrating AI systems with existing workflows, processes and technology can be a challenge that requires significant resources, technical expertise and training for employees. Oftentimes, this makes the use of AI in media companies seem not worth the struggle.

To make the adoption of AI in publishing easier, existing operations must continue to run smoothly. Media sales software like Adpoint show that this is not impossible. With out-of-the-box functionality, a user-friendly UI and a fully configurable system, Adpoint integrates seamlessly with your existing infrastructure and allows publishers to make changes without the need of a technical support team.

4. AI bias and accuracy

It’s important to remember that AI technology is not neutral. AI systems can sustain and even build on existing biases in data and algorithms, leading to inaccurate or unfair results.

It’s easy for AI-driven decisions to become embedded with inaccuracies and human bias. This is because to make decisions, AI systems require training data, which is often characterized by biased human thinking. For example, research has found that training NLP models on news articles can result in them exhibiting gender stereotypes.

5. Cost of AI implementation

Implementing AI systems can be expensive and requires a significant investment in technology and personnel. With AI systems, media companies may also have to provide frequent training in order to train-up new employees or keep updated with developments in the systems. This makes it important for AI systems to offer quick ROI and reduce TCO.

6. Lack of skilled talent in media industry

According to a recent study, a key factor slowing the adoption of AI in publishing is a lack of relevant skills. This can be seen in media companies who have relied on legacy technologies for years, and now face a steep learning curve with AI.

A shortage of individuals with the skills and expertise required to develop, implement and manage AI systems leads to competition for talent and higher costs for companies. This is why Adpoint was developed with out-of-the-box functionality, allowing companies to hit the ground running without the need to invest huge amounts of resources into training.

7. The media industry’s resistance to change

Some media industry workers may be resistant to the adoption of AI due to concerns about job loss or changes to established processes and workflows.

Part of this resistance comes from a lack of understanding around how AI tools improve processes. This can be linked to the industry’s reluctance to share its data with AI developers, resulting in a lack of real-world data that demonstrates the true value of AI and media.

Media and AI: 7 benefits

Despite its challenges, the growth of AI technology has created limitless opportunities for media companies to engage their audience, tailor their services, edge-out the competition and drive growth. The benefits definitely outweigh the challenges, and adopting AI will keep you one step ahead of the curve.

Here are the top seven benefits of media and AI:

1. Improved ad targeting: By analyzing consumer data and behavior, AI creates more targeted ads that address your audience’s specific needs, offers them the best value and reaches them at the optimum time.

2. Better use of data: AI analyzes huge amounts of data and provides you with key insights that empower business decisions.

3. Competitive advantage: While AI and media has created more competition, it also equips you with the resources, insights, and tools necessary to outshine competitors.

4. Flex to current demand: AI systems adjust their behavior and products based on the needs of individual customers. This is exactly how the dynamic product catalog in our Amplio subscription management platform works, allowing you to flex to demand and anticipate customers’ needs.

5. Enhanced automation: With AI tools, you’re able to automate manual tasks and complicated workflows, from content creation to data entry to finance reporting. This drives efficiency across your entire organization and saves valuable resources.

6. Trend analysis: AI assistants and machine learning algorithms improve media organizations’ content by analyzing data on reading patterns. This extends publishers’ news coverage by suggesting topics audiences are engaging with.

7. Service innovations: AI allows publishers to break out of the traditional media mold. With powerful data and increased opportunities, media companies can restructure value chains and create new, optimized business models.

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.