Understand AI’s capabilities, communicate use cases to become a savvy media leader

By Lukas Görög

Neue Zürcher Zeitung (NZZ)

Zurich, Switzerland


In the world of media, Artificial Intelligence (AI) stands as a transformative force. As a media professional aiming to lead in AI, understanding its capabilities and integrating them into your organisation is crucial.

This is my personal guide with practical steps and easy-to-understand strategies to help you navigate and excel in the AI landscape of the media industry if you want to be an AI leader.

AI can be a powerful publishing tool, if those in the media industry take the time to learn about and harness it with intention.
AI can be a powerful publishing tool, if those in the media industry take the time to learn about and harness it with intention.

Understand AI capabilities

The first step to becoming an AI leader in a media organisation is to understand the current capabilities of AI.

Today’s AI can automate routine tasks, personalise content delivery, and analyse vast amounts of data to identify trends. Understand it and stay realistic: AI can help with many tasks in the media organisation, but implementing each of these takes time.

AI must be connected with business problems

Once you grasp what AI can do, the next step is to connect these capabilities to specific challenges or opportunities within your media organisation. For instance, if your organisation struggles with engaging readers on digital platforms, AI can be used to analyse reader behaviour and preferences to create more engaging content strategies.

Let’s call it AI “improvisation”

Becoming a real AI expert is quite hard. The AI landscape changes every day; AI today looks very different from AI tomorrow.

It is good to stay curious, but how can you plan a project with technology that changes daily? Start with a vision — a business problem — and make the parts of your AI media problem flexible so you can change parts of it quickly.

An experimental culture has never been as important as it is now. Fail quickly, and learn from it.

Design and communicate AI use cases

Being able to design AI solutions and effectively communicate their potential impacts is vital. Develop clear use cases that describe how AI can solve specific problems or improve processes.

For example, you might design an AI use case to predict which types of video content will gain the most traction on different platforms, which aids in content planning and distribution.

Scope prototypes and write product requirements documents

Before fully implementing an AI solution, start with scoping prototypes. This involves creating a small-scale version of the project to test its feasibility.

Write a clear product requirements document outling what the AI solution will do, its requirements, and how it will integrate with existing systems. For example, a prototype might involve using AI to enhance the search functionality of your digital archives.

Know key players in the market

Stay informed about the leading AI technology providers and start-ups that are influencing the media sector. Companies like Google, IBM, and smaller start-ups often release innovative AI tools that can be pivotal in addressing specific media-related challenges. Networking with these players can provide insights and potential partnerships.

Don’t build everything yourself

While developing in-house AI solutions can be tempting, it’s often more cost-effective and efficient to explore existing tools on the market. Work with and empower your AI science, data engineering, and data analytics teams to evaluate whether building or buying is the best approach for your needs.

Sometimes leveraging established AI platforms and customising them can accelerate your projects without the overhead of starting from scratch.

Experiment and iterate

The process of integrating AI into media operations should be agile. Experiment with different AI tools and approaches, and be prepared to iterate based on what works and what doesn’t.

For example, if an AI model designed to predict trending topics is not as accurate as desired, it might need more training data or a different algorithm.

Be a mentor and advocate for inclusive AI in the newsroom

In conclusion, harnessing Artificial Intelligence within the media sector requires not only a deep understanding of its capabilities but also a strategic approach to implementation. As a media professional poised to lead in AI, it is essential to align AI solutions with business challenges, foster a culture of experimentation, and remain agile in adapting to the ever-evolving AI landscape.

By effectively designing AI use cases, communicating their benefits, and collaborating with key market players, you can significantly enhance operational efficiencies and drive innovative content strategies. Additionally, mentoring colleagues and advocating for inclusive AI practices will ensure your organisation leverages AI ethically and effectively.

Embrace AI as a transformative tool in your media toolkit, and you will be well on your way to becoming an AI leader in the industry.

About Lukas Görög

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