3-day AI design sprint fosters rapid collaboration, problem solving at news companies

By Lukas Görög

AI and Data Strategy Lead

Neue Zürcher Zeitung (NZZ)

Zurich, Switzerland

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In the fast-paced world of media and publishing, leveraging innovative technologies is crucial to staying competitive.

While Artificial Intelligence offers immense possibilities, many companies struggle with identifying the right use cases and implementing them effectively. Media houses understand AI is important and here to stay, but deploying it and pinpointing the most important applications can be tricky.

An intense and intentional focus on AI projects via design sprints can help media companies bring more use cases to the forefront.

This is where it can be useful to undergo an AI design sprint for media - a structured workshop designed to help organisations quickly develop concrete AI use cases.

What is an AI design sprint?

An AI design sprint is usually an intensive workshop specifically designed to assist companies in identifying and developing AI use cases. Targeted at management, executives, and decision-makers, the workshop aims to develop a concrete use case within three days - from ideation to technical requirements.

Benefits of AI design sprints

Media companies adopting an AI design sprint will find many benefits. These include:

• Rapid problem solving: The focused approach of an AI sprint enables participants to develop actionable solutions for specific challenges in a short time. This accelerates the implementation of AI solutions and improves efficiency.
• An opportunity to foster innovation and creativity: The workshop creates an environment that stimulates innovation and creativity. Participants are encouraged to develop new ideas and explore unconventional approaches, leading to innovative solutions.
• Customised collaboration: The workshop content is tailored to the company's specific needs. By defining specific requirements and collaborating with partners, the developed AI solutions are ensured to be technically feasible and aligned with business goals.

AI design sprint steps

The AI design sprint is comprised of four systematic steps that lead to developing a successful AI use case.

1. Ideation/opportunity mapping: Potential AI applications are identified in this step. Methods such as demand and supply side methods and creativity techniques are employed to generate innovative ideas. It's important to note AI isn't limited to generative AI but also includes projects focused on personalisation, recommendation systems, and more.
2. Framing/validation: The generated ideas are structured and assessed for feasibility and value. A structured assessment helps prioritise the most promising ideas.
3. Assessment: This phase involves a detailed analysis of the prioritised ideas. An assessment matrix, evaluation of data sources, and resources - along with an AI business model canvas - are used to further refine the ideas.
4. Requirements definition: The specific requirements for the selected use case are defined, including technical and partner requirements, collaboration, and technical fit.

Long-term planning with AI design sprints

An AI design sprint offers media and publishing companies the opportunity to achieve tangible results quickly and strategically plan long-term projects.

Through the structured approach and tailored workshop content, companies can ensure the developed AI solutions are not only innovative but also sustainable and aligned with their specific needs.

Stakeholders in media companies

For a successful AI design sprint, it is essential to involve key stakeholders from various departments within the media house.

These include:

• Newsroom: To ensure the developed AI solutions meet the editorial and content needs.
• IT: To assess the technical feasibility and integration requirements.
• AI and data team: To provide expertise in data analysis and AI technology.
• C-level executives: To align the AI strategy with the overall business goals and secure executive support.

Conclusion

The AI design sprint is a powerful tool for media and publishing companies to effectively leverage AI's benefits. By fostering intensive collaboration and following a structured approach, organisations can develop innovative, customised solutions that are strategically aligned with their long-term goals.

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About Lukas Görög

Lukas Görög is AI and data strategy lead at Neue Zürcher Zeitung (NZZ) in Zurich, Switzerland. Lukas can be reached at [email protected] or @lukas_gorog.

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