Listicle Report Tech

10 Tips for media to get into AI

Key strategies for publishers to leverage AI and advance their newsrooms

Editor’s note: This article originally appeared in the 2021 report on AI and Machine Learning in emerging media markets which was jointly prepared by International Media Support, The Fix, and El Clip. You can read the full report here.

There are a lot of conversations on how publishers can leverage AI to improve their processes, free up their staff from mundane tasks and deliver better journalism. While useful in practice, these discussions often lack clear next steps and a roadmap of moving from the idea to implementation. Here are 10 tips of how your team can get into AI (and stay there):

1. Set a 5-year vision

A five-year plan will help you set the right goals and path to implement the vision. Major change comes from top management – not some obscure lab or engineering team. Fully embracing AI adoption can get people on board and reduce friction.

But it’s hard to break old habits. Training takes time. Introduce change gradually, but persistently. Make results visible. The company you want to see will slowly take shape.

2. Assign a single, responsible team leader

Tackling machine learning projects can start from any corner of the organisation. But without an identifiable point of contact – visible and accountable – it is easy to lose focus. A single responsible person, outside the current organisation structure, should work across different areas (newsroom, sales, product etc.) and make them feel part of the process of building new digital skills. Moreover, the responsible person can propose, analyse and prioritise opportunities with the greatest impact for the entire organisation.

More from The Fix: The next disruption: AI and Machine Learning in emerging market newsrooms

3. Form an interdisciplinary team with a single point of contact

AI is not just an engineering issue. The goal is to solve problems scattered all over – in engineering, design, sales and editorial. You cannot realise a 5-year vision working in silos.

An interdisciplinary team should build foundational blocks for future projects – start with simple ones like indexing archives, connecting systems through APIs. This will make starting new projects easier and set realistic expectations on time and resources needed.


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4. Find low hanging fruit and aim for immediate results

Start with a project you know you can handle that will deliver an immediate impact. It will help set the tone and make people realise integrating AI into the workflow is not rocket science. You will also start adding valuable know-how into the company that you can later use for more complex projects.

5. Set realistic timeframes (but finish the 1st project in 3 months)

You want to avoid excessive time dedicated to meetings and focus on actual planning and executing your vision. Your first project is all about getting people on board. A quick win will boost confidence and results will inspire people to tackle new problems.

More from The Fix: Artificial intelligence in journalism: Key insights and new solutions

6. Use specific metrics (e.g., KPIs) to track progress

Key Performance Indicators (KPIs) help manage performance and evaluate the success of a particular project or the organisation overall. Actual KPIs vary between organisations. It can be pageviews, new subscribers, or a million other metrics. What is consistent is that they can be used to drive towards specific goals. Measure everything and align your AI projects to those metrics.

7. Validate ideas early and often by using short projectsprints

Many ideas don’t survive real world testing. Avoid projects that require huge amounts of time or headcount. Break projects into short sprints or repeatable time-boxed activities that deliver real outcomes at regular intervals (and measure the impact!). If you want to automate a process, start with the simplest piece and expand to more challenging parts. Change direction if it fails. “Trial and error” is your best friend.

8. Use projects to educate and train your staff in AI, ML and DP, with yearly goals that are clear to everyone involved

You can’t deliver a 5-year vision unless the whole organisation is aligned. But people won’t support things they don’t understand (an issue for any new technology). Fight fear of job losses with solutions that remove friction and free up time for people to focus on what they do best (and win you allies). It will also open eyes to new possibilities.

9. Collaborate with fellow media to push the boundaries

Many of the problems and limitations you face are not unique to your organisation. Work together with fellow media to overcome limitations and reach a higher standard sooner. Use international workshops and resources and embrace organisations helping push new technologies into the newsroom. It will help implement your vision faster and better.

10. Use vendor, open-source solutions to implement AI faster

No need to reinvent the wheel. Many external players offer solutions to integrate AI into your organisation. Be wise to integrate solutions you can measure against your KPIs. Make sure people see the benefits of AI in their daily work. Provide updates on results of vendor solutions. Highlight benefits for customers or competitive advantages gained. This will encourage the use of new technologies and set the right mindset for your team.

More from The Fix: Artificial Intelligence in the editor’s seat

Photo by Michael Dziedzic on Unsplash


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