From Fun AI Experiments to a Big-Picture Plan for News
Hey everyone, John here! For a while now, we’ve been hearing whispers and seeing cool little demos of AI in the world of news. Maybe you’ve seen an AI create a picture from text or write a short summary of a long meeting. It’s exciting stuff! Many news companies have been dipping their toes in the water, running small experiments to see what this new technology can do. It’s been a bit like a “honeymoon phase” – full of discovery and fun.
But according to a recent report from the experts at INMA, that initial phase is coming to an end. Now, news companies are facing a much bigger, trickier question: how do we go from these small, fun tests to using AI across the entire company? This next step is called “scaling,” and it’s the new mega-challenge everyone is talking about.
What Does “Scaling” AI Even Mean?
Lila: “Hold on, John. ‘Scaling’? That word makes me think of climbing a mountain or, well, fish! What does it mean when you’re talking about technology?”
John: “Haha, great question, Lila! It’s a perfect analogy. Imagine you’re a talented baker and you create one absolutely perfect, delicious cake in your home kitchen. That’s your experiment. Everyone who tries it loves it! Now, imagine you want to open a chain of 100 bakeries, and you need every single one of them to produce that same perfect cake, every single day. That’s scaling.
It’s not just about baking more cakes. You need to think about:
- A master recipe that anyone can follow (the technology and process).
- Hiring and training hundreds of bakers (the people and culture).
- Ensuring every bakery gets the right ingredients on time (the data and supply chain).
- A rulebook for quality and safety (the ethics and governance).
- And, of course, how to pay for it all (the budget!).
In the news world, scaling AI means taking a cool tool that works for one journalist or one small team and making it a reliable, safe, and useful part of everyday work for everyone in the company, from the newsroom to the marketing department.
Why Is Scaling AI So Hard for News Companies?
Making that leap from a single cake to a whole bakery chain is tough, and it’s no different for AI. The INMA report highlights that this is a huge hurdle. It’s not as simple as just buying some new software and telling everyone to use it. There are several big challenges involved.
Lila: “So it’s more than just a tech problem?”
John: “Exactly, Lila! The technology is only one piece of the puzzle. Here’s what makes it so tricky:”
- The People Problem: Change can be scary. Journalists and other staff might worry about their jobs or feel overwhelmed by new tools. A company needs to create a culture where people feel supported and excited to learn, not threatened. It’s about training, communication, and showing how AI can be a helpful assistant, not a replacement.
- The Tech Mess: Most large companies have a jumble of different technologies, some new, some very old. Getting a new AI system to talk to all the existing ones can be a technical nightmare. It’s like trying to connect a brand new smartphone to a rotary phone – they don’t speak the same language.
- The Rulebook Problem (Ethics & Governance): Journalism has a deep responsibility to be truthful, fair, and unbiased. How do we make sure the AI we use follows those same strict rules? Companies need to build a strong ethical framework before they let AI loose. This means setting clear guidelines on how to use it, how to check its work, and how to be transparent with the audience about it.
- The Money Problem: Implementing AI on a large scale isn’t cheap. It requires significant investment in technology, training, and sometimes hiring new experts. Companies have to be sure it’s worth the cost.
Avoiding the “Valley of Despair”
The journey of adopting a new technology often follows a predictable pattern. First, there’s a peak of excitement. Then, as the reality of all the hard work sinks in, motivation can plummet. The experts call this dip the “Valley of Despair.” It’s the point where the initial fun wears off, and you’re faced with the messy, complicated reality of making it all work.
It’s like deciding to get fit. The first week at the gym is exciting! But a month later, when you’re sore, tired, and not seeing huge results yet, it’s easy to want to quit. That’s the Valley of Despair. News companies are entering this phase with AI now. To get through it, they need more than just excitement; they need a solid plan.
A Blueprint for Success: The GenAI Framework
Lila: “Okay, I’m starting to see why it’s so complicated! So is there a guide or something to help them? Also, I keep hearing the term ‘GenAI.’ What is that, exactly?”
John: “You’re one step ahead of me, Lila! Yes, there is a guide, and yes, let’s clear up that term. ‘GenAI’ is short for Generative AI. Think of it as a ‘creative’ AI. It doesn’t just analyze information; it can actually generate new content, like writing a draft of an article, creating a social media post, or even making an image. It’s the type of AI that has everyone so excited.”
And to help companies use this GenAI wisely, the INMA (that’s the International News Media Association, a global club where news companies share knowledge) created a “Scaling GenAI Framework.” You can think of it as a blueprint or a recipe for success. It breaks the massive challenge down into six key areas to focus on:
- Vision & Strategy: What is our ultimate goal? How will AI help us serve our readers better and make our business stronger?
- Governance & Ethics: What are our non-negotiable rules for using AI responsibly? How do we maintain trust with our audience?
- People & Culture: How do we prepare our team for this change? What training and support do they need?
- Technology & Data: What are the right tools for us? How do we manage our data securely and effectively?
- Process & Workflow: How will our daily routines and tasks change? How can we make work more efficient and creative with AI’s help?
- Partnerships & Ecosystem: Who can we work with to help us on this journey? (e.g., tech companies, universities).
By thinking through each of these areas, a news company can build a sturdy bridge over that “Valley of Despair” instead of falling into it.
A Final Thought from John and Lila
John: As someone who’s watched technology reshape journalism for years, this feels like a truly pivotal moment. The INMA report makes it clear that the challenge isn’t just about finding a cool AI tool. The real work is in weaving it into the very fabric of a news organization—its people, its principles, and its purpose. It requires careful thought and a commitment to getting it right.
Lila: From my perspective as a newcomer to all this, it’s actually really comforting. Hearing that experts are creating detailed plans and ethical rulebooks makes the idea of AI in news less scary. It shows that the goal is to use it as a helpful tool to support journalists, not replace them, and that’s a future of news I can be excited about!
This article is based on the following original source, summarized from the author’s perspective:
News companies need to talk about AI adoption,
scaling