Several academic studies have ­already explored the impact of ­using ChatGPT across various professions, including law, customer support, ­programming, and creative writing. The consensus is clear – AI significantly enhances the productivity of lower-performing individuals, enabling them to accomplish more with better quality. High performers see less improvement, and in some cases, even a drop in productivity. Interestingly, early indicators suggest this productivity boost is consistent across many, if not all, white-collar disciplines.

This can be attributed to two primary factors. First, chatbots have become remarkably adept at simplifying complex tasks. Second, Gen-AI ­enhances creativity. While there’s ­ongoing debate in the scientific community about whether large language models can truly be creative, from a ­productivity standpoint, this is a moot point. After ­experiencing ChatGPT’s ­“creativity,” it’s clear that it’s quite adept at it.

Something bigger

But is the so-called AI revolution merely about increasing productivity by using ChatGPT and its counterparts in office work? Or is there something bigger at play here?

Comparing the CPU, the ­central processing unit of a ­computer, with the human brain, we find that they complement each ­other ­remarkably well. The CPU excels at rapidly executing instructions provided in code with structured data – tasks that humans find challenging.

Conversely, we humans excel at learning, a capability entirely absent in a CPU. We possess agency, intuition, creativity, and are multi-modal, meaning we process input and output through most of our senses.

The LLM sits somewhere between these extremes. It’s as fast as a CPU, but also capable of learning in the sense that it can be trained and fine-tuned. It possesses contextual understanding, a characteristic more akin to our brains than a CPU.

Low costs

The key takeaway is that we now have access to human-like intelligence at nearly zero cost. It’s more than just about chatbots. Large language ­models enable us to infuse human-like analysis, creativity, decision-making and more into workflows and processes at virtually no cost.

With this perspective, the advancements we’ve made in the past 50 years will likely pale in comparison to what we’ll achieve in the next 50 years, or even the next 15 years, for better or worse.

How can all of this play out more concretely, in one of Schibsted’s core business areas – news media?

The answer to this is that its practical implications will be vast and far-reaching. The expected transformations will challenge the very core of our traditional business models. To grasp the full breadth of AI’s potential impact, let’s first consider the fundamental business structure of the industry.

Most online businesses can be ­simplified into three core activities:

• Creation of goods
• Customer acquisition
• Distribution of goods
• From a financial perspective, these activities respectively translate into:
• Cost of goods sold
• Sales and marketing expenses
• Other operating expenses

Historically, the advent of the internet drastically reduced distribution costs in the news media, triggering substantial shifts in how content reached consumers and removing most barriers to entry into the market. Now, as we usher in the era of AI, we stand on the precipice of another profound change: a potential collapse in content creation costs. The ramifications of such a shift could be as transformative, if not more so, than the internet’s earlier influence on the business models and the broader ­industry landscape. In the short term, I predict several phenomena that are set to drive our transformation:

Democratisation of programming

Anyone can develop software using tools like ChatGPT and Replit. All it ­requires is a bit of curiosity and cou­rage. This democratisation signifies not just more efficient programming, but an increase in the number of programmers, which will further accele­rate digitalisation and innovation. As Sam Altman, CEO of OpenAI, puts it:

“I think the world is going to find out that if you can have ten times as much code at the same price, you can just use even more.”

Automation of content creation

Content with predictable production processes and performance, often format-driven, such as news summaries, listicles and interviews, will likely be generated either entirely by AI or more commonly in collaboration with journalists.

Unbundling of research and narrative

Traditionally, journalism involved ­researching facts and weaving them into a cohesive narrative. With AI, we can separate these processes. For instance, we can publish research material alongside articles, enabling readers to explore the underlying ­research through an AI-driven chat interface. Newsrooms may even have teams dedicated solely to establishing and verifying facts and other information building blocks, which are then used to automatically create content using AI.

Writing of previously unwritten stories

Many individuals possess important stories that remain untold due to a lack of competence in content production. With AI, these barriers between ­lower and higher performers are ­reduced, ­allowing many more voices to be heard.

Personalised consumption

Every individual has unique consumption preferences. With AI’s ability to transform text into various formats, we can cater to these individual needs more effectively, especially when mastering the arts of unbundling ­research and narrative, as well as the automation of content creation.

With the collapse in costs and barriers in distribution and content creation, customer acquisition becomes the primary competition area for both new and incumbent brands.

To succeed in this new paradigm, I’ve identified at least four distinct, but not mutually exclusive, strategies that news media brands can deploy.

1. Creating an addictive product

Develop a service so engaging that it captures users’ attention far more than traditional news outlets. The prime ­example is TikTok, which holds users’ attention for an average of 90 minutes daily. Achieving this is extremely, challenging, likely impossible, but the payoff is tremendous if accomplished.

2. Fostering a movement

Tap into deeper emotions such as fear and hope to capture audiences’ energy and passion, generating extraordinarily high engagement and loyalty. Fox News, for better or worse, has done this. There is no doubt that in these times of high uncertainty, audiences are yearning for hopeful narratives.

3. Nurturing a trusted brand

This is the go-to strategy for established brands. Establishing and maintaining credibility in an era of information overload should be rewarding. However, in a future hostile media landscape, no matter how strong the brand is, brands will require greater degrees of discipline, transparency, and accountability than before.

4. Building a community

In a world of increasingly personalised experiences, individuals will seek shared interactions and rewarding experiences. This insight isn’t new for news media, but most previous ­attempts to build communities encountered scaling issues as the community grew, leading to its downfall. This para­dox may be resolved if we can leverage AI to address the challenges that arise as the community expands.

Technology of the present

AI is not a technology of the future anymore; it’s very much a technology of the present. Every media organisation must actively engage with AI tools and platforms. Training your teams on platforms like ChatGPT or similar AI tools can lead to innovative storytelling techniques, streamlined content production, and a deeper understanding of audience behaviour.

On a personal level, embracing this new paradigm means integrating AI ­into your daily routine. You need to incorporate it into your life to such an extent that you automatically turn to it whenever you face challenges that require collaboration, or that can be solved faster and more effectively than you or your colleagues can do on your own. Only when it becomes an integral part of your life will you be able to fully understand it and its potential.

Rethink the pipeline

The barriers to software development are being lowered every day. Embrace this demo­cra­tisation by encouraging your teams to experiment. Host inter­nal hackathons or workshops. Foster a culture of prototyping; this not only breeds innovation but also promotes a fail-fast mentality in which learnings are quickly integrated.

With AI’s capabilities, media orga­ni­sations have the opportunity to ­rethink their content production pipeline. Centralising certain production ele­ments can help maintain ­consistency while leveraging AI can ensure content is tailored to audience preferences. Moreover, AI can assist in identifying content trends and predicting audience interests.

The transformative power of AI in the journalism industry is ­undeniable. We stand at a crossroads, facing a horizon with enormous uncertainty, limitless opportunities and inevitable challenges. The technological power that AI presents has profound implications on how we produce, distr­ibute and consume news. As AI shapes a new paradigm for humanity, it becomes imperative for the journalism industry to not just adapt but lead the way. By wholeheartedly embracing AI, media brands can redefine their narrative in this new era. This journey won’t be without pitfalls, but the ­rewards – both for the industry and society at large – are immense. The future of journalism, powered by AI, awaits.