A few years ago, I decided to return to analogue photography after a 20-year digital hiatus. What struck me wasn’t just rediscovering this craft but how I learned the basic skills of analogue photography — from picking the right camera to developing and printing film at home — entirely without speaking to another human being.

YouTube taught me film developing techniques. ChatGPT advised me on vintage cameras, recommendations for lenses, and repair tips for cameras. When a recent acquisition from Japan produced foggy images, I uploaded photos to an AI system, received instant diagnosis and detailed repair instructions — all without exchanging a single word with another person.

The AI had become my photography buddy: always available, never judgmental, endlessly knowledgeable.

And I realised: This is the future of how people will seek expertise, guidance, and even companionship.

From high street to AI companion

This behavioural change mirrors what happened to retail over the past two decades. People stopped going to the high street; they moved online.

More crucially, they stopped asking shop assistants for advice and did their own research instead. The helpful salesperson who knew products inside and out was replaced by Amazon reviews, comparison Web sites, and online forums.

Now, people are rapidly replacing human advisors with AI companions across every domain. They are turning to ChatGPT for life advice, career guidance, and relationship counselling. They are using AI for everything from learning new skills to making purchasing decisions.

The pattern is clear: When people need expertise or guidance, they increasingly prefer the convenience and accessibility of AI over human interaction. AI is increasingly becoming a trusted guide — not simply a tool for information retrieval.

This shift represents a fundamental change in how people consume expertise. Instead of seeking one-off information, they want ongoing dialogue. Instead of static content, they crave interactive guidance. Instead of impersonal sources, they want something that feels like a trusted advisor — a buddy.

Journalism’s hidden advantage

For journalism, this isn’t necessarily a threat; it’s one of the biggest strategic opportunities seen in decades. And journalism has been preparing for this transition for two decades without knowing it.

Think about your audience’s current relationship with your news organisation. Do they call reporters for opinions? Do they visit newsrooms for conversations? Do they interact directly with journalists?

Only in rare exceptions.

One back channel has always been the letters to the editor, but these are mainly a one-way communication. People consume the journalistic expertise, opinion, or advice through digital platforms, apps, and Web sites — completely mediated experiences with no human contact required.

Readers are already comfortable having a relationship with a news brand without human interaction. They trust the editorial judgment, rely on the analysis, and turn to the media brand for understanding complex issues. Actually, news media has been building the foundation of an AI buddy relationship for years.

While other industries panic about losing human connection, news organisations can leverage existing digital relationships. The audience doesn’t expect to talk to the newsroom. They expect the newsroom to talk to them intelligently, contextually, and helpfully.

The true power of this relationship lies in the quality of journalism’s accumulated reporting — a human-experienced data set we will return to later.

Beyond “what happened” to “what should I do”

Traditional journalism answers “what happened.” AI buddies answer “what should I do about it.”

Editorial strategies need to evolve from information delivery to guidance provision. This means stories should anticipate and answer the follow-up questions readers will inevitably have, while content must clearly articulate implications for readers’ lives rather than leaving them to draw their own conclusions.

Analysis should include actionable insights that help people make decisions, not just explanations of events.

Consider how a story about rising interest rates transforms in this new paradigm. Instead of merely reporting the Federal Reserve’s decision and expert reactions, the buddy-oriented approach provides guidance on mortgage timing, refinancing decisions, and investment implications tailored to specific audience segments.

The story becomes a consultation rather than just a report.

From articles to conversations

AI buddies don’t deliver monologues; they engage in dialogue. The strategic shift required isn’t technical. Large-language models can already restructure existing content conversationally and create follow-up responses.

But here’s the crucial limitation: The AI can only work with the content that is available as input. If your current coverage lacks actionable insights, the AI buddy will lack actionable insights. If the journalism doesn’t address reader implications, neither will the conversational interface. If there is purely descriptive reporting without guidance or context, an AI buddy will be equally unhelpful when people ask, “What should I do about this?”

The real challenge is editorial: deciding what conversations you want to have with your audience, what guidance you are qualified to provide, and fundamentally changing how you approach coverage to create the raw material for meaningful buddy interactions.

This means making fundamental decisions about the editorial scope: Will you offer personal finance guidance, or stick to explaining economic trends? Can you advise on local restaurant choices, or should you focus on food policy? Are you prepared to help people interpret medical research, or will you limit coverage to healthcare systems?

These aren’t technical questions. They’re strategic choices about the brand promise and editorial responsibility that directly determine what an AI buddy can actually help people with.

The unique data advantage of journalism

What makes an AI buddy operated by a media organisation fundamentally different from general-purpose AI tools such as ChatGPT or Perplexity is not only the underlying technology. The decisive advantage lies in the nature of the data set itself.

Media organisations possess content that has been generated by professional journalists applying editorial judgement, verification processes, and deep contextual understanding. This body of work reflects years — sometimes decades — of consistent reporting on local, national, and global developments.

Every story has been selected, researched, written, and reviewed to serve audiences with reliable, meaningful information about the real world as it is actually experienced by human beings.

In contrast, general-purpose language models are trained on enormous, increasingly also synthetic, and often noisy data collected indiscriminately across the Internet. While technically powerful, these systems frequently lack the depth of curated judgement, relevance filtering, and accountability that define professional journalism.

The media organisation’s data set offers a uniquely human-experienced representation of reality. It embodies context, historical continuity, and the editorial discernment required to distinguish what matters.

This gives an AI buddy developed by a media organisation a distinct and defensible advantage: It can deliver personalised, situation-aware guidance grounded in journalistic integrity and public service responsibility, not merely in generic pattern recognition.

When audiences seek advice that affects their personal lives, careers, finances, or communities, they require not just information but trusted, context-rich guidance. Only a media organisation, through its own carefully built archive of reporting, can consistently offer that level of dependable expertise.

The conversational infrastructure

Building AI buddy capability centres around implementing retrieval-augmented generation (RAG), the technology allowing AI systems to pull relevant information from your content archive before generating responses. Unlike generic training models, RAG ensures the AI generates responses grounded in your organisation’s trusted journalism.

When a reader asks, “Should I refinance my mortgage?” the system first searches the database for relevant coverage on interest rates, mortgages, and refinancing, and then generates an informed, brand-controlled response.

Introducing agentic AI: from passive answering to active assistance

While current language models and RAG systems can restructure existing journalism into conversations and generate helpful follow-up responses, the AI buddy builds on its agentic capability. Rather than simply responding to prompts, agentic AI enables the buddy to operate proactively and in a goal-oriented way: monitoring, evaluating, suggesting, initiating actions, and executing multi-step tasks on behalf of users.

An AI agent can autonomously scan multiple data sources, identify emerging topics, track ongoing developments, and coordinate task execution using tools that are available to it — whether that means recommending refinancing steps based on shifting interest rates or directly booking a restaurant after suggesting dinner options.

In an agentic model, AI buddies evolve from reactive answer engines into active companions supporting users with both advice and real-world action.

This shift is central to a “buddy economy.” The value proposition moves beyond information delivery toward outcome enablement — reducing friction, simplifying complex tasks, and delivering tangible solutions — all while grounded in the trusted, curated journalism that defines media organisations’ unique data set advantage.

A fully developed buddy experience therefore requires integration with external service providers. Connections to booking platforms, travel systems, ticketing services, and local event organisers transform advice into immediate action.

While these integrations add technical complexity and require advance agreements, they significantly increase user value and open up new monetisation opportunities well beyond traditional subscriptions and advertising — by solving real problems and completing tasks directly for users.

From content sales to relationship revenue

The buddy economy fundamentally changes how news organisations generate revenue. Instead of selling access to information, you are selling access to guidance and solutions for problems.

For instance, basic subscribers receive standard content access. Premium subscribers pay additional fees for personalised guidance, real-time alerts tailored to their circumstances, seamless service integrations, and even access to human experts when AI alone is insufficient.

Transaction revenue sharing creates new monetisation opportunities without traditional advertising friction. When an AI buddy provides a review of a restaurant and facilitates the booking, a fee is earned from the reservation platform.

These aren’t advertisements disrupting the user experience; they’re natural extensions of editorial guidance readers have specifically requested. The revenue follows value delivery rather than interrupting it.

Editorial boundaries and ethical considerations

Transaction-based revenue builds on the established foundation of affiliate marketing, but with a crucial difference: the focus shifts from product sales to service completion. Rather than promoting products for commission, news organisations can facilitate actions readers have already decided to take.

Journalistic integrity sets clear boundaries on what news organisations can and cannot pursue. Editorial coverage must be genuinely beneficial to readers and driven by the idea that the service helps people to “get things done,” rather than lure them into buying something.

As with restaurant table booking, when covering local entertainment, the buddy can book cinema tickets or theater seats as a natural extension of event recommendations, generating transaction fees from ticketing platforms.

Similarly, travel coverage becomes more valuable when the AI can actually book flights, hotels, or rental cars mentioned in destination guides, earning standard travel industry commissions while providing genuine convenience to readers.

Some opportunities remain off-limits regardless of revenue potential. Recommending specific stocks or investment products, for instance, crosses into financial advice that requires regulatory compliance most news organisations cannot practically manage.

Similarly, endorsing political candidates or causes — even through seemingly neutral-booking services for campaign events — would compromise editorial independence.

The strategic imperative

The transformation from news source to life agent isn’t just about technology; it’s about reimagining journalism’s role in people’s lives. In an age where everyone has a digital companion within immediate reach, the organisations that become the most trusted, helpful, and insightful buddies will own the relationships that matter.

The photography community I never joined still exists, but it became less relevant to my learning process as this new form of guidance took over. Audiences are making similar choices daily across every domain where they need expertise and support. In-person guidance may well become relevant again when I need more specialised,hands-on help to progress further.

The organisations that recognise this shift and position themselves as trusted AI-powered advisors will capture relationships competitors still don’t realise are available.

The buddy economy isn’t a distant possibility; it’s an immediate opportunity for news organisations willing to expand beyond information delivery into guidance provision. The technology exists, the audience behaviour is already shifting, and the revenue models are proven in adjacent industries.

The question isn’t whether this transformation will happen but whether media organisations will lead it or watch others capture the advisory relationships they have spent decades building. In a world where everyone carries a potential buddy in their pocket, becoming the most trusted voice in that conversation may be journalism’s most important strategic imperative.

The strength of media organisations lies not only in technology adoption but in the unique data set they already possess — a curated, verified, and human-experienced representation of reality. This is the ultimate foundation of audience trust in the AI-powered era.

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .