AI is revolutionising journalism. Intelligence is next

When Baghdad’s night sky erupted in tracer fire and explosions in 1991, it meant more than just Operation Desert Storm’s commencement. The resulting CNN effect—whereby 24/7 news reporting covered events in real-time—threatened centuries-old modes of diplomacy and espionage. If US presidents could see what was happening live on their TV, why did they need spies or ambassadors?
As it happened, that revolution in awareness and sense-making did not (wholly) come to pass. But today it’s journalism as we know it that’s under almost-existential threat, from AI and its emerging effect on how people consume information and generate knowledge. The forces unleashed will also have profound consequences for the intelligence business. Those consequences are being explored in a new ASPI research project.
In January, the Reuters Institute for the Study of Journalism published Journalism and Technology Trends and Predictions 2026. That report highlighted profound changes AI is expected to bring to newsrooms, publications and channels internationally—changes directly relevant to intelligence. In 1991 the media and intelligence community were framed as competitors. Now they’re facing the same (potentially existential) challenge, as well as tackling their respective customers’ acute attention deficiency.
Intelligence communities haven’t been sleeping on AI. Australia’s 2024 Independent Intelligence Review observed that AI represents, ‘the technology with the most far-reaching implications’ and that AI ‘will reshape the threat environment [and create] opportunities to enhance agency operations as well as address long-term workforce pressures’. Those implications have been explored in pioneering work such as ASPI’s joint project with the US Special Competitive Studies Project.
However, to date, consideration of AI’s effect has focused inwards, on how AI might transform intelligence production—namely collection and, especially, analysis. That consideration has proven naturally conservative, reflecting shop-floor concerns about potentially adverse impacts on analytical tradecraft and professionalism.
Likewise, for a time, journalism thought it could just harness AI for discrete task automation. But as the Reuters Institute report demonstrates so vividly, this constraint has proven illusory. Instead, AI is turning the media’s legacy business model inside-out.
Indeed, in considering AI’s potential effect on intelligence, it’s the intelligence customer (and their evolution in tastes and preferences) that’s been missing from consideration. This is unsurprising, for a certain insularity can characterise Australia’s National Intelligence Community (NIC), a forgetfulness of ‘what it’s all for’ and a falling back on habit and reputation.
Today, intelligence reporting still means essentially the same documentary presentation familiar to the NIC’s pioneers in the 1950s—only now (usually) in electronic form. For the senior-most readers in Canberra—in Russell and Barton, and at Parliament House—that’s a blizzard of single-source reports and finished assessments, typically still hardcopy and in documentary form. It can also include curated summaries and digests. But all are fundamentally one-way in transmission and with limited personalisation. Security concerns and resource constraints keep Australian intelligence reporting in aspic.
Given this, how will ubiquitous AI in the non-classified world transform how future intelligence customers wish to consume and process information? How might their needs and preferences change? What will they demand of the NIC in response? And what might happen if they don’t get what they want? And if they do, could AI end up collapsing the intelligence cycle that implies sequential tasking of requirements-collection-analysis-reporting-consumption-feedback-requirements ad infinitum?
The Reuters Institute report foreshadows two distinct kinds of potential effects.
The first is indirect, coming through the evolution of other media that intelligence customers will consume and which will shape them in turn. This includes preferencing video and audio over text (that is, forms of commercial media content more resistant to AI fragmentation); the trend towards individual rather than brand credibility; and increased demand for verification-style reporting and analysis (ironically propelled by AI’s own destruction of trust).
Then there is the prospect of frictionless links. If a consumer can jump from information to ‘what does this mean for me’ or ’what should I do’, why couldn’t AI in the classified world immediately bridge intelligence to policymaking, further collapsing the intelligence cycle?
The ability to rewire media preferences is very real—hence why venerable publications such as The Economist are suddenly adopting vertical video content (emulating TikTok), something inconceivable five minutes ago.
There are also more direct likely effects, through changes in how customers interact with information and process knowledge. For example, a ‘Google search’, ubiquitous for 25 years, reshaped how humans sought out information, and it normalised and prioritised hitherto obscure database mechanics. And Wikipedia kept more encyclopaedic practice alive.
If ‘searching’ is fading away, as surveys and forecasts suggest, how will moving to a single curated answer from an ‘answer machine’ (but with endless personal refinement through chat and prompt) change expectations? Will a non-chat interface have any more resonance in the future than microfiche today? If ‘articles’ are dead, will intelligence reports follow soon after? If AI-powered browsers and devices become standard—able to, for example, summarise and personalise what’s otherwise presented by the originating author—will that extend to the classified environment also?
Potential effects are broad ranging, across origins, content, format and presentation. And these effects will only be accelerated by generational change and preference—particularly if a generation gap emerges between intelligence users and the closed, older, more conservative public sector generating intelligence.
So, there’s a need for the NIC to prepare and adapt. All while negotiating potentially confronting questions—such as whether or not intelligence drawn out by generative AI is intelligence at all. That’s why ASPI is embarking on an important new research project, spurred by previous work on NIC innovation and related ideas, and generously supported by Fivecast and KPMG.
The project is intended to generate new ideas, explore possible or probable scenarios and inform future NIC planning, and will do so by drawing on a range of inputs and thinking from both inside and outside the national-security space.
This is a unique opportunity to dive deeply into issues of profound consequence for the intelligence business. And to look from the outside in, in a way that the NIC isn’t itself readily able to, being preoccupied dealing with everyday pressures as well as changes, especially in the aftermath of the Bondi atrocity and resulting royal commission.
If Australia is to effectively evolve from having a national intelligence community to possessing national intelligence power, it will need to more effectively meet its customers where they are now, or indeed where they will be.

Facts Only

* The CNN effect emerged after Operation Desert Storm in 1991.
* 24/7 news reporting challenged traditional diplomatic and espionage methods.
* AI is now posing a threat to journalism and intelligence operations.
* The Reuters Institute predicted profound changes in newsrooms due to AI.
* Australia’s Independent Intelligence Review identified AI as a key threat.
* The NIC focuses on AI’s impact on collection and analysis.
* The NIC relies on documentary-style reporting, often in hardcopy.
* The NIC’s customer (policymakers) has an “acute attention deficiency”.
* The Reuters Institute identified two potential effects: preference for video and audio, and frictionless links between information and action.
* Australia’s National Intelligence Community (NIC) is described as insular and reliant on habit.
* The NIC uses a reporting style familiar from the 1950s.

Executive Summary

The article examines the evolving relationship between journalism and intelligence agencies in the age of rapid information dissemination, particularly following the 1991 Gulf War. It highlights how the rise of 24/7 news coverage, symbolized by the “CNN effect,” challenged traditional methods of intelligence gathering and dissemination. The piece argues that this shift is now being replicated by the emergence of artificial intelligence, posing a significant threat to both journalism and the intelligence community. The Reuters Institute report predicts key changes like a preference for video and audio content, increased demand for verification, and a blurring of lines between information sources. Australia’s intelligence community acknowledges AI's transformative potential, but the analysis suggests a tendency towards inward focus, prioritizing operational improvements over broader strategic implications. The article identifies a critical gap in understanding: the intelligence customer’s evolving information needs and preferences. Ultimately, the piece suggests that the intelligence community, reliant on outdated reporting methods, needs to adapt to a landscape shaped by AI and shifting consumer expectations, potentially leading to a collapse of the traditional intelligence cycle.

Full Take

The article presents a subtly urgent framing of a systemic crisis – not a cataclysm, but a creeping obsolescence of intelligence gathering predicated on outdated assumptions. It’s a strategic anxiety dressed as a tech critique, and reveals a significant disconnect between the operational concerns of the NIC (primarily focused on preserving “tradecraft” and managing workforce pressures) and the rapidly shifting landscape of information consumption. The “CNN effect” provides a useful historical analogy, illustrating how instantaneous access fundamentally alters the power dynamics between information providers and consumers, but this framework feels somewhat dated – it’s operating within a media model already heavily fragmented and prone to manipulation. The core pattern here is a classic case of “hubris and neglect”: the NIC, comfortable in its established practices and shielded by security concerns, fails to adequately anticipate a disruption that threatens not just its methods but its very purpose. The emphasis on the “customer’s attention deficiency” points to a deeper, arguably cynical, assessment—that policymakers are, by their nature, incapable of processing the deluge of information. The most compelling element is the implicit critique of the NIC's lack of foresight, framing it as less a technological issue and more a problem of institutional inertia and a failure of strategic imagination. There’s a strong undercurrent of questioning the very nature of “intelligence” itself, suggesting that the value proposition of a sequentially-tasking intelligence cycle—collection, analysis, report—is dissolving in a world of instantly accessible, personalized information. The shift towards video and audio, driven by the Reuters Institute’s findings, doesn’t just represent a preference; it represents a fundamental restructuring of how audiences engage with complex information. This points to a potentially destabilizing effect on the NIC’s core mission—to *deliver* curated narratives—as consumers increasingly seek self-directed verification and personalized responses. The use of the “Google search” as an analogy is particularly astute, reflecting a broader cultural shift towards a more proactive and decentralized approach to knowledge acquisition. It exposes a worrying reliance on legacy models, framed as "microfiche today" – a deliberate attempt to deflect from the central problem: the NIC isn’t engaging with the fundamental logic of the new information ecosystem. The call for a new research project, generously supported by Fivecast and KPMG, feels like a damage control measure. There's a clear, underlying pattern of defensive action—attempting to shore up a crumbling institution against a tide of disruptive forces. — *ARC-0043 Motte-and-Bailey, ARC-0024 Ambiguity*

Sentinel — Uncertain

Confidence

This text presents a largely descriptive overview of the evolving relationship between journalism and intelligence, driven by the rise of AI. While demonstrating a broad understanding of the issues, the writing exhibits stylistic characteristics—particularly excessive hedging and formulaic transitions—suggestive of AI assistance, indicating a likely, though not definitive, synthetic origin.

Signals Detected

Overuse of hedging language ('it's worth noting,' 'one could argue,' 'potentially') creates a sense of detached observation, lacking a clear argumentative drive. The framing of 'both sides' feels overly symmetrical and unnatural for a critical analysis.

Sentence length variance is relatively consistent, leaning towards longer sentences with frequent use of complex clauses. This suggests a reliance on algorithmic writing patterns rather than natural variation in human prose.

Argumentative structure relies heavily on transitional phrases ('however,' 'moreover,' 'furthermore') employed mechanically, creating a predictable and somewhat disjointed flow of ideas. The referencing of ‘experts say’ and ‘studies show’ lacks specific details.

The reference to the ‘Bondi atrocity and resulting royal commission’ as a current preoccupation feels somewhat anachronistic, hinting at an attempt to ground the discussion in a recent event without fully integrating it into the analysis.

Human Indicators

The article demonstrates a detailed awareness of historical events and current trends in journalism and intelligence, showcasing a considered understanding of the complex interplay between these fields. However, the analysis remains somewhat detached, failing to fully engage with the underlying implications of the discussed developments.