Shadow AI refers to the use of tools like ChatGPT and DeepSeek, often on personal accounts for clearly official tasks, such as drafting reports from meetings, preparing talking points, translating notes, or summarising lengthy documents. For diplomats, this is deeply attractive as LLMs provide speed, efficiency, and stylistic polish. Yet diplomacy is a profession of discretion and sometimes secrecy. Shadow AI introduces a structural contradiction: the more diplomats rely on commercial AI platforms, the greater their risk of undermining the confidentiality and discretion on which diplomatic practice is based. Behind Shadow AI lies the ‘two-speed’ problem of rapid technological changes and slow institutional adaptation. Diplomatic services take years to provide secure, in-house AI solutions. In the meantime, AI platforms are literally one click away on diplomats’ phones and laptops. The paradox is that secure in-house AI, based on open-source models, is technically feasible and financially affordable. The bottleneck for AI transformation is much less technical than organisational: how foreign ministries value, preserve, and utilise knowledge as their core asset. The experience and curiosity of those who experimented with LLMs in Shadow AI style should be considered to be a critical asset. Shadow AI is not the first time that digital tools have outpaced institutional memory practices. Archivists have warned of a “digital dark age” to describe how records from the late 1990s and early 2000s were lost because institutions were still geared to paper files, while records shifted to electronic form: emails, early websites, and word-processing files. To recover these traces, “digital archaeologists” scour obsolete storage media, long-abandoned websites, and private email archives, attempting to reconstruct what institutions once knew and decided. A 2024 Pew Research Centre study illustrates how fragile digital memory can be: 38% of webpages that existed in 2013 were no longer accessible by 2023, and about a quarter of all pages seen at any point between 2013 and 2023 had disappeared by late 2023. Much of this loss is unintentional: links break, hosting is discontinued, formats become obsolete. But the effect is a “black hole” in institutional and societal memory. Shadow AI risks creating a similar grey zone in diplomatic memory, but now the problem is not just loss, but the gain of diplomatic knowledge by somebody else. Namely, big AI platforms used by diplomats can capture, organise, and ultimately, provide this knowledge as a commercial service or strategic asset. IBM defines Shadow AI as ‘the unsanctioned use of AI tools or applications by employees without formal approval or oversight of the IT department’. ShadowAI is not a marginal behaviour. Recent research indicates that a large majority of organisations have employees using unapproved AI tools at work, and around one-third of AI-using employees openly admit to sharing sensitive work data with AI platforms without permission. Analysts, such as Gartner, project that by 2030, around 40% of enterprises will experience security or compliance breaches linked to shadow AI. In diplomacy, the incentives for shadow AI are even stronger: The result is a fertile environment for shadow AI to emerge as a normal, if unofficial, part of diplomatic practice. Major corporations are taking decisive steps to mitigate the risks of Shadow AI, the unauthorised use of external AI tools by employees. As reported by Reuters, Amazon has mandated that its 250,000 developers cease using all AI platforms except its own, named Kira. The primary motivation is to safeguard intellectual property and prevent competitors from accessing proprietary software solutions. This trend is also evident in the banking sector, where financial institutions are banning Shadow AI, perceiving it as a dangerous vulnerability that could leak invaluable business and banking secrets. The most visible form of shadow AI is simple: a diplomat opens ChatGPT or another chatbot in a browser, types a question, and gets an answer. But questions themselves are data. They reveal: Across many queries, an external provider could reconstruct a strikingly detailed picture of a country’s concerns, red lines, and preferred framings. Even if no single prompt is highly sensitive, the behavioural pattern revealed over hundreds of prompts is. Moreover, chat logs, questions, plus follow-up comments on the answers can build a rich behavioural profile of individual diplomats: their style, risk appetite, thematic focus, and even psychological traits. For diplomacy, where strategic opacity and controlled signalling are often integral to negotiation, this is a non-trivial leak. Diplomats draft constantly: reports to capitals, minute-by-minute readouts of negotiations, non-papers, letters, talking points, or speeches. LLMs are extremely helpful here: they can clean up language, reorganise arguments, and adapt a text for different audiences. However, the risks are layered: Confidentiality of content Textual inflation and erosion of diplomatic craft As it becomes tacitly understood that “AI probably wrote this,” diplomats may read less attentively, skim more, and treat long documents as boilerplate. Important nuance can be buried in standardised paragraphs, undermining the precise, carefully crafted language that diplomacy relies on. Convergence of language and positions Multilingualism is central to diplomacy. AI translation services are widely used because they are fast, accurate, and easy. But submitting internal or confidential texts to commercial translation services exposes those texts to the service providers. Even if the provider claims it does not store or use data for training in certain modes, the diplomat must trust: In practice, a stream of translations can reveal which documents are considered important, which languages are prioritised, and where sensitive bilateral or multilateral engagements are intensifying. Summarisation tools are attractive for diplomats facing hundreds of pages of negotiations, resolutions, or reports. Feeding large volumes of text into AI to get summaries is now a common practice. Risks include: As graphs, infographics, and slide decks become standard in multilateral meetings, diplomats increasingly rely on AI tools that can generate presentations, diagrams, and “data stories.” Uploading datasets, internal statistics, or draft messages into these tools carries the same confidentiality risks as text-based usage. In addition, visualisations can fix certain interpretations of data as “the” narrative, sometimes oversimplifying complex political balances into easily digestible—but misleading—graphics. At a technical level, interaction with AI platforms can be intercepted at several points: Even without interception, AI companies have full control over the inference process. They hold large databases of prompts and outputs which, in many cases, can be used for model improvement, product analytics, or security monitoring. Commercial incentives usually push companies to protect user data. Trust is at the heart to their business model. However, they are embedded in legal jurisdictions. In both the United States and China, home to many leading AI providers, laws allow authorities, under certain conditions, to request access to stored data, including service logs and user interactions. For diplomatic services, there is no recognised diplomatic immunity that shields such data from subpoena or security requests. This creates a strategic vulnerability: sensitive diplomatic reasoning may, unintentionally, become accessible to foreign authorities through perfectly legal channels directed at private companies, rather than through classical espionage or hacking. Standard responses to new digital risks are familiar: awareness-building campaigns, guidance notes, and training. While useful, they have clear limits in the context of Shadow AI. Experience from basic cybersecurity hygiene is instructive: despite years of training, people still reuse passwords, click on phishing links, or write credentials on sticky notes. Awareness alone rarely overcomes powerful incentives and habits. With AI, the incentives to overlook safety concerns are even stronger as AI offers efficiency (saving hours of drafting or translation), quality (improved language, structure, and clarity), and immediacy (answers on demand, without bureaucratic delays). For a diplomat under time pressure, these “carrots” will usually outweigh risk concerns, often perceived as abstract. It is unrealistic to expect that mere awareness will stop shadow AI, especially when sanctioned alternatives are weak or absent. Thus, the policy question is not whether diplomats will use AI (they will), but rather which AI they will use, under whose control, and with what safeguards. If Shadow AI is a symptom of unmet needs, then the primary solution must be to meet those needs safely. For diplomatic services, these points aim to build or procure in-house AI systems, based on open-source models and tailored to the diplomatic context. The main champions of AI transformation should be those who have shown initiative and curiosity in experimenting with LLMs in Shadow AI style. Building on them as critical asset for changes, other elements of such a solution should include: Local control of data and models Training models on diplomatic knowledge Clear governance and guardrails Smart gateways to the outside world Redesign of workflows, not just “new tools” In this way, diplomatic services can address shadow AI not by trying to forbid AI outright, which is likely to fail, but by offering equally powerful, safer alternatives that match diplomats’ practical needs Shadow AI is dangerous for diplomacy, not because AI is inherently hostile to diplomatic values, but because unsanctioned, externally controlled AI quietly erodes three foundations of diplomatic practice: The historical lesson from the “digital dark age” is that institutions which fail to adapt their record-keeping and knowledge practices to new technologies pay a high price later in lost institutional memory, weakened accountability, and diminished strategic capacity. Shadow AI extends this risk from memory to live negotiation and strategy. The way forward is not nostalgia for pre-digital diplomacy, nor a naïve embrace of consumer AI tools. It is the deliberate construction of trusted, in-house AI ecosystems that embed diplomatic values – discretion, reliability, balance – into the very architecture of the tools diplomats use every day. Only then can diplomacy move from being a passive consumer of Shadow AI to an active steward of AI for the benefit of their countries and the global public good.
Historical echo: from ‘digital dark age to Shadow AI
What is Shadow AI?
The corporate crackdown on Shadow AI begins
Everyday Shadow AI practices – and why they are risky
Chatbots as informal advisers
Drafting: from reports to speeches
To achieve good outputs, users typically paste in detailed context, including names of interlocutors, meeting dynamics, sensitive assessments, or internal positions. This material may then be stored on servers controlled by foreign private companies and potentially subject to foreign legal processes.
LLMs are optimised to produce fluent, abundant prose. They make it easy to generate long texts with little effort. This can lead to inflation of diplomatic text: more pages, less signal. Quantity risks overtaking quality and genuine insight.
If many diplomats rely, even partially, on similar AI systems, their texts may converge towards similar framings and metaphors. Subtle national perspectives and political nuances risk being flattened into generic “AI-speak,” eroding the distinct voice and normative positions that are part of diplomatic identity.Translation: speed at the cost of confidentiality
Summarisation: compressing nuance
Visualisations and presentations
Where do Shadow AI risks materialise?
Why training and awareness-building are not enough
Towards solutions: in-house AI as the realistic path
Conclusion: AI from shadow to stewardship
