I spend most of my time applying Brand Drift to companies, because that's where the clearest, most public, most easily documented cases keep showing up in the ordinary course of following the news. But somewhere in the middle of building my four-country research design, I started asking a question I couldn't quite let go of: if a corporate brand can drift away from its stated values through an automated system nobody was watching closely enough, can a country do the exact same thing to its own national brand — and would the mechanism actually look any different?
What a "national brand" even means, theoretically
This isn't just a loose metaphor I'm reaching for. Simon Anholt's work on nation branding — what he later reframed as "competitive identity" — treats a country's reputation as something built the same way a corporate brand is: through the accumulated pattern of what the country actually does, not just what it says about itself in tourism campaigns or diplomatic statements. A national brand, in this sense, has a stated identity — the values a government claims to uphold, the promises made in its founding documents and public commitments — and an actual output, the sum of what its institutions and systems genuinely do to citizens and the world, day to day. That's the identical two-halves structure I use to define corporate Brand Drift, just scaled up to the level of a state.
If that structure holds, then a country's stated commitment to fairness, dignity, or due process, and an automated government system's actual behavior toward citizens, are exactly as capable of drifting apart as a brand's stated values and an unsupervised chatbot's actual output — and I think Australia's Robodebt scheme is close to the cleanest large-scale demonstration of exactly that mechanism I've come across in any country I've looked at closely so far, corporate or governmental, precisely because the paper trail behind it is so unusually complete.
What Robodebt actually did
Between 2015 and 2019, the Australian government ran a welfare debt-recovery program that became known as Robodebt. The scheme used an automated data-matching process, called income averaging, to compare a welfare recipient's reported fortnightly income against their annual tax data and flag apparent overpayments — effectively reversing the usual onus of proof, so that more than half a million people were issued debt notices they then had to disprove themselves, often without easy access to the old payslips or bank records needed to do so, and often with reduced access to a human case officer who might have caught the error sooner. A subsequent Royal Commission found the scheme was not just poorly designed but unlawful, built on a method that had been flagged as legally doubtful internally years before the government finally stopped defending it in court, at real and mounting human cost the whole time. The final toll: more than half a million unlawful debts raised, a A$1.8 billion settlement, further payouts bringing total government compensation past A$2.4 billion, and findings connecting the scheme to serious psychological harm, including multiple deaths by suicide among people caught in its debt-recovery process, according to the government's own Royal Commission.
Where the drift actually happened
Here's the part that maps directly onto the corporate cases I study. Australia's government did not lack a stated commitment to fair, lawful treatment of welfare recipients — that commitment existed in social security law, in the department's own stated obligations, and in ordinary public expectation of how a government should treat people navigating a difficult period of their lives. The actual output of the automated system drifted sharply away from that stated commitment, and — this is the detail I keep returning to — internal legal advice warning that the scheme was likely unlawful existed years before the scheme was finally abandoned, without that sensing ever translating into a seizing response from anyone with the authority to stop the program. A department lawyer flagged the legal risk in 2017, in writing, circulated among senior colleagues. The department continued the scheme regardless, and continued debt-recovery action even after a court had already ruled parts of it unlawful, according to a later ombudsman's report.
That is drift, at the scale of a state: a widening, sustained gap between a nation's stated legal and ethical commitments and its actual automated administrative behavior, running for years, with the information needed to catch it sitting internally the entire time, unacted upon, for reasons the Royal Commission's own findings suggest were more about political incentive and bureaucratic momentum than about any inability to have seen the problem coming.
Why this matters for how I think about national branding research
This is part of why I don't think Brand Identity Governance research should stay confined to the corporate sphere, and part of why my own research work treats national cultural identity and corporate brand governance as related, not separate, questions. A national brand actively promoted by a government — trustworthy, innovative, fair, efficient, whatever the specific promise happens to be — is making exactly the same kind of identity claim a corporation makes, and is exposed to exactly the same kind of drift the moment automated systems start administering that promise faster than anyone is checking whether the promise is actually being kept in practice. The stakes are simply higher, because the "customers" experiencing the gap are citizens, and the mechanism for holding an unlawful automated government system accountable is generally slower and more expensive than a customer simply switching to a competing brand.
What Dynamic Capabilities Theory adds to the Robodebt story specifically
I don't think it's a coincidence that the same three-part structure I've applied to corporate drift elsewhere — sensing, seizing, transforming — describes Robodebt's failure just as precisely as it describes CNET's or Levi's. The sensing existed, internally, in the form of the 2017 legal advice warning the scheme was likely unlawful, and again in 2018 when external counsel reached a similar conclusion. What never happened was seizing: nobody with the authority to pause the scheme actually did, despite the sensing signal being about as unambiguous as internal legal advice gets. And transforming, in the sense of restructuring the underlying process so a similar gap couldn't recur, only happened after a Royal Commission, years of harm, and a multi-billion-dollar settlement forced the issue — which is about as expensive and as delayed as transforming ever gets, precisely because sensing and seizing had both already failed by the time it became unavoidable.
This is, I think, the strongest possible argument for why sensing capability has to be built deliberately rather than assumed to exist because "someone would surely notice." Someone did notice, twice, in writing, years before the scheme ended. The gap wasn't a knowledge gap. It was a gap between knowing and acting on what was known — precisely the seizing failure Dynamic Capabilities Theory would predict is the harder, more organizationally costly capability to build, because seizing requires someone with real authority to accept short-term cost or embarrassment in exchange for avoiding a much larger cost later, and that trade is exactly the one bureaucracies, corporate or governmental, are structurally worst at making under pressure.
The uncomfortable parallel to my own regional research
I want to be honest about why this case unsettles me slightly, given the rest of my research. I've written elsewhere about the UAE and Saudi Arabia moving aggressively on AI adoption as part of ambitious, top-down national strategies, and I've framed that speed as a genuine opportunity to build governance habits early, before bad practices calcify. Robodebt is the cautionary version of exactly that same story, just in a different country: a government moving confidently on automation, in service of a stated efficiency and fairness goal, without building the internal sensing capability to catch the gap between that stated goal and the system's actual behavior before the gap became a half-million-person scandal. I don't think that parallel means aggressive national AI adoption is inherently dangerous. I think it means the sensing capability has to be built with the same seriousness and the same urgency as the adoption itself, at the level of a government exactly as much as at the level of a company — and Robodebt is what happens when a state builds the second without the first, at a scale and a human cost no corporate case I've studied comes close to matching.
If you're thinking about how brand governance principles might apply beyond the corporate sphere you usually see them discussed in, that's a conversation I'd genuinely enjoy having. Get Your Free Brand Audit →
References
Anholt, S. (2007). Competitive Identity: The New Brand Management for Nations, Cities and Regions. Palgrave Macmillan.
Blavatnik School of Government. (2023, July 26). Australia's Robodebt scheme: A tragic case of public policy failure.
Royal Commission into the Robodebt Scheme. (2023). Final Report.
Victoria Legal Aid. (n.d.). Learning from the failures of robodebt — building a fairer, client-centred social security system.