Why Trump’s appointment of Musk as an ‘efficiency tzar’ is about AI transformation?

President-elect Donald Trump has appointed Elon Musk as his ‘efficiency tzar’ with the stated goal of reducing federal administration. Many observers see this move as a personal vendetta against the so-called ‘deep state.’ However, focusing on Trump’s motivation for Musk’s appointment together with Vivek Ramaswamy as the advisor for government efficiency could lead to losing sight of the wider context of the profound AI transformation of administrations worldwide, from national governments to the UN.

The reality is that current bureaucratic machinery is largely anchored in outdated models—the Taylorian model of industrial production and the Weberian concept of bureaucracy. These frameworks, which emphasise rigid processes and control of information, are becoming anachronistic in the AI era.

The need for AI transformation

Namely, AI is and will increasingly automate text, which is a core tool of any bureaucracy since ancient civilisations. Many text-centred tasks within bureaucracies will disappear or undergo profound changes in the coming years. For instance, it is estimated that up to 50% of diplomatic tasks centred around text, such as diplomatic reporting, will be automated by AI. This major disruption in the operations of bureaucracies is not a prediction but a fast merging reality as organisations and governments start leveraging AI to streamline their operations and enhance effectiveness.

Thus, Musk’s task will be to codify this profound AI transformation of the modus operandi of the US government, which is likely to be mimicked by other governments and international organisations in the coming years.

Preparing for AI transformation

While following this major transition in the USA, here are a few steps that can be taken by governments and international organisations to prepare for AI transformation of public institutions.

First and foremost, society must start serious discussions about the changes on the horizon. Rather than getting bogged down in general discussions about AI ethics and, for example, long-term risks of AI, we need to have substantive conversations about how AI will specifically impact the work of governments and international organisations now and here.

Second, we should adopt a proactive mindset. Instead of waiting for influential figures such as Musk or big tech companies to lead the charge on AI integration, we must take initiatives in a bottom-up style by developing AI solutions at the level of government departments, communities, and other public and societal institutions. This ‘capillary’ AI would help us to preserve our knowledge and adjust AI to local specificities.

Third, we must identify public functions and tasks which cannot and/or should not be automated by AI, as efficiency should not be the only criterion for deciding about the use of AI. For example, the human element in diplomatic representation and negotiation is critical for ensuring core functions of diplomacy as a way of managing interactions between human groups, currently organised in national states. Thus, decisions to use AI in diplomacy should not be based solely on efficiency criteria.

Fourth, instead of squandering already tight public budgets on flashy AI projects and technology-driven solutions, we should invest in training staff and restructuring organisations to adapt to the changes that AI will bring. An experience from Diplo’s AI transformation shows that technology plays less relevance in AI adoption than preparation of staff and changes in organisations that were centred at Diplo around nurturing ‘cognitive proximity’ among us, humans, and between us and machines.

Fifth, taking care of people should be critical. Instead of automatically replacing people with AI, serious efforts should be made to fit their unique talents and experience in the emerging ‘knowledge economy.’ There are many creative solutions that are sometimes overlooked in the simplified dichotomy of machines vs. humans. For example, communities of interpreters and translators should not fight lost battles against AI but focus on contributing to the development of AI models in different languages. Philosophers and linguists are in high demand as the focus shifts from technology, which is becoming a ‘commodity,’ to knowledge insights that can only be provided by humans.

Sixth, efficiency should not be the only criterion for AI transformation, as governments and public institutions have many other functions to control power, represent interests, and ensure societal stability.

Next Steps…

So far, there has been mainly knee-jerk media coverage of Musk’s appointment, shaped by overall tension between Trump and the US government machinery. Regardless of Trump’s motives for this move, the focus should be on much deeper changes which Musk, as ‘efficiency tzar’, will bring to the way our public institutions will function in the AI era. By engaging in meaningful discussions, taking proactive steps, and investing in building capacities, we can prepare public institutions, including diplomacies, for the AI transformation ahead of us. The time for action is now!