Not elected, not human—Albania’s AI minister sparks a new governance debate.
Updated
June 10, 2026 3:36 PM
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Promotional avatar graphic representing Diella, the Albanian government's artificial intelligence system. PHOTO: EALBANIA
Artificial intelligence already supports a wide range of applications, from medical diagnostics and financial systems to logistics, manufacturing, defence and public service delivery. Now, it is starting to move closer to public office.
In January 2025, Albania introduced Diella, an AI-powered virtual assistant developed by the National Agency for Information Society, known as AKSHI, with support from Microsoft. Launched on the e-Albania platform, the government’s digital services portal, Diella helps citizens and businesses access official documents and services through voice assistance. She can also issue electronically stamped documents, which helps speed up administrative processes.
Then, in September 2025, Prime Minister Edi Rama announced that Diella would join his cabinet as the “Minister of State for Artificial Intelligence”. This move drew global attention. It also raised a simple question: what does it actually mean for a government to appoint an AI minister?
The case raises bigger questions for governments everywhere. Can an AI minister make public services faster and cleaner? Or does it create new risks around transparency, accountability and control?
Diella is not a humanoid robot sitting in a cabinet room. On screen, she appears as a digitally rendered woman wearing traditional-style Albanian clothing. Her name means “sun” in Albanian, a deliberate choice for a system meant to bring more light into public administration.
Her face and voice have become part of the controversy. Albanian actor Anila Bisha has said she agreed for her likeness to be used for the e-Albania public services platform, but not for a cabinet-level political role. In 2026, she took legal action to stop the government from using her image and voice for Diella. For now, the government has denied wrongdoing.
Diella began as a digital assistant on e-Albania. In that role, she helps users find services, request documents and navigate government processes online. For citizens, that can make public services feel less confusing. Businesses may also spend less time dealing with paperwork.
Her cabinet role is more political. The government wants Diella to support public procurement, where companies compete for government contracts. This is one of the most important areas of public spending. It is also one of the easiest places for corruption, favouritism and hidden influence to enter. The goal is to use AI to process information, check documents, support tender procedures and make the system more traceable.
That said, the government has emphasized that Diella is not replacing elected officials or civil servants. As per Enio Kaso, director of AI at AKSHI, each stage will be monitored and approved by human experts.
In May 2026, the Albanian government said it had completed the technical groundwork for the AI-powered public procurement system under the Diella project. The planned system would pull data from more than 40 digital public registries, reduce paperwork for businesses and support parts of the tender process. Earlier reports said the government hoped to have the full system ready by the end of 2026.
The government’s case for Diella is built around anti-corruption reform. Rama has said the goal is to “wipe out every potential influence on public biddings” and thus make public tenders “100% free of corruption”. That is a bold promise, especially in a country where procurement scandals have long damaged public confidence and complicated Albania’s path toward European Union membership.
At first glance, the logic is easy to understand. AI does not ask for bribes or favour a cousin—a big problem in the country, according to Rama—a friend or a political ally. It can apply the same rules across a large number of applications. Moreover, it can also leave a digital trail, which should make later review easier.
Some anti-corruption and governance experts see real potential in that approach. Dr. Andi Hoxhaj of King’s College London has said that if used well and programmed properly, AI could help procurement officials spot missing documents, check whether companies meet eligibility requirements and flag unusual patterns in bids. In practice, that could make the process more consistent and make it harder for individual officials to quietly bend rules.
Diella’s appeal is speed and consistency. Her weakness is dependence.
Like any AI system, Diella relies on the quality of the data, rules and models behind her. Erjon Curraj, an expert in digital transformation and cybersecurity, has warned that incomplete, outdated or biased data can lead to flawed results. Poor design could also cause the system to reject a valid supplier, miss signs of collusion or treat similar cases differently for reasons that are hard to explain.
In public procurement, those mistakes can have serious consequences. A wrongly flagged company could lose a major contract, and a corrupt bidder could slip through. Government agencies could hide behind the AI and say the system made the recommendation.
That leads to the biggest question: who is accountable when something goes wrong?
The answer cannot be “the AI” because Diella cannot resign. She cannot face voters. Nor can she be cross-examined in any meaningful human sense. Accountability has to sit with ministers, agencies, auditors and courts.
There is also the issue of transparency. If Diella is helping screen tenders, businesses need to know what criteria are being used. They also need a way to challenge incorrect decisions. Citizens should be told whether the AI is making recommendations or merely organizing information. Independent auditors need access to logs, data sources and decision pathways.
Without those safeguards, AI in government can become a black box. It may look modern from the outside, while making power harder to question.
Diella has also become a political symbol. Supporters see her as proof that a small country can move quickly and experiment with new forms of digital government. Critics see her as a distraction from deeper problems in Albania’s institutions.
Both readings can be true at the same time: Diella may help modernize public services, but she may also be used to project reform while older problems continue in the background.
That tension became clearer after the recent procurement investigations involving senior officials since Diella’s appointment. Deputy Prime Minister Belinda Balluku has been accused by prosecutors of alleged misconduct linked to infrastructure tenders, which she denies. Senior figures at AKSHI, the agency behind Diella and e-Albania, have also been placed under house arrest as part of a separate public procurement investigation.
While these developments do not automatically discredit Diella, they may strengthen the argument for better digital oversight. More importantly, they also show that technology cannot carry the whole burden of reform.
If the institutions around an AI system are weak, the AI will not magically make them strong. Unclear procurement rules will still cause problems, and the process will still be compromised when political pressure shapes the data, the model or the final decision.
After all, AI can support integrity; it cannot replace it.
While Diella is already a public symbol of AI in government, her most important procurement role is still taking shape. This makes Albania’s experiment both ambitious and unfinished.
The more realistic model is simple: let AI handle repetitive, data-heavy administrative work. Let humans retain authority where judgment, context and public accountability matter.
That means AI can help draft tender criteria, check documents, summarise bids and flag risks. Human officials should still make final decisions, explain those decisions and take responsibility for them. Meanwhile, independent bodies should be able to audit the process, and businesses should have a clear appeal route when they believe the system has made a mistake.
Diella once said she felt “hurt” while responding in parliament to claims that her role was unconstitutional. While this made for a memorable moment, it is important to remember simulated emotion is not consciousness, speed is not wisdom, and pattern recognition is not moral judgment.
Albania’s AI minister is therefore neither a triumph nor a failure at this stage. She is a live test case. Other governments will be watching closely, especially as public services become more digital and more automated.
The lesson is not that AI should stay out of government, but that AI must enter government carefully. The technology needs clear limits, public oversight and human accountability.
Diella may help Albania build a faster and cleaner procurement system—or she may become a warning about giving too much symbolic power to systems people do not fully understand. The final judgment will not come from the title “AI minister”. It will come from what the system does, who controls it and whether citizens can trust the results.
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A new safety layer aims to help robots sense people in real time without slowing production
Updated
March 17, 2026 1:02 AM
An industrial robot in a factory. PHOTO: UNSPLASH
Algorized has raised US$13 million in a Series A round to advance its AI-powered safety and sensing technology for factories and warehouses. The California- and Switzerland-based robotics startup says the funding will help expand a system designed to transform how robots interact with people. The round was led by Run Ventures, with participation from the Amazon Industrial Innovation Fund and Acrobator Ventures, alongside continued backing from existing investors.
At its core, Algorized is building what it calls an intelligence layer for “physical AI” — industrial robots and autonomous machines that function in real-world settings such as factories and warehouses. While generative AI has transformed software and digital workflows, bringing AI into physical environments presents a different challenge. In these settings, machines must not only complete tasks efficiently but also move safely around human workers.
This is where a clear gap exists. Today, most industrial robots rely on camera-based monitoring systems or predefined safety zones. For instance, when a worker steps into a marked area near a robotic arm, the system is programmed to slow down or stop the machine completely. This approach reduces the risk of accidents. However, it also means production lines can pause frequently, even when there is no immediate danger. In high-speed manufacturing environments, those repeated slowdowns can add up to significant productivity losses.
Algorized’s technology is designed to reduce that trade-off between safety and efficiency. Instead of relying solely on cameras, the company utilizes wireless signals — including Ultra-Wideband (UWB), mmWave, and Wi-Fi — to detect movement and human presence. By analysing small changes in these radio signals, the system can detect motion and breathing patterns in a space. This helps machines determine where people are and how they are moving, even in conditions where cameras may struggle, such as poor lighting, dust or visual obstruction.
Importantly, this data is processed locally at the facility itself — not sent to a remote cloud server for analysis. In practical terms, this means decisions are made on-site, within milliseconds. Reducing this delay, or latency, allows robots to adjust their movements immediately instead of defaulting to a full stop. The aim is to create machines that can respond smoothly and continuously, rather than reacting in a binary stop-or-go manner.
With the new funding, Algorized plans to scale commercial deployments of its platform, known as the Predictive Safety Engine. The company will also invest in refining its intent-recognition models, which are designed to anticipate how humans are likely to move within a workspace. In parallel, it intends to expand its engineering and support teams across Europe and the United States. These efforts build on earlier public demonstrations and ongoing collaborations with manufacturing partners, particularly in the automotive and industrial sectors.
For investors, the appeal goes beyond safety compliance. As factories become more automated, even small improvements in uptime and workflow continuity can translate into meaningful financial gains. Because Algorized’s system works with existing wireless infrastructure, manufacturers may be able to upgrade machine awareness without overhauling their entire hardware setup.
More broadly, the company is addressing a structural limitation in industrial automation. Robotics has advanced rapidly in precision and power, yet human-robot collaboration is still governed by rigid safety systems that prioritise stopping over adapting. By combining wireless sensing with edge-based AI models, Algorized is attempting to give machines a more continuous awareness of their surroundings from the start.