February 2026 – PSA Parliaments

By Franklin De Vrieze.

Across democratic governance systems, parliaments are facing a paradox. Never before have there been so many technological tools promising to improve legislative scrutiny, evidence use, and public engagement. Yet never has the gap between the pace of technological change and the capacity of democratic institutions to respond felt so wide. This is not simply a story about adopting new software or experimenting with artificial intelligence (AI); it is about institutional transformation. The application of technology and AI in legislative scrutiny requires a fundamental change process in parliaments: one that reshapes data practices, organisational culture, and even how we conceptualise lawmaking itself.

The pacing problem: when governance moves slower than technology

The “pacing problem” captures the growing mismatch between rapid technological innovation and slower institutional adaptation and governance.

Westminster Foundation for Democracy (WFD) and POPVOX Foundation distinguish three interlocking layers of this challenge with regards to parliaments. First, the external pacing problem: parliaments struggle to keep up with technologies already embedded in society. Secondly, the intra-government pacing problem: executives are often early adopters of AI for service delivery, policy design, or enforcement, while legislatures lag behind in their ability to scrutinise these tools effectively, reinforming existing patterns of executive dominance. Thirdly, the internal pacing problem: parliamentary ICT systems, data structures, and workflows frequently remain fragmented, paper-based, or incompatible with modern analytical tools.

The risks of inaction are not abstract. According to the IPU World e-Parliament Report 2024, over 70% of parliaments globally now publish legislative information online, but fewer than half report having interoperable legislative data systems capable of supporting advanced analysis. As AI adoption accelerates in the executive and private sectors, these internal weaknesses can translate into real power asymmetries, further weakening legislative oversight and checks and balances.

How parliaments are already using AI

Despite these challenges, parliaments are not starting from zero. A growing number are experimenting with AI across administrative, legislative, and participatory functions.

On the administrative side, AI is increasingly used to automate transcription, translation, document classification, and summarisation. The European Parliament, for example, deploys eTranslation, speech-to-text systems, and automated indexing to manage multilingual debates and documents at scale. Similar AI functions are noted in the Canadian House of Commons.

Legislatively, AI tools are being applied to amendment analysis, legal consistency checks, and information retrieval. Italy’s Parliament has piloted AI-supported compliance checking of amendments against constitutional and legal constraints. The National Assembly of France has created tools using open data to model fiscal and social impacts and to compare draft bills with existing legislation.

Perhaps the most comprehensive example is Brazil’s Ulysses Suite, an integrated parliamentary AI ecosystem supporting everything from bill analysis to citizen interaction. These cases reflect a broader trend: many parliaments are piloting AI for legislative research, amendment tracking, and committee support.

Yet experimentation alone does not equal transformation. Many pilots remain isolated, dependent on individual champions, or constrained by legacy systems and procurement rules.

Technology across the legislative cycle

The potential of AI becomes clearer when viewed across the full legislative cycle. As highlighted in the Course Manual for the Certified Course on Legislative Scrutiny and Technology, technology is already reshaping each phase of lawmaking.

During legislative drafting, AI-assisted tools can analyse vast corpora of statutes and case law, suggesting language aligned with existing norms and reducing ambiguity. This supports consistency without replacing human judgment.
In ex-ante impact assessment, predictive modelling and data analytics allow parliaments to interrogate the likely economic, social, or environmental consequences of proposed legislation. Such tools can surface unintended effects earlier in the process, strengthening evidence-based scrutiny.
Citizen engagement is also being transformed. Digital platforms enable large-scale consultations, while AI can help analyse submissions, identify patterns, and surface underrepresented perspectives. This is particularly valuable as consultation volumes increase beyond what manual analysis can reasonably handle. Some argue for a path of Augmented Deliberation regarding citizen-initiated mechanisms for democratic participation, including a governance roadmap of digital guardrails such as AI watermarking, public-interest AI platforms, and independent algorithmic audits.
Finally, in post-enactment analysis, data analytics can track implementation and outcomes, support post-legislative scrutiny and close feedback loops between lawmaking and lived experience.

These applications demonstrate that AI does not sit at the margins of parliamentary work. It intersects with core legislative functions.

The centrality of explainability

The opportunities are significant, but so are the risks. AI evolves faster than parliamentary cycles, creating persistent regulatory lag. Existing standing orders and parliamentary procedures rarely anticipate automated analysis or algorithmic support. Capacity gaps mean expertise is often concentrated in a handful of staff or external vendors, raising dependency risks.

There are also well-documented technical and ethical challenges: bias in training data, errors and “hallucinations” in generative AI, data protection concerns when handling sensitive parliamentary or constituency information, and the growing threat of AI-enabled disinformation through synthetic submissions, as analysed by OECD, among others.

Across all these risks, one principle stands out: explainability. As Bruce Schneier and Nathan Sanders have argued in their book “Rewiring Democracy”, democratic institutions cannot rely on systems they do not understand. If MPs and staff cannot interrogate how an AI tool reached a conclusion, its outputs cannot legitimately inform legislative scrutiny. Explainability is therefore not a technical luxury but a democratic requirement.

AI adoption is a change process, not a tech project

Too often, AI adoption is framed as a procurement or IT challenge. In reality, it is an institutional change process. Deploying tools without addressing underlying data quality, governance, skills, and culture will at best produce marginal gains, and at worst undermine trust.

Effective change requires attention to at least six interlinked elements: strategy, prioritisation, implementation, governance, training, and coordination. It involves iterative piloting rather than “big bang” rollouts; cross-parliamentary governance bodies rather than siloed initiatives; and continuous learning rather than one-off training.

Data governance is foundational. Without legislature-wide data maps, data management plans, and interoperable systems, AI outputs will be unreliable or biased. Treating data as a strategic asset is a precondition for any meaningful AI readiness.

Crucially, this change process also invites deeper reflection. Rethinking lawmaking in terms of “law as code”, exploring how digital tools reshape legislative design, and reimagining human oversight so that humans remain firmly “in the loop” are all parts of the transformation.

The theory of organizational change by sociologist Everett Rogers, called the Diffusion of Innovations, points at different categories how people adapt to proposed changes. In any organization, including in parliaments, some are innovators, early adapters, early majority, late majority and the laggards. The innovators are often in a minority, but their approach will determine if the majority adapts and accepts the proposed changes. Similar categories on people’s approach to change applies to parliaments when introducing AI in the parliamentary workspace.

Frameworks to guide the journey

Parliaments do not have to navigate this alone. The Guidelines for AI in Parliament, published by the WFD, provide a practical framework covering ethics, governance, capacity, and implementation. Complementing this, the IPU’s Maturity Framework for AI in Parliaments offers a self-assessment tool across six levels, from “initial” awareness to “leadership”, where parliaments act as global benchmarks. The UK Parliament has issued guidance to its Members on the use of generative AI tools.

Together, these frameworks suggest a pragmatic path forward: start with pilots, invest in data foundations, prioritise explainable systems, learn from peers, and embed AI within transparent, ethics-driven governance structures.

Bridging expertise: lawmaking, technology, and parliamentary strengthening

Finally, successful transformation depends on people as much as systems. One of the clearest lessons from comparative practice is the need to connect three communities that too often operate separately: lawmaking experts, technology specialists, and parliamentary strengthening practitioners.

This was the guiding logic behind the January 2026 Certified Course on Legislative Scrutiny and Technology, which deliberately brought these three perspectives together. Hence, it was co-organized by leaders in each of these three fields: Institute of Advanced Legal Studies (IALS) of the University of London, Popvox Foundation and WFD. Legislative quality scholars, parliamentary officials, technology specialists, and democracy practitioners all contributed to a shared understanding: AI in parliament is not just about efficiency, but about safeguarding democratic legitimacy in an age of acceleration.

The rise of AI and legislative technology is not merely an administrative upgrade. It is a fundamental institutional challenge. If parliaments fail to adapt, the pacing problem will deepen, oversight will weaken, and democratic accountability will erode. If they succeed, AI can become a powerful ally in strengthening scrutiny, transparency, and public trust.

About the author

Franklin De Vrieze is the Head of Practice Accountability at the Westminster Foundation for Democracy.

By Cristina Leston-Bandeira.

How does one write about someone who you never thought would not be here? How do you put on paper how much that person meant to you? Contrary to David, I’m terrible at writing; he would know what I want to say, without me having to say it.

For no particular reason or design, David Judge became a sort of mentor to me – and this happened without either of us thinking about it, but simply because he was such an extraordinary person and such a pleasure to work with. He was a major intellectual force in parliamentary studies, having looked at pretty much every angle well before many others, just not making much of a fuss about it, whilst also being a wonderful and kind person.

Representation, the incongruities of democratic representation, and theory would become his preferred focus, but he addressed pretty much everything else in parliamentary studies. From his seminal study on petitions in 1978 and his PhD on backbench specialisation in the UK Parliament, to his landmark The Parliamentary State, his series of books on the European Parliament, and our recent co-edited book on Reimagining Parliament, David had an eye to spot what really mattered. Also, he understood intuitively why it mattered to study different legislatures.

And yet, talking to him, you’d never get a sense of the giant scholar he was. He was never one for self-promotion and as much of a self-deprecating academic as there ever was, as illustrated by his responses to the ‘Urgent Questions’ feature of the PSA Parliaments specialist group.

The first time I met David was in Manheim in 1999 at an ECPR Joint Workshop he had put together with Gabriella Ilonszki (Corvinus University of Budapest). I was a young PhD student, away from my 2-year-old son, doing the stuff that we need to do as academics, presenting work at conferences; and very unsure that I had anything to say, especially in a workshop full of big names such as David and Michael Rush (another lovely man and huge in parliamentary studies, now also sadly gone). David obviously put me totally at ease, in a very discreet way, simply because he was kind and he understood what it meant to be unsure and to be away from your young child. Something that not many male academics understood in the late 1990s.

A few years went by, and David was less present in academic circles because he became Head of Department at Strathclyde University’s School of Government. I never worked at Strathclyde, but I know how dedicated he was to the role and how it took him away from the research and writing he so loved. He had the good sense to take early retirement and regain time for thinking and writing.

He should have been just enjoying his very well deserved retirement of course, but he kept answering the call to do more. He enjoyed the challenge of new ideas, whilst making the most of being away from academia as such. It was thanks to this that I had the privilege to work with him and co-author a couple of articles and co-edit a book. He also kept a close eye on what was happening and every so often would email me with ideas of things that needed pursuing.

To talk of David without mentioning his Lorraine, and Ben and Hannah, though, is not to mention David at all. David was so proud of his family. Every opportunity was good enough to mention Lorraine and her hope of travel and time away from work; the immense pride in his children, the repairs in Hannah’s flat, Ben’s wedding. They were all always just next to David.

The last time David and I met in person was at the Political Studies Association annual conference hosted by Strathclyde University, in 2024. Towards the end of the conference, a panel didn’t sound too appealing and David and I just sat in the corridor chatting; chatting about this and that, past colleagues, academia, family (always family), and yet again I thought what an incredible man he was. A foremost scholar in parliamentary studies whilst incredibly caring and generous.

Whenever I needed advice, whenever things were difficult, I always knew I could count with David’s support. He’d understand, he’d know what to say. One of the last things he told me was to slow down and retire early. You never know what’s ahead and, as Lorraine always reminded him, there is so much more out there than work. And yet, it is thanks to work that David leaves such a huge scholarly legacy. I shall miss him deeply; his generosity, his openness to ideas, his wise perspective over things, his reminder that what really matters are people; wouldn’t academia be so much better if we were all a bit more liked David Judge? Except that he would have been horrified to know I’ve written this;).

About the author

Cristina is a Professor of Politics at the University of Leeds.