AI for Barristers
Designed for barristers, Heads of Chambers and senior decision-makers, this course provides in-depth insight into AI risks, regulatory frameworks, and practical implementation across chambers and barristers’ practices - created in line with the BSB's guidance on AI for the Bar.
Duration
1.5 Hours
Lessons
7
CPD Hours
1.5
Certificate
On Completion
WHAT YOU WILL LEARN
Six outcomes from this training
Understand what AI is as an umbrella term for different technologies, its development in recent years, and the key terminology that senior leaders in chambers need to know
Analyse current legal frameworks regulating AI, including the EU AI Act and UK GDPR, and the implications these have for both chambers and members
Identify, assess, and manage AI-related risks both before and after deployment across chambers, including confidentiality, data protection, and accuracy risks
Understand the principles of responsible AI use and your role in ensuring AI tools are used in a compliant and appropriate way
Gain an overview of the practical benefits of AI use within chambers, including the main providers already serving the Bar and the competitive advantages they offer
Recognise common AI use cases for barristers, and understand the case-specific risks that members need to be aware of in practice
About this training
AI is no longer a future concern for chambers. AI technology is already being used by 89% of lawyers in the UK, and the regulatory framework governing it is developing rapidly. For all barristers and chambers senior leadership teams, the question is not whether to engage with AI but how to do so in a way that manages the risks and makes the most of the opportunities it presents.
This advanced course is designed to go beyond the fundamentals, and to cover the regulatory landscape, risk assessment and management, responsible use obligations at a leadership level, and practical AI implementation across chambers. It equips barristers, and those running chambers, with the knowledge to develop policy, manage risk, and position their set to benefit from AI as the profession evolves.
Key topics
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1
The fundamentals of AI
-
2
AI’s risks to the Bar and you in practice
-
3
Your duties and responisbilities to clients
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4
Regulatory and ethical compliance considerations
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5
Real-life scenarios and applications
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6
Responsible use obligations
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7
The AI tech stack
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8
Implementing AI across chambers
Frequently asked questions
Artificial intelligence (AI) refers to computer systems or software that can perform tasks that normally require human intelligence. These include problem solving, language understanding, visual perception, learning, and decision-making. AI systems can be trained to recognise patterns, make predictions, and adapt based on new data.
Yes, our training has been designed to align with the BSB's AI guidance, published in May 2026. Barristers need make themselves aware of the risks of AI, how it can be used, how to spot AI. also they should have appropriate framework and governance structures in place. Ultimately, barristers must have training to understand the risks involved and evidence that they have audited their practice, and remedy any risks.
Barristers should opt for a risk based approach, per page 4 of the BSB's May 2026 guidance. They must 1. have training to understand risks 2. evidence that they have audited their practice with any risks being highlighted and remedied.
Generative AI is a type of AI model that can create new content, such as text, images, audio, or video, rather than simply analysing existing data. Tools like ChatGPT and Microsoft Copilot are examples of generative AI that are already in use across the legal sector.
AI works by analysing large sets of data, identifying patterns, and learning from them to make predictions or decisions. It relies on machine learning and deep learning models to produce results for its users. The quality and accuracy of those results depend heavily on the data the system was trained on.
Machine learning is a branch of AI that enables systems to learn from data without being explicitly programmed. Instead of following fixed rules, machine learning algorithms find patterns in historical data and use those patterns to make predictions or recommendations.
Deep learning is a branch of AI and machine learning that uses artificial neural networks to learn from large amounts of data. These networks are made up of many layers, allowing a system to detect complex patterns and relationships automatically without being explicitly programmed to do so.
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Briefed works with chambers on AI policy, governance, and advisory support. If your set needs more than training, we can help.