Day One - Monday 29 June 2026

Click on each stream card above the programme to view the each sessions streams. 
Click on the button below to view the day two programme.

Please note: This programme is subject to change

07:30 — 09:00
Welcome: registration, refreshments and exhibition

Welcome to the 2nd Annual Global AI Conference 2026!

Collect your badge and head to level 3 to enjoy refreshments, explore the exhibition hall, and connect with our exhibitors. Grab a coffee and take a moment to settle in before diving into the day's exciting programme.  

09:00 — 09:30
Welcome day one and opening keynote

Ground Floor, Churchill Auditorium

Join us as we officially open day one of our 2nd Annual Global AI Conference 2026. The day begins with a warm welcome and inspiring keynote to set the tone for two-days of learning, exploration and collaboration.  

09:00 - 09:05 Opening remarks - Dr Stephen Harden, President of the RCR

09:05 Keynote address: To be announced

09:45 — 11:15
Session 1: How is radiology AI education evolving

Discover how to get started using AI in clinical practice and hear the RCR's perspective on integrating AI as part of the curriculum and exams in the future. This session offers practical guidance and insights into how AI may shape the curriculum and assessment landscape.

Dr Nicky Thorp picture
Dr Nicky Thorp
09:45 — 09:50
Welcome and introductions
Dr Nicky Thorp picture
Dr Nicky Thorp
09:50 — 10:10
Introduction to AI faculty training courses

This session introduces the AI courses available from the Royal College of Radiologists, helping attendees understand what is on offer and how they can enrol on the courses and when these will be. It will provide a practical guide to the different courses, outlining the content, describing who the course are aimed at, and explaining how they can support teaching and professional development.

Dr Thomas Booth picture
Dr Thomas Booth
10:10 — 10:30
AI in the RCR Clinical Radiology Curriculum

This talk will explore where training of AI sits within the RCR Clinical Radiology curriculum, including who we should train, what we should train them, and how we should train.

Dr David Little picture
Dr David Little
10:30 — 10:50
AI in medical education: positives and pitfalls

Examples of positive experiences of AI in education together with current concerns for the future.

Dr David Marshall picture
Dr David Marshall
10:50 — 11:15
Panel discussion and close
11:15 — 11:45
Morning break: exhibition and poster viewing, refreshments and networking

Level 3, Exhibition - Fleming, Whittle and Britten 

11:45 — 13:15
Session 2: AI Fellowship Programmes in the UK - Case studies and experiences

Do you know how many training oppportunities there are to deepen your exposure to imaging-AI and it's clinical potential? In this session, you'll hear directly from Fellows who have completed well-established training Fellowships, including Topol Fellows, NHS Clinical AI Fellowship, and others. 

Dr Claire Mallinson picture
Dr Claire Mallinson
11:45 — 11:50
Welcome and introductions
Professor Gerald Lip picture
Professor Gerald Lip
11:50 — 12:00
Clinical deployment of artificial intelligence autosegmentation (Limbus AI) in a radiotherapy imaging workflow

Experience of the NHS Clinical AI Fellowship and pearls and pitfalls from my experience of implementing a commercial AI software into the NHS.

Ms Akriti Nanda picture
Ms Akriti Nanda
12:00 — 12:10
NHS Clinical AI Fellowship: Design and Evaluation in a Multi-Site NHS AI Trial

This session will reflect on the experience as an NHS Clinical AI Fellow contributing to a multi-site cluster randomised AI trial. It will explore practical considerations in trial design, outcome development, evaluation frameworks, and the realities of cross-site implementation within the NHS.

Mr Tom Nash picture
Mr Tom Nash
12:10 — 12:20
Feasibility testing of MIDI AI tool in DGH setting
Dr Michael Adofo Kwakye picture
Dr Michael Adofo Kwakye
12:20 — 12:30
Radiology - AI surveillance
D
Dr Jesus Perdomo
12:30 — 12:40
Clinical oncology: auto contouring
12:40 — 12:50
Scaphoid fracture project
Dr Aoife Fox picture
Dr Aoife Fox
12:50 — 13:00
Challenges and lessons learnt in deploying deep learning tools in neuroradiology

This talk will focus on how Dr Nikunj Davda used his clinical AI fellowship to overcome barriers to deplyoment and formulated strategies to successfully deploy AI for research at an NHS trust.

Dr Nikunj Davda picture
Dr Nikunj Davda
13:00 — 13:10
Public health
D
Dr Varthani Kirupanandan
13:10 — 13:15
Panel discussion and close
13:15 — 14:15
Lunch break: exhibition and poster viewing, refreshments and networking

Level 3, Exhibition Hall - Fleming, Whittle and Britten 

14:15 — 15:45
Session 3: Academic medicine and AI – threat or opportunity?

Will radiologists still be needed in the future? Join this thought-provoking discussion exploring the evolving role of medical imaging professionals in the age of AI. We’ll examine the competencies required to work effectively with AI tools and consider how the profession may adapt as technology advances.

Professor David Strain picture
Professor David Strain
14:15 — 14:20
Welcome and introductions
14:20 — 14:40
Benefits of investing in AI education
M
Ms Fiona Fraser
14:40 — 15:00
Teaching AI for radiology applications
15:00 — 15:20
To be announced
15:20 — 15:45
Panel discussion and close
15:45 — 16:30
Afternoon break: exhibition and poster viewing, refreshments and networking

Level 3, Exhibition - Fleming, Whittle and Britten 

16:30 — 17:15
Keynote address: The future of radiology in the era of artificial intelligence

Artificial intelligence (AI) is an incredibly powerful tool for building systems that support the work of radiologists. From its early roots in digital image analysis, AI has evolved into a key driver of innovation, developing machine learning methods to support healthcare decision making. This sparked high interest and explosive growth in the use of AI and machine learning methods to analyse medical imaging data.

These promising techniques create systems that perform some diagnostic tasks at the level of expert radiologists. The systems have the potential to provide real-time assistance to radiologists, thereby reducing diagnostic errors, detecting disease early, improving patient outcomes, and reducing costs.

This session will explore the origins of AI and its applications to medical imaging, define key terminology, and showcase examples of real-world applications that suggest how AI and large language models may change the practice of medicine.

We'll also address the key limitations and challenges of AI that may limit the application of these new methods. Finally, we will present a forward-looking model predicting how AI will affect the radiology workforce in the next five years.

Professor Curtis Langlotz picture
Professor Curtis Langlotz
17:15 — 18:15
Complimentary networking drinks reception and exhibition

Level 3, Exhibition Hall (Britten, Fleming and Whittle)

For those joining us in-person, we’re delighted to welcome you to our inclusive drinks reception. Enjoy refreshments, connect with fellow attendees, and continue conversations in a relaxed and welcoming settng.

18:15
Day one close
07:30 — 09:00
Welcome: registration, refreshments and exhibition

Welcome to the 2nd Annual Global AI Conference 2026!

Collect your badge and head to level 3 to enjoy refreshments, explore the exhibition hall, and connect with our exhibitors. Grab a coffee and take a moment to settle in before diving into the day's exciting programme.  

09:00 — 09:30
Welcome day one and opening keynote

Ground Floor, Churchill Auditorium

Join us as we officially open day one of our 2nd Annual Global AI Conference 2026. The day begins with a warm welcome and inspiring keynote to set the tone for two-days of learning, exploration and collaboration.  

09:00 - 09:05 Opening remarks - Dr Stephen Harden, President of the RCR

09:05 Keynote address: To be announced

09:45 — 11:15
Session 1: Green and quantum computing

AI is here to stay in our clinical and research practice, but as we move to increasingly complex machine learning models, how do we keep abreast of the raw computational cost of AI, and the huge energy requirements? In this session, we will examine this question from two angles. The first is to look forward at the hope of quantum computing, which offers unique potential in image acquisition and numerical optimisation that underpins our workflow. The second is to look at initiatives that optimise our use of high performance computing through better choice of task appropriate algorithms.

09:45 — 09:50
Welcome and introductions
09:50 — 10:10
An idiots guide to quantum computing
10:10 — 10:30
The future of greener algorithms
Professor Michael Inouye picture
Professor Michael Inouye
10:30 — 10:50
Sustainable AI for radiology
Professor Andrea Rockall picture
Professor Andrea Rockall
10:50 — 11:15
Panel discussion and close
11:15 — 11:45
Morning break: exhibition and poster viewing, refreshments and networking

Level 3, Exhibition - Fleming, Whittle and Britten 

11:45 — 13:15
Session 2: Hidden AI - how AI is changing your workflows

Join our multi-industry session to uncover what is really going on behind the scenes we need to be aware of. We are increasingly introducing AI in our NHS hospitals without necessarily knowing we are procuring them as they come part of a package. Are we aware of this, how is it happening, what do we need to know?

In addition, industry partners who provide our technologies are using AI to enhance clinical workflows, both in software and imaging hardware. The session offers a unique opportunity to learn about best practice in AI development across sectors, and to understand how these innovations are shaping the future of care delivery from key industry partners.

11:45 — 11:50
Welcome and introductions
11:50 — 12:10
Embedded AI for streamlined clinical notes - the promise and the pitfalls
12:10 — 12:30
To be announced
12:30 — 12:50
AI - practical problem-solver in acute radiology

Successful implementation of AI for analysis of CT brain for trauma patients in the acute setting. This was followed by the implementation of the C-spine algorithm, both in close connection with neurology and ED doctors. Secondarily, we started with the PE algorithm, both for the acute cases as well as for oncology screening.  Not only TurnAroundTimes improved, but also the ED stay was significantly shortened.

D
Dr Annet Driessen-Waaijer
12:50 — 13:10
Reimagining triage - evidence from deploying autonomous AI in community care
13:10 — 13:15
Panel discussion and close
13:15 — 14:15
Lunch break: exhibition and poster viewing, refreshments and networking

Level 3, Exhibition Hall - Fleming, Whittle and Britten 

14:15 — 15:45
Session 3: Imaging AI theranostics

Discover how artificial intelligence is transforming oncology by driving innovation across drug development, delivery, and imaging. This session explores the potential of AI to inform the design of novel drug radiation conjugates and optimise their delivery and response monitoring.

You'll learn how AI tools are being applied to target DNA damage repair mechanisms in cancer, offering new avenues for precision treatment. Gain insights into the clinical impact of these technologies and how they are reshaping therapeutic strategies and patient outcomes.

Professor Maria Hawkins picture
Professor Maria Hawkins
14:15 — 14:20
Welcome and introductions
14:20 — 14:40
Targeted Radionuclide Therapy - where we are in the UK and how AI might help

This session will provide an overview of recent developments in targeted radionuclide therapy, what is being done to support development of this treatment modality in the UK, and consider how AI might help to personalise treatment so that every patient derives the maximum possible benefit.

Professor Jon Wadsley picture
Professor Jon Wadsley
14:40 — 15:00
How computation is being used to design targeted therapies affecting DNA damage response
15:00 — 15:20
Labelling morphological profiles from high-throughput glioblastoma compound screen for supervised learning property prediction

Image-based profiling assay data (cell painting) has increasingly been used to assess the impact of compounds’ cellular treatments. An uncharted use for this data is its incorporation into supervised learning tasks for molecular property prediction. Here, I present a protocol that uses cell painting fingerprints for clustering and labelling compounds according to drug effect. The methodology is deployed on 1,280 compounds from a LOPAC library assay of glioblastoma multiforme (GBM), a cancer of high complexity to treat due to its heterogeneity, with no new therapeutic candidates delivered to patients in over two decades. The computational screening capabilities of the pipeline are expanded by training binary classifiers of cellular phenotype over the labelled data, transforming the structural compound representations of each cluster into a physicochemical descriptor space. The property predictions are assessed on the C3L library, a chemically diverse set of 786 structures. The result is an end-to-end machine learning (ML) pipeline to test compounds for their probability to be GBM drug candidates.

Dr Vanessa Smer Barreto picture
Dr Vanessa Smer Barreto
15:20 — 15:45
Panel discussion and close
15:45 — 16:30
Afternoon break: exhibition and poster viewing, refreshments and networking

Level 3, Exhibition - Fleming, Whittle and Britten 

16:30 — 17:15
Keynote address: The future of radiology in the era of artificial intelligence

Artificial intelligence (AI) is an incredibly powerful tool for building systems that support the work of radiologists. From its early roots in digital image analysis, AI has evolved into a key driver of innovation, developing machine learning methods to support healthcare decision making. This sparked high interest and explosive growth in the use of AI and machine learning methods to analyse medical imaging data.

These promising techniques create systems that perform some diagnostic tasks at the level of expert radiologists. The systems have the potential to provide real-time assistance to radiologists, thereby reducing diagnostic errors, detecting disease early, improving patient outcomes, and reducing costs.

This session will explore the origins of AI and its applications to medical imaging, define key terminology, and showcase examples of real-world applications that suggest how AI and large language models may change the practice of medicine.

We'll also address the key limitations and challenges of AI that may limit the application of these new methods. Finally, we will present a forward-looking model predicting how AI will affect the radiology workforce in the next five years.

Professor Curtis Langlotz picture
Professor Curtis Langlotz
17:15 — 18:15
Complimentary networking drinks reception and exhibition

Level 3, Exhibition Hall (Britten, Fleming and Whittle)

For those joining us in-person, we’re delighted to welcome you to our inclusive drinks reception. Enjoy refreshments, connect with fellow attendees, and continue conversations in a relaxed and welcoming settng.

18:15
Day one close
07:30 — 09:00
Welcome: registration, refreshments and exhibition

Welcome to the 2nd Annual Global AI Conference 2026!

Collect your badge and head to level 3 to enjoy refreshments, explore the exhibition hall, and connect with our exhibitors. Grab a coffee and take a moment to settle in before diving into the day's exciting programme.  

09:00 — 09:30
Welcome day one and opening keynote

Ground Floor, Churchill Auditorium

Join us as we officially open day one of our 2nd Annual Global AI Conference 2026. The day begins with a warm welcome and inspiring keynote to set the tone for two-days of learning, exploration and collaboration.  

09:00 - 09:05 Opening remarks - Dr Stephen Harden, President of the RCR

09:05 Keynote address: To be announced

09:45 — 11:15
Session 1: Regulation without the jargon: AI compliance for decision-makers

Navigating AI regulation shouldn't require a law degree. This session cuts through the complexity to deliver what procurement professionals and decision-makers actually need to know. We'll map the current regulatory landscape, from the EU AI Act to UK MDR updates, and translate dense policy into practical guidance.

Learn which regulations apply to your AI purchases, what compliance really looks like in practice, and how to ask the right questions of vendors. Whether you're procuring diagnostic algorithms or administrative tools, leave with a clear framework for making informed, compliant decisions without getting lost in regulatory weeds.

Dr Hugh Harvey picture
Dr Hugh Harvey
09:45 — 09:50
Welcome and introductions
09:50 — 10:10
EU AI Act and its implications on the UK
Professor Matthias May picture
Professor Matthias May
10:10 — 10:30
What NHS Trusts should look for when procuring AI
10:30 — 10:50
NHS-E approach to software and AI as medical devices
10:50 — 11:15
Panel discussion and close
11:15 — 11:45
Morning break: exhibition and poster viewing, refreshments and networking

Level 3, Exhibition - Fleming, Whittle and Britten 

11:45 — 13:15
Session 2: Beyond approval: managing AI risk across the clinical trial journey

This session bridges the gap between cutting-edge research and practical governance standards for AI safety. You'll discover how to manage risk at every stage of clinical trials, from protocol design through post-market surveillance. You'll gain actionable strategies for monitoring algorithm drift and safeguarding data integrity. Learn how to maintain safety as AI systems evolve in real-world settings, and walk away with practical tips for conducting robust AI trials that satisfy good clinical practice and regulators, while advancing responsible innovation.

Dr Amrita Kumar picture
Dr Amrita Kumar
11:45 — 11:50
Welcome and introductions
11:50 — 12:10
Post-market surveillance and monitoring
12:10 — 12:30
Setting up AI trials - EDITH study

The NIHR Health technology Assessment funded EDITH trial (Early Detection using Information Technology in Health) is testing whether or not one reader using AI can replace the standard two expert readers in the UK breast screening programme. In up to 30 sites 660,000 women will be recruited into one of three arms – AI replacing one reader, triage arm where low likelihood mammograms read by one reader and high likelihood read by two people compared to standard care. This talk will highlight the steps required to deploy AI within NHS Trusts describing real life examples where hold-ups occur and explore mechanisms to streamline governance and clinical safety processes.  

Professor Fiona Gilbert picture
Professor Fiona Gilbert
12:30 — 12:50
To be announced
12:50 — 13:15
Panel discussion and close
13:15 — 14:15
Lunch break: exhibition and poster viewing, refreshments and networking

Level 3, Exhibition Hall - Fleming, Whittle and Britten 

14:15 — 15:45
Session 3: The AI investment dilemma - when do healthcare systems break-even?

Healthcare leaders face mounting pressure to invest in AI, but when does it actually pay off? Drawing on a systematic review of health economic outcomes research in radiology AI, this session examines the evidence behind the promises.

We'll explore NICE's Early Value Assessments and rules-based frameworks that help decision-makers separate hype from genuine value. This session will highlight which AI applications demonstrate measurable ROI, what timelines are realistic for break-even, and how to evaluate economic claims critically. You'll discover practical tools for assessing whether AI investments will deliver both financial and clinical returns within your system and organisation.

14:15 — 14:20
Welcome and introductions
14:20 — 14:40
Are we missing the value? Considerations for outcomes and metrics in the economic evaluation of AI for radiology and diagnostics.

This session will present the findings from a recently published systematic literature review of economic evaluations of AI in radiology. A discussion of these findings will detail guidance on appropriate data collection when conducting economic evaluations of radiology AI, with the aim to support its adoption in clinical practice.

Miss Lucy Gregory picture
Miss Lucy Gregory
14:40 — 15:00
What NICE looks for in AI devices
15:00 — 15:20
AI health economics evaluation - breast / MSK
Dr Anna Barnes picture
Dr Anna Barnes
15:20 — 15:45
Panel discussion and close
15:45 — 16:30
Afternoon break: exhibition and poster viewing, refreshments and networking

Level 3, Exhibition - Fleming, Whittle and Britten 

16:30 — 17:15
Keynote address: The future of radiology in the era of artificial intelligence

Artificial intelligence (AI) is an incredibly powerful tool for building systems that support the work of radiologists. From its early roots in digital image analysis, AI has evolved into a key driver of innovation, developing machine learning methods to support healthcare decision making. This sparked high interest and explosive growth in the use of AI and machine learning methods to analyse medical imaging data.

These promising techniques create systems that perform some diagnostic tasks at the level of expert radiologists. The systems have the potential to provide real-time assistance to radiologists, thereby reducing diagnostic errors, detecting disease early, improving patient outcomes, and reducing costs.

This session will explore the origins of AI and its applications to medical imaging, define key terminology, and showcase examples of real-world applications that suggest how AI and large language models may change the practice of medicine.

We'll also address the key limitations and challenges of AI that may limit the application of these new methods. Finally, we will present a forward-looking model predicting how AI will affect the radiology workforce in the next five years.

Professor Curtis Langlotz picture
Professor Curtis Langlotz
17:15 — 18:15
Complimentary networking drinks reception and exhibition

Level 3, Exhibition Hall (Britten, Fleming and Whittle)

For those joining us in-person, we’re delighted to welcome you to our inclusive drinks reception. Enjoy refreshments, connect with fellow attendees, and continue conversations in a relaxed and welcoming settng.

18:15
Day one close
07:30 — 09:00
Welcome: registration, refreshments and exhibition

Welcome to the 2nd Annual Global AI Conference 2026!

Collect your badge and head to level 3 to enjoy refreshments, explore the exhibition hall, and connect with our exhibitors. Grab a coffee and take a moment to settle in before diving into the day's exciting programme.  

09:00 — 09:30
Welcome day one and opening keynote

Ground Floor, Churchill Auditorium

Join us as we officially open day one of our 2nd Annual Global AI Conference 2026. The day begins with a warm welcome and inspiring keynote to set the tone for two-days of learning, exploration and collaboration.  

09:00 - 09:05 Opening remarks - Dr Stephen Harden, President of the RCR

09:05 Keynote address: To be announced

09:45 — 11:45
Session 1: Real world deployment casefiles

A showcase of successful NHS and industry AI deployments that have moved from concept to clinic, exploring real-world impact, integration challenges, and lessons from those leading AI-enabled service transformation.

Professor Amanda Isaac picture
Professor Amanda Isaac
09:45 — 09:50
Welcome and introductions
09:50 — 10:10
From development to delivery – scaling the use of Ambient AI

Using an Ambient AI (or an AI scribe) solution to improve patient care and reduce clinician admin burden in multiple settings (hospital outpatients, community care, primary care, mental health, emergency room, and ambulance service settings); Describing the journey from problem, to early phase development and evaluation, to use case scaling, to delivery.

P
Professor Andrew Taylor
10:10 — 10:30
To be announced
10:30 — 10:50
AI in diagnostics

An update on delivery to date and future plans for scale and spread of AI in diagnostics across the NHS in England.

Dr Rhydian Philips picture
Dr Rhydian Philips
10:50 — 11:15
Panel discussion and close
11:15 — 11:45
Morning break: exhibition and poster viewing, refreshments and networking

Level 3, Exhibition - Fleming, Whittle and Britten 

11:45 — 13:15
Session 2: AI enabled cancer MDT

From imaging to histopathology and treatment planning, this session explores how AI is reshaping multidisciplinary cancer care, providing decision support, prognostic insight, and workflow efficiency across the patient pathway.

Dr James Wang picture
Dr James Wang
11:45 — 11:50
Welcome and introductions
11:50 — 12:10
AI powered prostate cancer detection MRI
12:10 — 12:30
AI in prostate biopsy diagnostics
12:30 — 12:50
The STELLA Project - an AI powered radiotherapy machine for low and middle income countries

This talk will provide an update on research undertaken into the design of a novel smat radiotherapy device that is aimed to enhance access to radiation therapy in low and middle income countries, and in rural areas of high income countries.

Professor Raj Jena picture
Professor Raj Jena
12:50 — 13:15
Panel discussion and close
13:15 — 14:15
Lunch break: exhibition and poster viewing, refreshments and networking

Level 3, Exhibition Hall - Fleming, Whittle and Britten 

14:15 — 15:45
Session 3 : Infrastucture for AI implementation and deployment

AI innovation can only move as fast as the infrastructure beneath it. In this session, leading experts share how scalable, secure and interoperable foundations, from federated datasets and clinical data platforms, enables safe, effective and equitable AI deployment across health systems. 

14:15 — 14:20
Welcome and introductions
14:20 — 14:40
Implementing artificial intelligence tools for chest diagnostics: lessons from a rapid, mixed-methods evaluation

This session will present key findings from the NIHR Rapid Service Evaluation Team's mixed-methods evaluation of implementing AI tools for chest diagnostics, as deployed through NHS England's AI Diagnostic Fund. We will discuss implementation approaches, impact on service delivery, resource use, and cost-effectiveness. We will discuss considerations for future implementation of AI in NHS services.

Dr Angus Ramsay picture
Dr Angus Ramsay
14:40 — 15:00
Reducing variability in imaging vetting using evidence‑based automation
15:00 — 15:20
Delivering diagnostic AI at scale - lessons from the AI diagnostic fund

The AI Diagnostic Fund (AIDF) has successfully deployed AI diagnostic support tools across over half of NHS hospital trusts in England, exceeding the original target of 40–50 trusts while delivering under budget at £19m. It is projected to significantly reduce turnaround times for priority lung cancer scans, benefiting many of the 43,000 patients diagnosed nationwide each year.  This presentation narrates the story of the AIDF from the early stages of policy making to the deployment and benefit realisation, highlighting key lessons that are informing plans for the next phase of scaled AI deployment in diagnostics across the NHS.

Mr Robert Dale picture
Mr Robert Dale
15:20 — 15:45
Panel discussion and close
15:45 — 16:30
Afternoon break: exhibition and poster viewing, refreshments and networking

Level 3, Exhibition - Fleming, Whittle and Britten 

16:30 — 17:15
Keynote address: The future of radiology in the era of artificial intelligence

Artificial intelligence (AI) is an incredibly powerful tool for building systems that support the work of radiologists. From its early roots in digital image analysis, AI has evolved into a key driver of innovation, developing machine learning methods to support healthcare decision making. This sparked high interest and explosive growth in the use of AI and machine learning methods to analyse medical imaging data.

These promising techniques create systems that perform some diagnostic tasks at the level of expert radiologists. The systems have the potential to provide real-time assistance to radiologists, thereby reducing diagnostic errors, detecting disease early, improving patient outcomes, and reducing costs.

This session will explore the origins of AI and its applications to medical imaging, define key terminology, and showcase examples of real-world applications that suggest how AI and large language models may change the practice of medicine.

We'll also address the key limitations and challenges of AI that may limit the application of these new methods. Finally, we will present a forward-looking model predicting how AI will affect the radiology workforce in the next five years.

Professor Curtis Langlotz picture
Professor Curtis Langlotz
17:15 — 18:15
Complimentary networking drinks reception and exhibition

Level 3, Exhibition Hall (Britten, Fleming and Whittle)

For those joining us in-person, we’re delighted to welcome you to our inclusive drinks reception. Enjoy refreshments, connect with fellow attendees, and continue conversations in a relaxed and welcoming settng.

18:15
Day one close
15:20 — 15:45
Panel discussion and close
07:30 — 09:00
Welcome: registration, refreshments and exhibition

Welcome to the 2nd Annual Global AI Conference 2026!

Collect your badge and head to level 3 to enjoy refreshments, explore the exhibition hall, and connect with our exhibitors. Grab a coffee and take a moment to settle in before diving into the day's exciting programme.  

09:00 — 09:30
Welcome day one and opening keynote

Ground Floor, Churchill Auditorium

Join us as we officially open day one of our 2nd Annual Global AI Conference 2026. The day begins with a warm welcome and inspiring keynote to set the tone for two-days of learning, exploration and collaboration.  

09:00 - 09:05 Opening remarks - Dr Stephen Harden, President of the RCR

09:05 Keynote address: To be announced

09:45 — 11:45
Session 1: To be announced
11:15 — 11:45
Morning break: exhibition and poster viewing, refreshments and networking

Level 3, Exhibition - Fleming, Whittle and Britten 

11:45 — 13:15
Session 2: AI in clinical practice - interactive taster sessions
Dr Thomas Booth picture
Dr Thomas Booth
11:45 — 12:00
Welcome and introductions
12:00 — 12:30
Taster session 1 – deep learning explained

This taster session is drawn from the RCR's acclaimed Clinical Radiology AI Course 1: AI Fundamentals for Imaging and Healthcare. It aims to provide an accessible introduction to the technical concepts underpinning modern AI.

Dr Matthew Townend picture
Dr Matthew Townend
12:30 — 13:00
Taster session 2 – understanding data bias

When AI fails in clinical practice, bias is often the reason. This session examines where bias emerges in healthcare datasets, how it affects performance across patient groups, and what clinicians must do to safeguard safe implementation.

Dr Sonam Vadera picture
Dr Sonam Vadera
13:00 — 13:15
Panel discussion and close
13:15 — 14:15
Lunch break: exhibition and poster viewing, refreshments and networking

Level 3, Exhibition Hall - Fleming, Whittle and Britten 

14:15 — 15:45
Session 3: Guiding the next generation: radiology training and AI

At the request of Radiology Residents, a selection of speakers with significant experience in medical education to discuss training as well as AI. We explore widening participation, how to teach and learn, how residents can get involved with AI, day to day implications for clinical practice and how this may affect training. We welcome you to join this education focused session and contribute with our speakers!

Dr Honida Mansour picture
Dr Honida Mansour
14:15 — 14:20
Welcome and introductions
14:20 — 14:35
What residents need to know in the next 5 years
14:35 — 14:50
Day to day clinical impact of AI, how will this affect training?
14:50 — 15:05
To be announced
15:05 — 15:20
Introduction to coding for residents
Dr Daniel Fascia picture
Dr Daniel Fascia
15:20 — 15:45
Panel discussion and close
15:45 — 16:30
Afternoon break: exhibition and poster viewing, refreshments and networking

Level 3, Exhibition - Fleming, Whittle and Britten 

16:30 — 17:15
Keynote address: The future of radiology in the era of artificial intelligence

Artificial intelligence (AI) is an incredibly powerful tool for building systems that support the work of radiologists. From its early roots in digital image analysis, AI has evolved into a key driver of innovation, developing machine learning methods to support healthcare decision making. This sparked high interest and explosive growth in the use of AI and machine learning methods to analyse medical imaging data.

These promising techniques create systems that perform some diagnostic tasks at the level of expert radiologists. The systems have the potential to provide real-time assistance to radiologists, thereby reducing diagnostic errors, detecting disease early, improving patient outcomes, and reducing costs.

This session will explore the origins of AI and its applications to medical imaging, define key terminology, and showcase examples of real-world applications that suggest how AI and large language models may change the practice of medicine.

We'll also address the key limitations and challenges of AI that may limit the application of these new methods. Finally, we will present a forward-looking model predicting how AI will affect the radiology workforce in the next five years.

Professor Curtis Langlotz picture
Professor Curtis Langlotz
17:15 — 18:15
Complimentary networking drinks reception and exhibition

Level 3, Exhibition Hall (Britten, Fleming and Whittle)

For those joining us in-person, we’re delighted to welcome you to our inclusive drinks reception. Enjoy refreshments, connect with fellow attendees, and continue conversations in a relaxed and welcoming settng.

18:15
Day one close