Suzanne Ellison is Head of Product at Lloyds Banking Group, leading innovation and delivery of AI-powered solutions. With over 15 years at Lloyds, Suzanne has championed a customer-first approach to technology implementation, building and leading multi-disciplinary teams of up to 300 professionals.

Her journey to technology leadership took an unconventional path. After leaving school at 16, Suzanne worked in insurance, studied business at night school and then went on to a computer science program at the University of Salford, where she earned a first-class degree. She joined HBOS (now part of Lloyds Banking Group) through its graduate scheme, progressing through technical roles before moving into scale delivery and product management.

Suzanne will be speaking at DTX Manchester, taking place on 2nd and 3rd April at Manchester Central.

The following interview has been edited for length and clarity.

Q: What will you be speaking about at DTX Manchester and how does this align with this year's theme: Innovation with Integrity | Driving Value, Delivering Purpose?

At DTX Manchester, I'll be discussing how we create and execute effective AI action plans at Lloyds Banking Group. My perspective bridges business and technology – I understand business needs, commercials and technical possibilities, which is crucial for AI implementation to create value beyond proof of concept.

For me, innovation with integrity means avoiding technology for technology's sake. It's about finding genuine business or customer problems that AI can solve, delivering real value rather than just impressive use cases.

I'll share insights from our scaled AI implementations, including our knowledge management solution now used by 20,000 colleagues. These aren't just tests but working systems delivering measurable benefits. I take a no-nonsense approach to discussing what's gone well and what's been challenging – offering practical insights into extracting value from AI capabilities while navigating adoption, testing and scaling hurdles.

Q: How will your session help attendees balance technological advancement with purposeful, responsible innovation?

Most of our AI solutions support colleagues who serve customers, rather than for customers directly. This creates an interesting perspective on purposeful innovation and also allows us to control risk.

Take our knowledge management solution used by customer-facing teams. These colleagues want to engage in quality, empathetic conversations with customers without stressing about processes or procedures. For example, our team that handles bereavement calls – if they're distracted about where to find information or what documentation is needed, it could potentially impact their ability to show empathy during these sensitive conversations.

Our AI provides information in a clear and straightforward way, giving colleagues what they need at their fingertips without searching through procedural documentation. This allows them to focus on the human elements of customer interaction rather than process mechanics.

As for responsible innovation, AI is only as good as your data. If your data quality is poor, the AI will provide incorrect information. We've developed practical approaches to data cleansing, quality management and setting appropriate expectations. People tend to expect AI to be infallible – ironically holding machines to higher standards than humans – which requires careful messaging around capabilities and limitations.

Q: If you could offer three takeaways from your speaking session, what would they be?

First, focus on tech for customer and business value, not tech for tech's sake. There are countless proofs of concept and exploratory projects, but the real challenge is managing senior executive appetite while delivering valuable use cases with measurable impact.

Second, manage your expectations because AI is only as good as your data. If your data is flawed, the outputs will be too. There's significant work in data preparation, cleansing and quality management before AI can deliver reliable results.

Third, test thoroughly and implement appropriate guardrails for production systems. We've found that people forgive human errors more readily than AI mistakes. When a manager provides incorrect information, there's natural forgiveness, but if AI delivers wrong answers, the reaction is much more severe.

Q: What are you looking forward to at DTX Manchester?

I'm particularly excited about connecting with the Manchester tech community. Lloyds has a significant hub in Manchester, and we're delivering substantial AI technology and digital journeys for the bank.

I'm actively involved in the local tech scene and partnerships, including our community partnership with DigitalHer, a non-profit organisation part of Manchester Digital. Events like DTX Manchester strengthen these community connections while providing opportunities to learn from others in the tech space.

I also hope to strengthen Lloyds' visibility in Manchester's tech ecosystem and make valuable connections with others in the space. We’re the UK's biggest digital bank and want to demonstrate our leadership in the tech and data space, with initiatives like our No Ordinary Tech Podcast – which has topped the tech podcast charts.

I'm naturally curious, so I look forward to hearing how others approach AI and digital transformation. These perspectives often spark new ideas for innovation at Lloyds. The opportunity to share experiences, challenges and solutions with peers across different industries is invaluable, particularly in rapidly evolving fields like AI.

Suzanne Ellison will be speaking at DTX Manchester, taking place on 2nd and 3rd April at Manchester Central. For more information and to register – for free – please visit: https://dtx-manchester-2025.reg.buzz/