Conference Day Two - Wednesday 2nd April
This agenda is subject to change.
As the UK Government and regulatory bodies drive forward with new AI guidance, businesses must stay agile and compliant in an increasingly complex legal environment. This panel will offer critical insights into the latest developments, compliance strategies, and how companies can proactively prepare for regulatory shifts that impact generative AI innovation and operations. Attend to delve into:
Discover how the latest generative AI technologies can transform your business, streamline operations, and drive innovation at scale.
The publishing industry is undergoing a profound transformation as generative AI reshapes content creation, distribution, and monetization strategies. The Financial Times, a bastion of quality journalism, is navigating this sea change by balancing innovation with ethical considerations and brand integrity. This journey illuminates the critical importance of AI literacy and fluency in driving sustainable progress while safeguarding core values in the rapidly evolving media landscape. Attend to explore how they are:
• Implementing comprehensive AI literacy programs to empower staff across all departments
• Developing robust governance frameworks that ensure ethical AI use and brand protection
• Creating AI-driven product strategies that align with audience needs and value-add goals
As the BBC integrates GenAI into its content creation process, the organization faces unique challenges around trust, transparency, and combating misinformation. In today’s fast-paced news landscape, ensuring that AI-driven content meets the highest ethical standards is critical to maintaining audience trust. This session will explore how the BBC is operationalizing GenAI to enhance content while addressing the complexities of AI governance in media.
In the evolving landscape of generative AI, Bupa has been at the forefront of innovation, transforming early-stage ideas into actionable pilots. With excitement and confusion surrounding the technology, Bupa’s approach emphasizes building capabilities, fostering trust, and driving responsible AI initiatives. This session dives into how Bupa is developing a GenAI strategy, from ideation to production, while navigating cloud maturity, data trust, and disruptive innovation.
• Building cloud capability and foster trust in business data for AI tools.
• Encouraging early-stage ideation through sandbox environments and democratized innovation processes.
• Implementing responsible AI practices to ensure ethical and trustworthy customer-facing solutions.
Deepfakes present a dual-edged sword of innovation and risk, posing unique challenges for media integrity, consumer trust, and enterprise security. In this session, Ofcom will share recent findings on the strengths and vulnerabilities of deepfake tools, including watermarking techniques, metadata schemes and content labelling methods.. Attend to delve into:
With GenAI at the peak of its hype cycle, many are questioning whether now is the right time to invest. Despite its promise, GenAI brings challenges like high costs, risks, and the need for enterprise transformation.
This presentation will provide practical insights to navigate the complexities of GenAI deployment effectively:
• Real-world use cases where GenAI addresses business challenges
• Key considerations for building a GenAI capability
• Lessons learned from implementing GenAI at Philips to support AI initiatives
The insurance industry stands at a pivotal crossroads as generative AI transforms core operations from underwriting, to claims management to customer support. Generali's journey in implementing AI across its business functions offers valuable insights into the challenges and opportunities of this technological revolution. This session explores how Generali is leveraging AI to enhance efficiency, personalize customer experiences, and drive innovation in a traditionally conservative industry.
Business leaders can effectively harness generative AI in insurance by:
• Fostering a culture of AI literacy and experimentation through company-wide training and innovation methodologies
• Balancing internal innovation with strategic partnerships to accelerate AI adoption
• Prioritizing use cases that enhance customer experience and operational efficiency
As enterprises rush to adopt generative AI, finding the right balance between innovation and strategic restraint is crucial for sustainable success. This session explores how organizations can determine the optimal level of GenAI investment and integration to maximize value while mitigating risks and avoiding resource overcommitment.
• Developing a value-driven GenAI roadmap aligned with core business objectives and capabilities
• Implementing agile experimentation frameworks to rapidly test and scale GenAI initiatives
• Establishing cross-functional governance structures to ensure responsible and strategic AI adoption
Navigating change management in Generative AI at a global scale requires coordination across functions, regions, and cultures. In this session, our speaker will share case studies and current progress on how their organisation is aligning strategies, synergising, and scaling GenAI solutions from pilot
to production globally. Learn how to practically unify teams and functions to ensure seamless adoption and maximize AI’s impact across the enterprise.
• Building cross-functional strategies for scaling Generative AI across global teams and multiple business units.
• Leveraging data and shared experiences to pilot and expand AI solutions across regions and functions.
• Developing effective change management frameworks to support AI adoption in different global markets.
As the generative AI hype plateaus, a strategic, long-term approach is crucial for sustainable success and real value creation. This talk explores a comprehensive framework for embedding GenAI into enterprise strategy, focusing on challenge-led implementation, robust governance, effective success metrics, and scalable deployment methodologies.
• Prioritizing challenge-led use cases that align with core business objectives
• Implementing robust governance frameworks to ensure ethical and compliant AI use
• Developing clear success metrics and scalable deployment strategies for long-term growth
As generative AI reshapes the business landscape, fostering widespread AI literacy across all organizational levels has become a critical competitive advantage. By equipping employees with the knowledge and skills to understand, interact with, and leverage AI technologies, companies can unlock unprecedented levels of innovation, efficiency, and problem-solving capabilities.
• Implementing comprehensive AI literacy programs tailored to different roles and departments
• Developing hands-on AI workshops and sandboxes to encourage practical learning and experimentation
• Establishing clear career pathways that incentivize continuous AI learning and skill development
In this session, Nick Brown, Executive Head of Predictive AI & Data, will explore how leveraging knowledge graphs and AI can significantly improve data accuracy, scalability, and enterprise search capabilities within the pharmaceutical industry and beyond. He’ll share first hand examples of how his team uses GenAI & imaging to predict safety, toxicology and clinical challenges. Dive into the complexities of deploying AI at scale by:
· Leveraging knowledge graphs to enhance data accuracy and scalability across the enterprise
· Showcasing use cases to that improve our understanding of real-world implementation
· Exploring what future opportunities exist for drug discovery
In today's data-driven economy, organizations are sitting on vast troves of information that could potentially be transformed into significant revenue streams. However, challenges such as data quality, regulatory compliance, and ethical considerations often hinder effective data monetization strategies. This panel explores how enterprises can leverage generative AI and advanced analytics to unlock the full potential of their data assets while navigating the complex landscape of data governance and privacy.
Business leaders can drive successful data monetization by:
• Implementing robust data quality and governance frameworks to ensure reliable insights
• Exploring innovative data products and services that align with market demands
• Balancing data monetization efforts with ethical considerations and regulatory compliance
As generative AI adoption accelerates, its environmental impact becomes a critical concern for responsible and forward-thinking enterprises. Implementing sustainable AI practices is not only crucial for reducing carbon footprints and energy costs but also for meeting stakeholder expectations and regulatory requirements while driving long-term business value.
As generative AI reshapes the business landscape, ensuring inclusivity and accessibility is not just ethical—it’s a strategic imperative. Inclusive AI has the power to democratize technology, break down barriers for people, and unlock unprecedented opportunities for innovation and growth. This panel explores how enterprises can harness the transformative potential of AI to create more inclusive products, services, and workplaces.
Adopting new technologies, especially generative AI, can bring transformative benefits, but maintaining the human touch is critical in any process. As businesses navigate the integration of AI into workflows, preserving creativity, empathy, and customer connection is key to successful implementation. This session explores how business leaders can inspire teams to embrace tech while ensuring human-focused processes remain intact.
Generative AI is reshaping the landscape of creative industries, offering unprecedented tools for innovation, efficiency, and artistic expression. Understanding the impact and potential of AI in creative fields is crucial for businesses to stay competitive, unlock new revenue streams, and redefine the boundaries of human-AI collaboration in content creation.
As generative AI reshapes industries, the uneven distribution of risks among tech companies, deployers, and developers poses significant challenges to sustainable innovation and responsible AI adoption. Establishing a framework for equitable risk burden is crucial not only for fostering trust and collaboration within the AI ecosystem but also for ensuring long-term growth and mitigating potential regulatory backlash.
• Implementing transparent risk-sharing agreements across the AI value chain
• Collaborating on industry-wide standards for risk assessment and mitigation strategies
• Advocating for balanced regulatory frameworks that distribute responsibility fairly among stakeholders
Join Perry as he delves into Entain’s journey so far with Generative AI. Discover how Entain is leading innovation while maintaining trust, compliance, and a customer-first approach. Attend to delve into:
The rapid rise of generative AI is prompting higher education institutions to rethink traditional approaches to learning and teaching. From legal frameworks to practical applications, institutions are navigating a complex landscape of AI-enhanced education and rapidly evolving learner expectations, as well as the complexities of getting ahead and implementing this technology themselves. This panel will explore how leaders in higher education are addressing the challenges and opportunities of embedding AI into the future of learning and assessment, with insights on faculty training, curriculum integration, and the evolving role of educators.