CAIO Institute: UK

CAIO Institute: UK

Location: London

Date: Thursday 23rd May 2024

Time: 08:00 - 17:30 BST

Event Summary

The Global CAIO Institute Event Series delivers a world-class full day of collaboration, networking, and discussions focusing on the latest trends and challenges currently faced within the industry. Provided through a dynamic combination of thought leadership and best practice strategies, our exceptional end-user-driven academic platform assists digital business leaders in improving productivity and growth within their organisations.

 

Featuring 80-100 hand-picked C-level & senior IT leaders from our global IT community, the day will consist of thought-provoking Panel discussions, Keynote presentations, interactive Boardrooms, 1-2-1 brokered business meetings, and networking opportunities. Discussions are driven by experts in the field, basing their insights on key business outcomes and allowing all to access powerful and useful content throughout the event.

2023 Featured Attendees

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2023 Agenda

Navigating the Data-AI Nexus: Exploring the integration of AI strategies with data governance frameworks to drive innovation and competitive advantage.

Ethical AI and Responsible Data Stewardship: Discussing the importance of ethical AI practices and how leaders can implement these in their organisations.

Tackling the Talent Challenge: Insights on cultivating in-house expertise, fostering a culture of continuous learning, and the importance of diversity in tech teams to bring varied perspectives.

Predicting Future Trends: Forward-looking perspective, on the next wave of trends in the data and AI landscape.

Tailoring AI for Specific Needs: Discuss the process and importance of customising generative AI models to meet specific business requirements and objectives.

Challenges in Model Customisation: Explore the key challenges and considerations in adapting generative AI models, including data selection, algorithm tuning, and ensuring ethical compliance.

Case Studies and Practical Applications: Examine real-world case studies highlighting successful customizations of generative AI models across various industries, focusing on the methodologies and outcomes achieved.

  • How to transform your business with AI to boost efficiency and decision making?
  • Discuss communication issues on organsational level and how to leverage AI for competitive advantage.
  • Tackle AI's challenges head-on, addressing data privacy, ethical considerations, and employee upskilling for successful integration.

Identifying and Cultivating AI Talent: Examine strategies for identifying potential AI and machine learning talent within existing teams and effective methods to cultivate these skills.

Bridging the Skills Gap: Discuss approaches to bridge the talent gap in AI and machine learning, including partnerships with educational institutions, upskilling programs, and recruitment strategies.

Fostering a Culture of Continuous Learning: Highlight the importance of creating a workplace culture that encourages continuous learning and innovation in AI and machine learning to keep pace with technological advancements.

  • Overview of NLP technologies and their applications.
  • Exploration of advancements and challenges in NLP.
  • Discussion on the impact of NLP in communication and data analysis.
  • Overview of the development and advancements in machine learning and deep learning.
  • Discussion of key milestones and breakthroughs in these fields.
  • Exploration of the future directions and potential of machine and deep learning.
  • Examination of ethical considerations and challenges in AI development.
  • Strategies for ensuring responsible AI innovation and deployment.
  • Analysis of the balance between technological progress and ethical implications.
  • Examination of AI's role in promoting sustainable development goals.
  • Analysis of AI-driven solutions for environmental and social challenges.
  • Case studies showcasing successful AI applications in sustainability.

Understanding Shadow AI: Delve into the concept of Shadow AI, its prevalence in enterprises, and the potential risks it poses to security, privacy, and compliance.

Mitigating Risks of Unauthorized AI: Explore strategies for identifying and mitigating the risks associated with unauthorized AI deployments, including governance frameworks and policy enforcement.

Balancing Innovation with Control: Discuss how enterprises can balance the need for innovation in AI with the necessity of maintaining control over AI systems to ensure security, privacy, and compliance.

Defining Hyperautomation: Introduce the concept of hyperautomation, its evolution from traditional automation, and its role as a transformative force in modern enterprise operations.

Implementing Hyperautomation Strategies: Discuss practical strategies for implementing hyperautomation in business processes, including technology selection, workforce integration, and process optimization.

Measuring Impact and ROI: Examine methods for measuring the impact and return on investment of hyperautomation initiatives, including productivity gains, cost reduction, and enhanced operational efficiency.

  • Identification of biases in AI algorithms and their societal impacts.
  • Methods and best practices for mitigating bias in AI systems.
  • Case studies demonstrating successful bias reduction in AI applications.
  • Examination of how AI technologies like chatbots and personalised recommendations enhance customer interactions.
  • Strategies for integrating AI into customer service and engagement to improve satisfaction and loyalty.
  • Analysis of case studies where AI has successfully transformed the customer experience in various industries.
  • Analysis of how AI is transforming business strategies and operations.
  • Discussion on the integration of AI into various business processes.
  • Future outlook on the role of AI in shaping business models and competitive advantages.
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