Day 1 - 6th September
AI for Enterprise: Chairperson’s Welcome
Responsible AI is Profitable AI: Lessons from early adopters
- AI investments in the financial services sector are predicted to reach $22.6B annually by 2025, driven by AI’s ability to innovatively and cost-effectively meet customer demands, drive operational productivity, and develop new products.
- AI faces a regulatory challenge, with many systems going rogue and creating business risk and financial loss, effectively stalling future AI projects.
- In this session you will learn how Responsible AI Framework and Tools are being deployed by early adopters in banking and financial services to manage five new AI business risks, build customer trust, and achieve a competitive edge
Associate Director - Advanced Technologies Group
09:30AM - Day 1
09:50AM - Day 1
Driving Business Value with Big Data and AI: A Case for Pilot-First Enterprise AI Projects
- For every success story, there are numerous examples of failure to implement and scale AI. Misalignment between leadership and technologists, an unclear understanding of what’s possible, or the lack of organizational support can drive organizations to a never-ending PoC cycle. It prevents them from harnessing AI’s actual potential value.
- In this session, we will explore the technological and use case landscape of AI projects. We will also explore a pilot-first approach to maximize the scalability of enterprise AI projects.
Combating fear of The Unknown – Building trust through explainability
- What level of trust and autonomy should we give our AI systems?
- Providing explanations for decisions made by AI systems
- Overcoming hesitation to deploy AI-powered solutions
VP Data Centres
Bulk Infrastructure Group
10:20AM - Day 1
10:40AM - Day 1
Building a sustainable digital infrastructure
- Details to follow soon..
Global CIO - Retail Banking & Wealth Management
09:30AM - Day 1
10:40AM - Day 1
11:20AM - Day 1
Director of AI
10:40AM - Day 1
11:20AM - Day 1
03:20PM - Day 1
Panel: Responsible delivery – the ethics of AI
- What is AI bias, and is it fair?
- Discussing liability and security
- Who benefits from AI, and could it result in a decrease in human-human interaction and employment issues?
Increasing Contact Centre ROI Affordably
- The use of technology to supercharge the customer experience is not a new idea, but few companies have been able to get this critical transformation right.
- Meet TMAC, a proudly different AI solution provider for contact centres and hear about their deployments of affordable speech analytics and their next best action playbook in a top five supermarket and FTSE 250 Insurer.
Transforming the Business with AI
- Harnessing Multi-sensor Machine Learning
- Solving big problems with Operational AI
- Unbiased ML and Transparent AI
CEO & Co-Founder
The Data Analysis Bureau
11:40AM - Day 1
12:40PM - Day 1
Data has gravity: Cognition as a Service on a distributed learning framework for performance, cost efficiency and privacy
- The commoditisation of machine learning and AI is shifting the supply and demand of resources and insights for organisations. Where teams of data scientists were once required to solve challenges, solutions can now be purchased on-demand as a service
- By abstracting away the complexity, Cognition as a Service (CaaS) disrupting the Data Science and AI market by making solutions accessible, on-demand, to all in a fast and cost-effective way.
- Industrialised machine learning and robust high-end pre-packaged solutions are moving the needle for big and small players that want to access AI and ML solutions
- The competitive advantage is gained through distributed learning frameworks to deliver improved performance and cost-efficiency, and address key privacy concerns
- Machine Learning solutions are moving from a tailored approach, where frameworks are built around companies, towards a faster and more scalable one, where frameworks are built around challenges
Automating complex business operations at scale
- How your organisation can accelerate digital transformation through end-to-end automation
- Layering tools to enable operational efficiency
- Opening doors to innovation
Panel: Built to scale – Ramping up AI projects
- How to move your project from “experimentation” to “live”
- R&D budget signoff – understanding why you need AI
- Turning AI into ROI – what does value mean to your business?
- Top tips for moving your pilot to the next stage
Senior Principal Solution Engineer
12:50PM - Day 2
12:30PM - Day 1
02:20PM - Day 2
03:00PM - Day 1
Why is Data Pipeline Orchestration so important?
- Big Data projects and Data Pipelines have merged into the technology fabric of every organization. The tools for building and running application workflows must be not only easily versionable and testable but they must also provide access to business and non-technical users.
- They must deliver the operational richness required to operate complex applications and deliver business services in accordance with service level commitments.
- In this talk, Tijs Monté, Senior Principal Solution Engineer in BMC Software, explains the need of production-ready application workflow orchestration for data-intensive applications and how automation, Big Data and IoT helped a leading vehicle manufacturer to cut fleet downtime.
Operational AI Expert
01:30PM - Day 1
03:30PM - Day 1
Democratization of AI in your organisation
- Artificial Intelligence is becoming more mainstream and subsequently organisations are now increasingly investing and working with AI. However, most companies have trouble scaling their efforts and receiving satisfactory ROI.
- Peltarion offers a solution to this problem. With the Peltarion Platform you can put AI in the hands of every employee and coworker in your organisation. Thus, allowing you to scale your efforts and harvest the full potential of AI by allowing your domain experts to utilize state-of-the-art AI models to create value.
Senior Representative, Boltzbit
02:10PM - Day 1
03:50PM - Day 1
- Details to follow…
Problem resolution: the proactive approach
- How to significantly increase uptime by scheduling proper maintenance
- Establishing a high-level view of risk exposures and enacting disaster recovery
- Conduct visual inspections to increase productivity and lifetime of your assets