Enterprise AI

Chairpersons welcome and opening remarks.

• Latest advances in the field of Edge AI.
• The challenge – to use AI and IOT data to monitor satellite field wells for operational efficiency and production.
• The solution – a platform solution which runs a machine learning algorithm at the edge to classify DynaCards and enable smart alerts that proactively notify users if anomalies are found when monitoring data.
• The results – reduced anomaly downtime up to 70% for the connected wells.

We are at an inflection point. AI/ML is everywhere. But how can organizations easily go from POC to scale and what decisions are required? How can they make ML accessible to more people? How can they adopt new technology faster? And how can they do it all in a responsible way? In this keynote we will explore key themes like the future state of generative AI, responsible AI, and the democratization of machine learning – and share what we have learned working hand-in-hand with organizations on a global scale to translate AI and ML from theory to practice.

• Human-centred AI for the optimum patient experience.
• AI enhancing the human expertise, not replacing it.
• Private and sensitive data – how it is handled and processed is more important than ever.
• Adopting AI quickly into existing processes, think automating routine tasks.

• Sophisticated decision making through AI, how to eliminate the bias. 
• Learning from past mistakes – discussing the different approaches and concerns industries need to consider when tackling issues like privacy, surveillance and discrimination.  
• The role of responsible AI in aiding the ethical AI journey. 
• The need for governance and regulation as industry standards – where we are vs where we need to be and the laws around AI. 

In this session, you will learn:

• That despite immense potential of Generative AI and LLM, building and implementing these systems presents various challenges. We will discuss the key obstacles organizations face, including data availability, process complexities, cost considerations, outcome uncertainties as well as organizational and process challenges.
• A strategic framework from SoftServe for identifying and prioritizing high-impact use cases, turning ideas into tangible products while maximizing value, optimizing cost-efficiency and accelerating time-to-market.
• Best practices for successful implementations, covering solution ideation and the key design considerations, data prerequisites, model development, adaptation, and production deployment.
• How to navigate the complexities of the rapidly evolving Generative AI landscape, driving value across all aspects of your business and securing a competitive advantage in the digital age.

To follow soon …

AI-driven insights has the potential to transform every industry and it’s time for everyone – not just Data Scientists – to take advantage of this game-changing force. From optimizing supply chains to improving customer experiences and more, the session discusses the strategic potential of AI and how an AI-first mindset to data analytics can enable deeper insights faster than ever before.

• Creating a holistic strategy that includes AI, BI, ML and other disruptive technology processes and capabilities.  
• A shift towards simplifying the vendor landscape to limit the overlap here – focusing on gaps in the market and MVP (minimum value products).  
• Building partnerships across solutions and sectors as the key to an optimised eco-system. 

This talk focuses on building and implementing an A/B testing ecosystem for personalized meditation recommendations in an online meditation company. It will cover key metrics, strategies for testing, and best practices for deploying effective personalized recommendations to improve user experience and engagement.

Live streamed presentation 

The session will cover how data observability addresses key modernization challenges such as:

• De-risking data platform migrations with data reconciliation and pipeline performance comparison, both pre- and post-migration.
• Accelerating migration initiatives by automating and simplifying many aspects of validation and troubleshooting data and performance issues.
• Optimizing for cost by analyzing resource consumption to avoid unexpected overruns and determine optimal workload placement.

With the fast advancements in AI, the AI development paradigm is evolving. Led by Samantha Bowman, Microsoft for Startups’ Director of Go-to-Market Programs, this discussion and Q&A covers the present and future of AI development with four market leading startups in AI tooling. We discuss AI development best practices with large language models and how you can leverage them to stay ahead of the changing AI tech stack.

To follow soon …

View day 2 content here:

• Optimised Data & Analytics
• Transformational AI
• Human-centred Approaches to DTX