The State of GenAI & Machine Learning in 2025

The growth of GenAI & Machine Learning has brought new emerging challenges; in this talk we dive into the state of GenAI & ML in the ecosystem, where we provide an overview of trends, challenges, opportunities and tooling that the ecosystem is standardizing towards.

As part of this session, we will provide a snapshot of the current state of the ecosystem, as uncovered by recent surveys, which highlights the gaps in tooling and skills [1]. We will then cover the best practices and tooling that are arising from production use-cases of LLMOps/MLOps at scale to tackle domain-specific challenges such as agentic-workflows, AI guardrails, efficiency requirements - between others. These include the OSS frameworks [2] that are supporting the end-to-end LLMOps / MLOps lifecycle across pipelining, optimization, productionisation, monitoring/observability and ML safety.

[1] https://ethical.institute/state-of-ml-2024

[2] https://bit.ly/ml-list