As many as 85% of enterprises are either exploring or actively deploying GenAI to enhance automation, and European businesses are at the forefront of this shift. The latest ISG report highlights how GenAI and agentic AI are reshaping industries, streamlining operations, and fuelling demand for responsible AI frameworks.
GenAI, powered by large language models (LLMs), makes automation smarter by analysing massive datasets, generating complex outputs, and enhancing decision-making processes. Finance, healthcare, retail, and automotive organisations are embracing AI-driven automation to boost operational efficiency and reduce costs.
“GenAI has the potential to revolutionise intelligent automation, enabling organizations to analyse vast datasets and enhance their operational efficiencies,” said Steve Hall, Chief AI Officer, ISG. “Service providers are infusing GenAI capabilities into automation use cases, significantly accelerating innovation.”
The acceleration of intelligent automation
Service providers are integrating GenAI into automation solutions, creating accelerators, templates, and rapid prototyping workshops to help enterprises scale AI-driven processes. Industry-specific models are also gaining traction, allowing businesses to leverage AI within their unique ecosystems.
However, implementation remains challenging—especially for companies managing legacy systems and complex tech stacks. Successful adoption requires seamless integration, risk management, and alignment with automation maturity.
A cautious approach
Unlike their North American counterparts, European enterprises take a more risk-averse stance on GenAI adoption due to regulations such as the EU AI Act and GDPR. These frameworks demand ethical AI solutions, transparency, and compliance, pushing companies toward more responsible AI practices.
Agentic AI is also emerging as a game-changer in customer service, supply chain management, and employee onboarding. Unlike traditional automation that handles specific tasks, agentic AI enables autonomous, context-aware decision-making with minimal human intervention.