In the coming year, generative AI will evolve from the experimental phase to fully autonomous systems that can plan, control and execute complex workflows with minimal human supervision. The focus will shift away from pure modelling towards actionability, energy efficiency, governance and measurable return on investment. Industries such as telecommunications, manufacturing and logistics will lead the way in adoption through multi-agent systems and ‘self-healing’ IT processes.
However, increasing autonomy also brings with it challenges in the areas of security, compliance and energy. Energy availability and governance will be decisive factors. Traditional applications and data storage models will become less important and be replaced by short-lived, AI-generated modules and selective data storage. Competitive advantages will arise from expertise, energy control and trustworthy data pipelines.