Agent AI refers to autonomous intelligent systems that adapt to changing environments, make complex decisions, and collaborate with other agents and humans[1][2][6]. These systems enable the automation of dynamic multi-step processes in areas such as customer service, supply chains or finance[1]. In 2026, a transition from pilot projects to wider deployment in industry, especially in larger organizations, is expected[1][2][3]. Businesses will place emphasis on governance, compliance and retraining of employees to work with AI agents[1][5]. Agentic AI is transforming engineering workflows by taking early drafts of the software development cycle (SDLC), accelerating development[3]. Experts predict a change to multi-agent systems, where a coordinator manages specialized agents to avoid failures[5]. Physical AI will also emerge in controlled environments such as production and logistics[4][5]. The main challenges are security, ethical issues and loss of decision-making control[6].