The transition toward accelerated materials discovery has often been perceived as a high-barrier endeavor, reserved for specialized facilities. This symposium challenges that narrative by exploring the AnyLab AI paradigm, a modular, accessible approach to integrating artificial intelligence and automation into any research environment. We focus on lowering the entry barrier for the discovery of functional materials, spanning plasmonic nanostructures, heterogeneous catalysts, and next-generation optoelectronic materials.Central to this discussion is the emergence of multi-agentic workflows, where LLM-powered agents and autonomous synthesis platforms communicate dynamically to navigate complex chemical spaces. We will highlight how multi agent-based systems can bridge the gap between theory based predictions and physical experimental verification. By bringing together experts in self-driving labs and materials informatics, this session provides a roadmap for implementing closed-loop discovery for diverse applications from light-harvesting plasmonics to efficient catalytic surfaces with only basic specialized hardware. We invite contributions that demonstrate how democratization and agentic collaboration can solve critical challenges in material stability, scalability, and the rapid realization of functional architectures.