This chapter explores the homeostatic nature of sustainable investing and the transformative exploitation of robo-advisory to this end in the global asset management industry. This chapter navigates the evolving landscape of sustainable finance—from definitions to market growth, followed by evolution in the regulatory landscape and global sustainability standards frameworks. ESG investing is boosted by robo-advisory: these systems are bringing efficiency, accessibility, and democratisation of investment advice to an otherwise complex, yet transformative, investment landscape. With the issues of rating divergences, multiplicity, and conflicting nature of ESG standards, robo-advisory integrates AI capabilities to ingest not just data but can also provide comprehensive or segmented ESG scoring baselines to make consistent and robust investment decisions. Robo-advisory is streamlining investor idiosyncrasies, choices, and constraints—from moral/social values to climate-change trigger points. In addition, these platforms ensure that ESG standards, labels, and regulations are followed, with the ability to fast-track revisions to them, thereby mitigating issues such as greenwashing and green-hushing while embedding RegTech into robotic advisory services. The vertical integration of processes enables application of AI approaches such as NLP, LLMs, and ML to harness vast amounts of ESG disclosures and alternate datasets to bring additional insights in client advisory service. By highlighting the scope of hyper-personalisation and adaptive learning from client preference, this chapter provides a futuristic worldview of robo-advisory in the asset management sector. This chapter analyses how explainable AI is improving transparency and tractability for audit trails and compliance in ESG investing via robo-advisors.