Historically, BPO has struggled to meet the needs of enterprises due to reliance on human labor, which can lead to delays and misunderstandings, highlighting the need for more efficient solutions.

Software has traditionally failed to address the complexities of BPO tasks because it often requires handling unstructured data and making contextual judgments, which AI is now capable of managing effectively.

The best opportunities for AI in BPOs lie in areas with clear KPIs, such as customer support, where performance can be easily measured and improved.

Founders entering the BPO space should recognize that large BPOs are aware of AI's potential and will likely attempt to leverage it themselves.

The distribution of tasks within BPOs is often opaque, and many of their operations involve not just outsourcing but also developing internal tools for companies lacking IT resources.

AI can expand the scope of customer service by automating tasks across a broader range of products, creating new market opportunities for BPOs.

Building AI products that can perform tasks traditionally done by humans, like customer support or sales, is challenging but essential for winning large enterprise contracts.

Business Process Outsourcing (BPO) refers to the practice where large enterprises outsource unsustainable workloads to specialized firms, covering areas like customer support, HR, finance, and knowledge management.

AI excels at processing disparate and unstructured information from various systems, enabling it to synthesize data and take actionable steps, which opens up new use cases for software in the BPO sector.