Zach Bartholomew | Source | VP, Product at Perigon

Zach explains that an AI agent "can perceive its environment, plan, and take meaningful action largely on its own." He warns that mislabeling tools as agents can lead to wasted budgets. CIOs should ask critical questions about autonomy to ensure investments in true AI-driven solutions. Clearer definitions will soon distinguish genuine agents from mere chatbots.

Zach explains that AI bias arises from societal prejudices in training data, unlike AI hallucination, which generates incorrect information. He notes, "Creating AI systems that are completely free of bias is tough," but suggests diverse data, bias detection, and transparency as key strategies. Continuous updates are essential for reducing unfair outcomes.

Zach explains, “Vector databases are like super-efficient digital libraries for AI, but they pose risks of exposing sensitive data.” Despite these risks, their cost-effectiveness, scalability, and performance make them indispensable. To mitigate vulnerabilities, Zach urges the AI industry to enhance security protocols, developer education, and establish industry-wide standards.