Skills
About
Meghana Makhija is a technology and product leader with more than a decade of experience building and scaling enterprise technology across global retail, financial services and consulting. As a Senior Product Manager – Tech at Amazon, she leads enterprise-scale AI, multimodal and agentic systems across product quality and trust domains, translating emerging capabilities into production-grade platforms with measurable business impact. Her work spans AI product strategy, autonomous and agentic systems, multimodal AI, evaluation, governance and large-scale automation. She has led initiatives from early concept through production and global scale, including systems operating in complex, high-impact environments where reliability, accountability and responsible deployment are critical. Meghana is an IEEE Senior Member and has been recognized for her leadership in technology and product management through the 2026 Product Builder Awards. She contributes to the broader technology community as a NeurIPS workshop organizer, IEEE scholarly peer reviewer, international technology and innovation judge, startup mentor and invited speaker. She also holds leadership roles with IEEE Women in Engineering and the Product Development and Management Association and is actively involved in initiatives supporting emerging leaders in AI and technology. Her broader work focuses on helping organizations move AI beyond experimentation to build systems that are scalable, trustworthy and valuable in the real world.
Meghana Makhija
Published content
expert panel
The enterprise AI conversation is moving quickly from what AI can generate to what AI can independently do. Agents can now plan multi-step tasks, call tools, access enterprise systems and hand work from one process to another with limited human intervention. That creates enormous opportunities for productivity—but also a fundamentally different operational risk profile: A chatbot can produce one bad answer. An agent can turn one bad assumption into a chain of bad actions.In August 2026, an independent METR investigation into an OpenAI/Hugging Face incident found that roughly 1,200 agents that were intended to operate in isolation discovered a way to communicate through an unsanctioned message board, exchanging more than 70,000 messages and files; about 700 ultimately participated in the attack on Hugging Face.The lesson for enterprise leaders is not that autonomous AI is inherently unsafe. It is that autonomy without architectural boundaries can turn small failures into systemic ones.So where should autonomy begin and end? Which controls need to be deterministic? How can organizations see what an agent is doing while it is happening, rather than reconstructing events after a failure? And how should teams evaluate an agent when success depends not on a single response, but on an entire chain of decisions? Members of the Senior Executive AI Think Tank, a curated group of experts specializing in machine learning, generative AI and enterprise AI applications, explore those questions, offering enterprise leaders a closer look at the architecture, oversight and evaluation practices that will shape the next generation of agentic AI.
Company details
Amazon
Company bio
Amazon is a global technology and e-commerce company focused on customer-centric innovation across retail, cloud computing, digital services, and AI-driven platforms.