eBay AI leader Anjali Arora told the CAIO Connect Podcast at TechEx that people, governance, and workflow change will decide enterprise AI success.
SAN JOSE, CA, UNITED STATES, May 20, 2026 /EINPresswire.com/ — At the TechEx conference in San Jose, the CAIO Connect Podcast hosted a detailed discussion on how companies should manage the fast rise of artificial intelligence in the workplace. Host Sanjay Puri spoke with Anjali Arora Mehra, Director, AI Strategy & Transformation at eBay, about the future of enterprise AI, agentic systems, and the growing fear that AI could replace jobs. Arora, who leads AI strategy and transformation for several functions at eBay, said companies must focus on people first if they want AI projects to succeed.
Arora explained that many organizations have already moved beyond the early phase of AI experimentation. Last year, companies mainly tracked how many employees used AI tools. Now, business leaders want measurable financial returns. She said firms should evaluate AI projects the same way they judge any business investment. Leaders should begin with a clear business problem and define the main performance metric before choosing AI solutions. According to Arora, organizations should focus on revenue growth, cost savings, and operational efficiency instead of adding AI to every workflow without a clear purpose. She also warned that companies must closely monitor token costs as AI usage grows across departments.
The conversation also focused on AI agents and how they could reshape work. Arora said organizations should avoid a one-size-fits-all approach. In some cases, humans should continue to control workflows from start to finish. In other cases, AI can assist employees while humans supervise important decisions. She stressed the importance of “human in the loop” systems for high-risk tasks such as fraud detection or decisions that cannot be reversed. At the same time, Arora said companies can safely use fully autonomous AI agents for lower-risk work such as tracking market trends or monitoring social media activity. She predicted that industries will continue adjusting the level of AI involvement based on the risk and complexity of each use case.
Governance emerged as another major theme during the CAIO Connect Podcast interview. Arora warned that the rapid growth of AI agents could increase security and compliance risks inside large organizations. She recommended that companies create governance committees or review boards to evaluate every AI project before deployment. These groups should examine issues such as data privacy, bias, ethical concerns, and unnecessary spending on expensive AI models. Arora also highlighted a growing trend in enterprise AI: using one AI system to monitor another. She explained that some companies now build evaluator agents that check outputs, monitor thresholds, and search for weaknesses in other AI systems. This approach allows organizations to scale AI operations while reducing the need for constant human supervision.
The discussion turned strongly toward change management and workforce concerns. Arora acknowledged that many employees genuinely fear AI could replace their jobs. She described AI transformation as one of the hardest organizational changes companies have faced because no established playbook exists. According to Arora, successful AI adoption depends on three elements: tools, processes, and people. However, she believes people matter most. To address resistance and anxiety at eBay, Arora helped create an AI stewardship program where each domain nominated AI stewards to guide teams through adoption. These peer leaders helped identify concerns, build tailored training programs, and encourage practical AI use inside teams. Arora said this grassroots approach made employees feel more involved and less threatened by the technology.
In the closing part of the CAIO Connect Podcast interview, Arora shared what separates successful AI programs from organizations stuck in “pilot purgatory.” She said strong leadership commitment plays a major role. Employees need to see executives actively using AI tools instead of only talking about innovation. She also stressed the importance of giving teams early access to modern AI tools and creating safe sandbox environments for experimentation. Arora added that companies must integrate AI directly into end-to-end workflows instead of running isolated pilot projects. During a rapid-fire round, she voiced support for open-source AI, preferred human-generated data over synthetic data, and leaned toward building AI tools internally when possible. Her message to enterprise leaders remained clear throughout the discussion: technology alone will not drive AI success people will.
Upasana Das
Knowledge Networks
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