The AI Interview: Ivana Bartoletti, Wipro

2026-04-29 · Source: AI Magazine · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Cybersecurity & Data Privacy, AI Governance & Ethics · Depth: Intermediate, medium

Summary

Ivana Bartoletti, VP and Global Chief Privacy & AI Governance Officer at Wipro, emphasizes the critical need for organizations to build trustworthy AI systems by embedding accountability from the outset. Wipro's consulting-led approach focuses on governing AI, ensuring its trustworthiness, and delivering measurable value beyond pilot phases. Bartoletti's role spans internal operations, external regulatory engagement, and anticipating future AI risks like agentic and emotional AI. She highlights that current regulations are insufficient for agentic AI, particularly regarding responsibility and explainability, advocating for "trust by design" and a principle of non-delegable responsibility for organizations deploying autonomous agents. Bartoletti also warns against anthropomorphism in AI design, which can create misalignment between user expectations and system capabilities, stressing the importance of transparency in AI's nature.

Key takeaway

For Directors of AI/ML or AI Ethicists developing and deploying AI systems, prioritize a "trust by design" philosophy over mere regulatory compliance. Begin by conducting a comprehensive audit of your organization's AI landscape to understand existing systems, their ownership, and data usage. This foundational knowledge is crucial for establishing effective governance frameworks and ensuring non-delegable accountability, especially with agentic AI, thereby building genuinely trustworthy systems that offer a competitive advantage.

Key insights

Trustworthy AI requires embedding accountability, governance, and transparency from initial design through deployment.

Principles

• Accountability must be non-delegable to AI systems.
• Governance is a design principle, not a constraint.
• Transparency about AI's nature prevents misalignment.

Method

Implement a "trust stack" by first auditing existing AI systems to understand their function, ownership, decisions influenced, and data used, before applying governance controls.

In practice

• Audit all AI systems in operation.
• Design for human oversight and failure recovery.
• Avoid anthropomorphic AI design.

Topics

• AI Governance
• Trustworthy AI Systems
• Agentic AI
• AI Accountability
• Data Privacy

Best for: Director of AI/ML, AI Ethicist, Legal Professional

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Editorial summary, takeaway, and curation by AIssential. Original article published by AI Magazine.