Artificial Intelligence
Securing The Future Of AI: Balancing Innovation, Risk, And Trust Ft. Sandip Wadje, Managing Director At BNP Paribas
Overview
Emerging technology is fundamentally defined by the absence of regulatory certainty. From AI and cloud to quantum computing and digital assets, organizations are operating in spaces where controls have not been fully developed, and governance frameworks are still evolving. Sandip argues that this reality demands a different leadership mindset one built on education, shared perspective-setting, and proactive scenario planning rather than reactive compliance.
The Right Way To Sequence AI Adoption
Sandip introduces a practical sequencing model for AI deployment to summarize, write, and then reason. His insight is that roughly 50-60% of corporate knowledge work is summarization, making it the lowest-risk, highest-return starting point for AI projects. Organizations that skip this stage and jump directly to complex; high-stakes use cases like fraud detection or security operations expose themselves to failure before they have built any organizational confidence or ROI buffer.
Starting From Output, Not The Model
Rather than focusing on model guardrails or agent-level firewalls, Sandip argues that risk management should begin with the output. The key question is: if this output goes wrong, whose accountability is on the line? Working backwards from output failure scenarios, not forward from model configuration produces a more realistic and actionable risk framework.This shifts the conversation from theoretical compliance to practical residual risk management.
The Run The Bank vs. Change The Bank Inflection Point
One of Sandip's most compelling observations is that large institutions are approaching an inflection point where a single team or individual can no longer be expected to simultaneously run core operations and keep pace with emerging technology change. He advocates for a clear structural separation: one function focused on operational continuity, another on emerging technology readiness, with a deliberate handshake between the two.
The Global Regulatory Fragmentation Problem
Sandip outlines two concrete recommendations for regulators: provide prescriptive guidance to avoid divergent interpretations across risk and legal functions and harmonize regulations so that a single cloud workload is not subject to three separate audits under DORA, the EU AI Act, and GDPR simultaneously. He notes that fragmentation is not just inefficient; in fact, it is unsustainable for large financial institutions managing AI at scale.
Key Takeaways:
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Sequence AI adoption deliberately: summarize first, write next, reason last and build ROI at each stage before moving on.
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Start AI risk management from the output and work backwards, not from the model configuration forward.
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Quantum is not a distant threat: the rewiring required for post-quantum cryptography demands organizations start preparing now.
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Resilient leadership in uncertainty depends on listening, cultural intelligence, and how you handle situations under pressure.
About Sandip Wadje
Sandip Wadje is the Managing Director and Global Head of Emerging Technology Operational Risks & Intelligence at BNP Paribas, where he oversees the firm's approach to AI governance, quantum risk, digital assets, and threat intelligence across global operations. His career spans over two decades, beginning as a Class 1 government officer in India's Ministry of IT before moving through Deloitte, JP Morgan, KPMG and Risk IQ. He brings a rare combination of deep technical expertise and senior risk leadership experience across cybersecurity, financial systems, and emerging technology domains across global markets.
Thu, May 7, 2026
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