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Old data practices key to navigating new agentic ambitions

Metadata and data quality are not as sexy as autonomous agents, but data executives across the capital markets warn that they are integral to successful agents.

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Last week, in an interview with CNBC, Goldman Sachs’ president and chief operating officer, John Waldron, talked about the 157-year-old bank in “factory” terms. 

“Our human assembly lines will become more digitized. … Digital agents will be our robots [and these agents] will start to change the way we workflow [sic] the firm,” similar to the way that massive production robots revolutionized manufacturing and car factories. 

The promise of digital agents—a.k.a. agentic AI—is in streamlining

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M&As, MCPs and why clean data is essential

The Waters Wrap: Financial firms are racing to adopt AI—but the payoff depends on having the right foundations, particularly clean, normalized data, writes Wei‑Shen.

How governance-first architecture stabilizes complex systems

Chetan Patil argues that many transformation projects fail not because of the technology but because of weak data governance. Adopting a governance-first discipline early (and building speed, resiliency, and credibility over time) is best.

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