10 verified briefings on Governance. Each story includes a plain-English summary, why it matters, and the concrete action engineering teams should take.
A major Danish pension fund has blacklisted SpaceX, preventing further investment due to what it calls 'catastrophic governance.' The decision highlights growing investor scrutiny over corporate governance and internal controls, even at high-profile private tech companies, signaling a broader trend for the industry.
As teams use AI for more complex coding tasks, the focus is shifting from speed to safety. A new framework called AC/DC helps organizations govern AI coding agents, ensuring code quality, managing risk, and creating a repeatable system for steering, checking, and correcting machine-generated code.
The integration of AI, cloud analytics, and connected sensors into operational technology (OT) is creating new security vulnerabilities. While these technologies promise efficiency gains, they also complicate uptime and safety, forcing leaders to rethink governance, incident response, and visibility across combined IT and OT environments.
Uber exhausted its annual AI budget in just four months, prompting the company to implement spending caps for employees using AI tools. This move highlights the escalating and often unpredictable costs of adopting generative AI technologies at a large scale for any business.
AI experts are warning CIOs against deploying AI agents without proper governance and observability tools. Rushing into adoption without visibility into the agents' decision-making processes creates a "time bomb" with the potential for severe negative consequences, turning a potential productivity boost into a significant business risk.
Employees are using AI to build apps and automations without oversight, creating a new wave of 'shadow IT'. This code sprawl introduces major security risks that security leaders are now scrambling to manage.
A new report shows 68% of financial services firms are getting a positive return on their generative AI investments. This signals a major shift from experimental projects to AI systems that deliver measurable business value.
Gartner predicts that by 2025, 40% of enterprise autonomous AI projects will be partially derailed by governance failures. These gaps are often discovered only after production incidents occur, stemming from a flawed, all-or-nothing approach to trust and control, according to the analyst firm.
In a recent discussion, experts from Dataiku and 1Password explored the next frontier of AI challenges. They covered the essentials of data governance, managing complex data supply chains, and the critical need for robust security frameworks to protect increasingly autonomous and interconnected AI agent swarms.
Employees are increasingly using unapproved AI tools, creating security risks. A new guide outlines a five-step approach for companies to manage this "shadow AI." The goal is to establish practical governance and security policies without hindering employee productivity or innovation, balancing control with enablement for teams.