AI’s potential for innovation comes with equal parts vulnerability. Complex models, opaque algorithms and large data sets make it difficult to understand and secure their AI systems. Threats range from data privacy issues and unauthorized tool use to adversarial attacks, compliance pressures and supply chain risks.
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As the music industry continues to fine-tune its approach to generative AI, the value attributed to training data is increasingly recognized, negotiated and realized through lawsuit settlements and emerging partnerships. While the central issue in most of these cases has been whether the platforms’ purported use of copyrighted materials constituted infringement or fair use, Google…
Artificial intelligence has moved from experiment to everyday business tool. As organizations accelerate AI adoption, AI security has become just as important as innovation. Employees now draft communications, analyze data and even write software with AI assistants — often faster than leadership can put guardrails in place. That speed is a genuine competitive advantage, but…
Financial services organizations have always been early adopters of business intelligence (BI). The data volumes are large, the reporting requirements are stringent and the pressure to turn information into decisions quickly is constant. Many firms built out significant Tableau environments in the 2010s and those environments have grown in complexity ever since. Today, many of those same firms…
