Why human capital data is pulling AI back inside the firewall | Computer Weekly

"For the better part of two decades, the direction of travel in enterprise technology has been clear: everything moves to the cloud. The rationale was simple; the cloud was cheaper, scalable and easier to manage. But, as artificial intelligence (AI) enters the enterprise mainstream, that long-standing assumption is starting to bend."

"In certain areas, particularly where sensitive data is involved, companies are reconsidering how and where AI operates. Increasingly, they are exploring AI inside the firewall, running AI capabilities within their own on-premises controlled environments rather than relying entirely on cloud-based platforms."

"When organisations feed information into a cloud-based AI model, that data is, by definition, leaving their immediate environment. Even with strong assurances around privacy and training policies, many companies remain cautious about how sensitive information is processed and where it ultimately resides."

"The driver behind this shift is trust. Over the past year, AI tools from companies like OpenAI, Google and Anthropic have demonstrated extraordinary capabilities, from summarising complex documents to analysing data and accelerating decision-making across nearly every function of a business."

Enterprise technology has long shifted toward cloud platforms because they are cheaper, scalable, and easier to manage. As AI becomes mainstream, that assumption is changing for use cases involving sensitive data. Organizations increasingly run AI inside their own controlled environments, such as on-premises systems within the firewall, rather than relying entirely on cloud services. This shift is visible in human capital management, where millions of employees interact with workforce systems through time clocks, biometric verification, and workforce management tools. Trust drives adoption, especially concerns about where data goes when it is provided to cloud-based AI models. Regulated industries such as financial services, legal services, and healthcare face heightened caution due to confidential client data and internal strategy information.

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