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How does GDPR impact AI innovation, and what affects might AI have on regulations like GDPR? According to McKinsey, 78% of companies now use AI in at least one area of their business as of July 2024. But this quick adoption brings challenges for organisations handling data from the European Union and the UK. The main challenge for InfoSec and other enterprise leaders is clear. Using AI effectively means being able to develop faster.

Git and Perforce P4 are two powerful options for source code management, but choosing between them, or using both, depends on your specific use case and priorities. When evaluting these solutions, there's a lot to consider. So, we've broken down things to cover everything you need to know about Git vs. Perforce P4 in the table of contents below. Follow along or jump to the section that interests you the most.

In late 2020, hackers infiltrated SolarWinds—a company that produces network, systems, and information technology management software for public and private sector organizations. The resulting trojan went on to infect thousands of government entities and private companies as it was introduced into other software applications through version updates. Microsoft President Brad Smith called it "the largest and most sophisticated attack the world has ever seen.”

Every organization, regardless of the size or industry, has AI Ambitions. While this is an exciting and revolutionary time, it’s also filled with uncertainty and risk. At Perforce, we see what customers are facing. Organizations need to develop a clear and focused AI strategy that articulates the vision and value that AI can provide to the business. Security and compliance need to remain front and center, and vendor trust is essential.

The EU AI Act is a new law changing how organisations develop and deploy AI-powered solutions worldwide. Complying with it is a chance for organisations to stand out and build trust with customers through responsible AI use — all while continuing to innovate. As predicted by McKinsey and others back in 2023, AI (specifically generative AI) has become a key part of daily business operations across many industries.

Since the first vehicles were sold to customers, automakers have competed to deliver the newest features and the greatest benefits to the driving experience. Today, that competition is less about shaping a car’s physical characteristics and more about making cars smarter and more connected to the world around them. With thousands of car models and trim levels available worldwide, there is a fierce need to find new ways to stand out from the competition.

A commitment to user empowerment is at the heart of the Perforce P4 product philosophy. We believe in giving power and control to our users for ultimate configurability. This flexibility enables customers to tailor P4 to their specific workflows, but it also means they are responsible for securing their environment. For these reasons, we strongly recommend assigning the responsibilities of initial server setup, deployment, and ongoing maintenance to an experienced Perforce P4 administrator.

Gathering requirements in an Agile environment can feel like a balancing act, especially if you're operating in a heavily regulated industry. While the collaborative and iterative nature of an Agile approach facilitates productive and efficient workflows, it can make gathering and tracking requirements difficult. In the rush to complete a sprint, it’s easy to lose sight of user stories and the corresponding acceptance criteria. Three reasons Agile teams struggle with requirements gathering include.

Data masking protects sensitive information by replacing real data with realistic, fictitious values. It’s an essential technique for securing data, reducing breach risks, and meeting compliance standards. Let’s explore the fundamentals of data masking, its importance, common methods, and some real-world examples of how it’s used.