When AI Accelerates Everything, Security Has to Get Smarter

Software delivery has entered a new phase. Since 2022, AI-driven development tools have dramatically increased the amount of code being written, committed, and released. Teams are shipping faster than ever—and creating more applications than ever before. 

For security teams, this isn’t just acceleration. It’s multiplication. 

The challenge isn’t protecting an app. It’s protecting dozens of app version releases across Android and iOS (and sometimes web and desktop) without slowing down the teams building them. Traditional approach like manual tuning, broad-brush protections, or deep developer involvement do not scale in an AI-accelerated world. Especially when it isn’t just the white hats who are using AI to code faster, it is the black hats using AI to interrogate APKs. 

This is harsh reality that Digital.ai customers face every day.

Post-Build Security Was the Breakthrough — Now It Has to Be Intelligent

Post-build protection changed the game for Security Engineers. Instead of pushing security changes into source code and fighting developer friction, they could apply protections after the build, directly in CI/CD pipelines. Developers kept moving fast. Releases stayed on schedule. Security finally matched the speed of delivery. 

But as AI-driven code creation exploded, even post-build security needed to evolve. 

More applications meant more configurations. More releases meant more decisions. And not all code is equally valuable to attackers. Obfuscating everything might increase protection—but it also risks unnecessary performance impact and operational overhead. 

That’s where Quick Protect AI (QPAI) came in: automatically configuring protection blueprints based on application context, without manual effort. And now, we’ve taken that idea a step further.

Introducing Smarter Protection: Maximum Security, Minimum Impact

With our latest enhancements, QPAI now analyzes application code to identify what actually matters to attackers—and protects only that.

Instead of applying obfuscation based on pattern recognition, the system:

• Analyzes application structure and logic
• Identifies code paths most likely to expose secrets, IP, and critical business logic
• Applies protection precisely where it delivers the most security value
• Leaves non-sensitive code untouched to minimize performance impact

The result is stronger protection where it counts, and lighter impact everywhere else.

At the same time, we’ve expanded post-build protection to include Android native applications, extending these benefits beyond our existing coverage for iOS and Android Java apps. That means teams can now protect more types of apps, more easily, using the same post-build, AI-driven approach.

Security That Moves at the Speed of DevOps

In an AI-driven development era, security can’t rely on manual tuning or one-size-fits-all defenses. It has to be:

• Automated, to keep up with scale
• Selective, to preserve performance
• Post-build, to avoid slowing developers
• Platform-inclusive, to cover modern application portfolios

This latest evolution of Quick Protect AI reflects that philosophy. It helps security teams protect more applications, more effectively, with less friction—even as AI continues to accelerate everything else.

Security shouldn’t fight velocity. It should evolve alongside it.