This blog is a special contribution by Ivan Harris, CPTO at Provar.

Back in August last year, I sat on a panel at the Testμ 2024 conference, where we had a discussion about how AI is making testing omnipresent. I’ve been thinking a lot about it recently. Omnipresent testing sounds ambitious, but the reality is it’s already here. AI is changing the game, and if you’re not adapting, you’re going to fall behind.

Since then, Salesforce launched Agentforce, doubling down on autonomous agents across their platform. In March we launched support for testing Agentforce at TrailblazerDX. That’s not a coincidence. It’s a reflection of where the industry is headed, and it’s heading there fast — very fast.

Here’s what’s really happening: the traditional handoffs between product, design, dev, and QA are being replaced by continuous collaboration, powered by AI.

Let’s break that down:

  • AI is capturing requirements in real time, summarizing inputs across teams.
  • Design validation tools are flagging UX issues before developers write a single line of code.
  • Coding assistants are bridging the gap between design intent and implementation.
  • AI-driven test frameworks are creating, executing, and self-healing tests continuously, not after the fact.
  • And AI-powered feedback loops are instantly telling us if the experience we shipped matches the one we intended.

This isn’t just faster testing. It’s end-to-end alignment. And it’s why I say AI is “eating QA” in the best possible way: it’s absorbing the repetitive, manual work that slows teams down, and replacing it with insight, speed, and clarity.

The real unlock? Context-aware collaboration. When your AI tools understand the goals and intent of the product, when they share the same context your teams do, magic happens. Misalignment drops. Velocity increases. Quality becomes continuous.

But here’s the thing: this isn’t about ripping and replacing your stack. The smartest teams I know are integrating AI layer by layer, starting with areas where the ROI is immediate, such as test creation, code review, documentation, anomaly detection in CI/CD. That’s exactly how we’re doing it, both for our customers and internally.

At TrailblazerDX, when we unveiled support for testing Salesforce Agentforce, it wasn’t just a feature drop, it was a signal. A signal that autonomous agents in design, development, and QA aren’t some future-state, they’re arriving now. And if your tooling doesn’t evolve to support this new model, your delivery pipeline won’t keep up.

In the near future, we’ll see AI-powered test automation agents that don’t just suggest fixes, they’ll collaborate with designers, developers, and testers to prioritize, implement, and validate solutions in real time. They’ll understand the business context and adapt test strategies based on impact, risk, and real-world usage.

This is what’s next. And frankly, it’s already started.

If you’re still thinking of AI in terms of productivity boosts or “developer assistants,” you’re missing the bigger opportunity. The future is systems that understand, act, and align across disciplines.

So yes, AI is eating QA. But what it’s really doing is digesting complexity, and serving up clarity.

And I’m all for that!

Want to learn more about how Provar’s AI capabilities can help you achieve your quality goals? Book some time with us today!