AI Security Is Becoming a Software Discipline. We Should Have Seen This Coming.

terminal-arrows-control-layer

This week, AI security startup Neo emerged from stealth with $100 million in funding to tackle a problem that many organisations are only just beginning to recognise.

Not securing AI models.

Not securing prompts.

Securing the software that quietly becomes AI-powered overnight. (The Wall Street Journal)

That is a significant shift.

Gartner predicts that by the end of 2026, around 40% of enterprise software will contain AI agents, up from less than 5% in 2025. Every CRM, finance system, ERP platform and internal application has the potential to become more autonomous through what appears to be a routine software update. (The Wall Street Journal)

The challenge is no longer just asking:

“Can AI do this?”

It is now:

“Should AI be allowed to do this?”

layered-prompt-to-code-cards

AI isn’t creating a new security problem. It’s exposing an old engineering one.

For years, software development has focused on delivering functionality.

Authentication often came later. Authorisation followed.

Auditing became another feature.

Governance was usually something added after the first release.

AI changes that completely.

Once software can reason, make decisions and trigger actions, governance is no longer optional. It becomes part of the architecture itself.

You need to know:

  • What data can this AI access?
  • Which users can invoke it?
  • Which systems can it call?
  • What decisions is it allowed to make?
  • Can every action be audited afterwards?

These are software engineering questions, not AI questions.

This is exactly why deterministic platforms matter

At SWAIN, we’ve always believed AI should not sit directly on top of production systems without control.

AI is probabilistic.

Enterprise software cannot be.

The role of a deterministic platform is to provide the guardrails that AI operates within.

That means:

  • Authentication before execution.
  • Role Based Access Control (RBAC) by design.
  • Row Level Security protecting data automatically.
  • Policy enforcement before actions occur.
  • Complete audit trails.
  • Versioned APIs and governed interfaces.

The AI remains creative.

The platform remains predictable.

Security is moving earlier in the lifecycle

Neo’s announcement reinforces something we’ve believed for some time.

The next major software discipline isn’t simply AI engineering.

It’s AI governance engineering.

Developers will increasingly need to think about:

  1. identity
  2. permissions
  3. policy
  4. observability
  5. deterministic execution

before they even write business logic.

The organisations that build these capabilities into their architecture today will be able to adopt AI safely tomorrow.

The organisations that bolt them on afterwards will spend years trying to regain control.

The future isn’t about limiting AI

It’s about giving AI the freedom to innovate within boundaries that organisations can trust.

That’s where the industry is heading.

And that’s exactly the problem SWAIN was built to solve.

Book a Demo