Securing AI at Scale in APAC: Why Kode-1 and Enkrypt AI Are Building This Together
What CIOs & CISOs Are Telling Us Right Now
What we’re hearing from CISOs and CIOs across Australia, New Zealand, and Indonesia is a different worry, and it isn’t about strategy. It’s about visibility. Most of them rolled out Microsoft Copilot by default — quick, familiar, already paid for as part of the bundle. What they didn’t bank on was how fast shadow AI would follow. People found their own tools. Data started moving in ways nobody had mapped. And security was the last to know.
Why APAC Isn’t the US or Europe
I'll be blunt: the APAC market has its own character, and what we deploy here must fit it.
Australia doesn't have AI-specific legislation yet. What we've got are the existing privacy and discrimination laws, which still apply to AI. On top of that, a major Privacy Act update is coming that will require organisations to disclose when AI is used in decision-making. That changes the picture. But we've been moving fast without any of that regulation forcing our hand.
So, we've ended up with a market that's both racing ahead and to a large degree exposed. Agentic workflows are going into production quickly. Governance isn't.
I watched this happen recently at a well-known Australian firm. They stood up an AI strategy, ran with it for seven months, and then had to tear it down and start again. That cost them real money, but the bigger hit was the time: seven months gone, use cases stalled, and a competitive window that doesn't reopen. When speed to production is the advantage, that lost ground is what hurts.
What Kode-1 Brings to This Partnership
What companies here need is a partner who gets both the technology and the environment it runs in. That’s why we built Kode-1 the way we did.
Last year, we launched the first AI Security (AISEC) Practitioner Certification course in Australia. The reasoning was simple: if we’re going to advise clients on this, we need the in-house expertise and the credibility to back it. We work across Singapore, Indonesia, and the rest of the APAC region, and our roots are in traditional cybersecurity and risk management.
And that matters, because rolling out AI governance in a big enterprise isn’t really a technology problem. The tech is the easy bit. The hard part is people: working out who needs to be in the room, getting through procurement, bringing along teams that are moving fast and have no interest in slowing down, and making the internal case for security spend that doesn’t show up on a revenue line. That’s the work that happens before any platform goes live, and it’s the part we’re built for.
Why Enkrypt AI
What caught our attention about Enkrypt AI is that they didn't bolt this onto an existing product. They built it from the ground up for agentic workflows and security — exactly the surface our clients are trying to govern.
Policy-based guardrails and in-line compliance are core to the product, and they've got the track record to back it up: fewer policy violations, and a faster path to production. In a market where everyone's already deployed and exposed AI, so achieving the business outcomes faster without losing control is the whole point.
What Good Looks Like
And it's coming. The Privacy Act changes are almost here, Indonesia is working on its national AI policy, and the EU AI Act is already being felt by multinationals operating in Australia, wherever they're headquartered. Build governance into the workflows now, rather than retrofitting it later, and you're not the one scrambling once the rules bite.
That's what Kode-1 and Enkrypt AI are building together out here. If you're a security leader in Australia, New Zealand, or Indonesia wrestling with this right now, I'd be glad to talk.
Mahesh Silva is the Managing Partner at KODE-1, a digital risk advisory leader in building AI, data, and cyber resilience through business alignment and risk reduction. We take a holistic and pragmatic approach to risk management, accelerating organisations' readiness to anticipate and evolve in a constantly changing digital threat landscape. Connect with Mahesh | Learn more about Kode-1: www.kode-1.com | Talk to the Enkrypt AI team
Frequently Asked Questions
AI governance is the framework of policies, controls, and oversight that manage how AI systems operate, make decisions, and handle data across an organization. In APAC, it matters because companies are deploying agentic workflows into production faster than governance frameworks can keep pace, creating compliance and security exposure under existing privacy laws and upcoming regulations like Australia's Privacy Act update requiring disclosure of AI use in decision-making.
- Prevents shadow AI and untracked data movement across teams and tools.
- Aligns with regional privacy and discrimination law requirements.
- Reduces costly rework when governance gaps force production rollbacks.
Securing AI agents in production requires policy-based guardrails that run inline with agent execution, blocking unsafe actions and data leakage in real time without slowing performance. Agent guardrails enforce compliance rules, prevent hallucinations, and stop tool misuse before it reaches users or systems.
- Deploy runtime protection that catches violations before agents act.
- Use centralized policy management across all agent deployments.
- Monitor and audit agent behavior continuously for compliance drift.
Red teaming identifies vulnerabilities and risks in AI agents before production; guardrails prevent those risks from being exploited during runtime. Red teaming tests across 300+ risk categories to find weaknesses, while guardrails enforce policies to block attacks and unsafe behavior as agents operate.
- Red teaming is pre-deployment testing; guardrails are continuous runtime defense.
- Together they create a complete security posture from development to production.
- Guardrails catch novel threats that red teaming may have missed.
Enkrypt AI is purpose-built for agentic workflow security from the ground up, with policy-based guardrails and compliance automation core to the platform rather than bolted on. It reduces manual compliance effort by up to 90% and delivers fewer policy violations across deployments.
- Built specifically for agents, not adapted from legacy security tools.
- Centralized policy engine governs all agent types and LLM deployments.
- Proven track record with enterprises across APAC managing rapid AI rollouts.
Enkrypt AI's policy-based guardrails catch shadow AI and agentic drift before they cost you seven months. Book a demo to see how it works across your APAC environment, or start a free trial now.
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