Axipro 創辦人兼 CEO Ali Hayat 訪談

Ali Hayat is CEO and founder of Axipro, combining a background in industrial risk management and ISO auditing with experience in cybersecurity and compliance consulting. His early work involved high-stakes industrial environments, where safety, regulatory requirements, and operational risk were central concerns. He later built Axipro without outside investment, focusing on helping growing companies adopt practical security controls, prepare for audits, and manage emerging AI risks.

Axipro is a cybersecurity and compliance consultancy supporting organizations across frameworks including SOC 2, ISO 27001, ISO 42001, and data protection requirements. Its work combines consulting, compliance automation, audit preparation, and security testing, with an emphasis on continuous monitoring and human oversight. In this interview, Hayat discusses AI-driven compliance workflows, shadow AI, autonomous agent risks, regional governance differences, and the gap between certification and cybersecurity resilience.

Your career began in high-stakes industrial environments, working on projects involving Saudi Aramco, ADNOC, and TotalEnergies, where safety, risk management, and regulatory compliance were critical. What inspired you to transition from industrial safety and auditing into cybersecurity, and what ultimately motivated you to found Axipro?

I founded Axipro because I saw a gap in the market while working in quality management. In 2021 I noticed many new cybersecurity platforms were launching semi-automated SOC 2 and ISO 27001 compliance platforms.

It became clear that even though these platforms relieved technical teams of much of the compliance burden, they still required setup and maintenance, and startups, already struggling to keep up with growth, would pay a human-led team to stay on top of compliance. That’s how Axipro was born.

Then, in 2022, the first AI platforms were released. This was another a-ha moment. While many people in the industry feared becoming redundant, I quickly realized this was a huge opportunity. AI would most likely increase cyberattacks exponentially, and skilled humans would be required to guide startups’ security and compliance needs in response.

Today we’re a Drata Elite Partner and a Vanta Preferred Partner, and we’ve guided over 300 companies to compliance on leading cybersecurity and AI standards.

You built Axipro from the ground up without outside investment, growing it into an international consultancy serving hundreds of clients. What were the biggest challenges of bootstrapping a cybersecurity business, and how has technology and automation helped you scale operations while maintaining service quality?

The first few years were extremely challenging. From exhausting my savings with a baby on the way to seeing the first AI models take over the industry, the first 2 to 3 years are probably responsible for the set of grey hairs I now have.

I was competing against a few Goliaths with established reputations, large offices, and substantial market budgets. I was based in Bahrain, had a background in quality management, and my marketing budget was 0.

My response was to take the contrarian route: I stayed lean, efficient, and underpriced the blue chips.

This brought me many new clients, but our margins were thin. Cash flow management became an art form, and we barely survived those first 2 years. Everything changed when we signed our first multi-framework 5-figure deal. This gave us some breathing room, allowed me to make my first full-time hires, and start thinking about marketing outside of partnerships and referrals.

Axipro focuses on simplifying complex compliance frameworks through digital transformation and automation. How is artificial intelligence changing traditional compliance workflows, and which activities do you believe offer the greatest opportunities for AI-driven efficiency?

The compliance industry has benefited greatly from AI. It previously relied on large amounts of repetitive work, such as collecting evidence and mapping it, answering security questionnaires, and drafting policies. These tasks are almost all automated now. AI has also enabled continuous monitoring and risk signaling for cybersecurity and compliance risks.

AI now touches almost all steps of the compliance process. Once we onboard a new client, our in-house AI conducts an automated risk assessment based on the company’s industry, size, and location. We have a large database of past engagements that helps us surface any potential risks and red flags automatically. This is probably the biggest value-add from AI.

Cybersecurity attackers have also benefited from AI, and attacks have increased exponentially. There’s a kind of AI vs AI arms race with firms like ours on one side, working on automatic threat detection, and hackers on the other, automating attacks.

This is where human judgment comes in, and it’s central to how we work: AI must handle repetitive tasks and deliver operational efficiency so humans can focus on threat judgment and response.

Many organizations still approach cybersecurity compliance as a periodic exercise centered on preparing for audits. How are AI-powered tools and continuous monitoring platforms such as Drata changing this approach, and what does the transition toward continuous compliance mean for businesses?

When I started in compliance, everyone dreaded audit season. Companies ignored their controls for most of the year, then spent weeks chasing screenshots and logs before the audit deadline. Passing meant you were compliant on that day, and that was about it.

Drata and similar platforms changed this. They connect to a company’s cloud and HR tools and check controls every day. If someone switches off MFA, or a former employee still has access, it shows up right away and our team fixes it right away.

For businesses, compliance stopped being a yearly project and becomes part of normal operations. Audits get shorter and cheaper, and sales teams can show their security status to enterprise buyers on demand, which helps close deals faster.

Data privacy and cybersecurity are slowly shifting from a requirement to work in sensitive industries to a value-added marketing asset.

As organizations increasingly rely on AI to generate security documentation, assess risks, and review compliance evidence, how can they ensure these systems produce accurate and trustworthy results? Where should human expertise remain essential in the auditing and certification process?

AI is very good at writing documents that sound right. A policy can look perfect and still describe processes the company doesn’t have.

The way we handle it is that AI drafts and flags issues, but someone on our team checks everything before it goes to the client or the auditor. Anything the AI produces should also point back to the evidence behind it, so we can verify it.

Internal and External auditing is where I draw a hard line. Auditors sign off with their name and their professional reputation. AI can help them get through evidence faster, but the decision on whether a company gets certified should stay with a person. If nobody is accountable, the certificate loses its value.

Axipro supports organizations navigating standards such as ISO 27001, SOC 2, and ISO 42001, the international standard for AI management systems. What new challenges are companies encountering as they attempt to establish responsible AI governance, and how does managing AI-related risks differ from traditional information security compliance?

Most companies we speak to don’t even know how much AI they’re using. The term for this is “Shadow AI”.

Marketing has signed up for one tool, developers have plugged a model into the product, and someone in finance is pasting spreadsheets into a chatbot. None of it is malicious, people are trying to work faster, and AI tools are cheap and fast. However, this can easily expose company data.

The first and most important step of most ISO 42001 and AI compliance projects is mapping all of it. We look at expense reports, software sign-ups and network data, and we talk to each team about what they actually use day to day. The list we end up with is almost always longer than expected.

Banning AI rarely works and is counter-productive and inefficient. We want our clients to be able to take advantage of the efficiencies brought by AI models. A better approach is to give staff approved tools that do the job, set clear rules on what data can go into them, and make it easy to request new ones.

AI governance also asks questions information security never had to. With ISO 27001, the main concern is keeping the wrong people away from your data. With ISO 42001, you also need to know whether the AI is behaving properly, whether you can explain its decisions, and who’s responsible when it gets something wrong.

These risks change faster too. A vendor can update a model overnight and change how your product behaves without you touching anything.

Companies that already have ISO 27001 start with an advantage. Both standards use the same management system structure, so a lot of the groundwork is already done.

With the emergence of autonomous AI agents capable of accessing sensitive information, interacting with enterprise systems, and executing business processes, what new cybersecurity and compliance risks should organizations be preparing for? Are existing security frameworks equipped to address these increasingly autonomous systems?

Agents are the area I’m watching most closely right now. Normal software does exactly what it’s told. An agent makes its own decisions, and it can be tricked and trick others, as we saw with the hugging face incident.

The most common risk we are seeing is prompt injection. An attacker can hide instructions in an email or a PDF, and when your agent reads it, it follows them using whatever access you gave it.

The second risk is that companies give agents far too much access because it’s easier. Often times, employees will grant AI agents access through their own email accounts rather than dedicated accounts, making it extremely hard to determine if a human or bot made a change. If logging is weak as well, you might not even know what the agent did.

ISO 27001 and SOC 2 still cover basics like access control and logging, and ISO 42001 helps on the AI side. None of them were written with autonomous agents in mind, though, and I expect new guidance soon.

AIUC-1 is emerging as a leading standard for AIUC-1 and we’ve just started training our staff to implement it. We’ve had a few conversations with clients about it, but no case studies to present yet. It has some strong backing by large cyber security companies, so we expect this framework to emerge as the leading AI agent standar.

Having worked across the Middle East, Europe, and the United States, you’ve encountered different regulatory environments and approaches to risk management. How are regional differences in AI governance and data protection influencing the way companies deploy AI, and what challenges arise when organizations operate across multiple jurisdictions?

Being based in Bahrain and working with clients in Europe and the US, I’ve stopped expecting AI rules to converge. If anything, the regions are moving further apart.

Europe regulates through law. The EU AI Act sorts AI systems by risk and sets out what each category has to do, so European companies tend to move carefully and document everything. The US has no federal AI law, and the market does most of the regulating. Buyers ask for frameworks like NIST’s AI RMF in their contracts, and liability fills in the rest. China takes a third route, writing a new rule each time a technology raises a new risk.

The Gulf is the one I find most interesting. Saudi Arabia, for example, doesn’t have a horizontal AI act yet. Most of the binding rules sit in data protection law and in government procurement, because the state is the biggest buyer of technology in the region. What you need to comply with depends a lot on who your customer is. When SDAIA, the Saudi regulator, got ISO 42001 certified itself in 2024, that told the market which standard it would be looking for in tenders.

The hardest part is when a company operates in more than one of these regions. A Riyadh SaaS company selling into Europe can meet the EU’s technical requirements and still fail in Saudi Arabia on data registration and transfer rules. Neither side accepts the other’s paperwork.

Our approach is to build one base that travels, which is ISO 42001 alongside ISO 27001, and then add each region’s requirements on top. ISO 42001 doesn’t make you legally compliant anywhere on its own, but it’s the closest thing to a common language all of these regions accept.

There is often a significant gap between achieving a security certification and maintaining genuine cybersecurity resilience. How can organizations use AI and automation to move beyond checkbox compliance and develop security practices that continuously adapt to emerging threats?

I’ve seen companies with a brand-new SOC 2 report and basic security holes nobody had noticed. Their goal had been to pass the audit. A certificate shows a company met a standard on a certain date, but it doesn’t show whether it can stop an attack.

Getting past that means asking whether each control would hold up under testing. Automation helps a lot here. Continuous monitoring catches problems while they’re still small, and current threat data keeps risk assessments in line with what attackers are doing now. Regular penetration tests and attack simulations then show whether the controls work in practice.

Becoming CREST certified this year was part of that for us. We wanted to test our clients’ security and document it.

Looking ahead over the next three to five years, how do you envision AI transforming the cybersecurity and compliance consulting industry? Do you believe AI agents will eventually handle most routine compliance activities autonomously, and how do you see Axipro evolving as these technologies mature?

I think AI agents will handle most routine compliance work within five years, things like evidence collection, policy updates, and security questionnaires. Firms that make their money billing hours with no discernible expertise for that work are going to struggle.

I don’t think agents will run compliance on their own, though. The more work AI takes on, the more the remaining decisions matter. Someone still has to sign off on an audit and deal with the fallout when something goes wrong. With attackers using AI too, demand for skilled defenders will keep growing.

At Axipro, I see us spending less time on documentation and more on advising clients and testing their security. Our in-house AI will take on more delivery work, and our team will focus on decisions that require human judgment. Back in 2022, a lot of people thought AI would make firms like ours redundant. So far, it’s done the opposite, we’ve been growing 10%+ month-on-month sometimes having more work than we can handle, and we don’t expect things to calm down.

Thank you for the great interview, readers who wish to learn more about cybersecurity compliance, AI governance, and building continuous security practices should visit Axipro.