AI readiness has become a top priority for enterprises as artificial intelligence moves from experimentation to enterprise-wide deployment. Organizations are under increasing pressure to transform AI ambitions into measurable business outcomes, yet many CEOs believe they are not investing quickly enough, exposing a growing gap between strategy and execution.

In this exclusive interview with TECHx Media, Mohannad Abuissa, Managing Director Solutions Engineering & CTO, Cisco in Middle East, Africa, Türkiye, Romania and CIS, discusses the findings of Cisco’s latest CEO research, the importance of AI-ready infrastructure, AI security, governance, and data readiness, and explains how Cisco is helping organizations across the Middle East and Africa build the secure foundations needed to scale enterprise AI responsibly.

TECHx: The study shows a clear rise in CEO optimism around AI, along with growing concern about underinvestment. What do you see as the key drivers behind this shift, and how should enterprises interpret it in practical terms?

The shift comes down to a simple change in mindset. CEOs have moved from asking whether AI actually works to seeing real proof of its value playing out in the market. At the leadership level, the knowledge gap has narrowed considerably, so the early hesitation many leaders felt has turned into a different kind of worry: are we moving fast enough? You can see it in our research, where 91% of CEOs say they are more optimistic about AI’s potential than they were a year ago, even as 65% worry they are underinvesting. For enterprises, the message is hard to miss. The experimental phase is winding down, and strategic, company-wide execution is taking its place. I’d encourage organizations to treat that urgency as a signal to graduate from scattered pilots to scaled implementation, and to build on the foundations that make it possible: infrastructure, security, governance and secure data management.

TECHx: 65% of CEOs now feel they are not investing fast enough in AI. Where do you think organizations are most commonly going wrong when it comes to AI investment planning and execution?

The will to invest is clearly there, but execution is where most organizations stumble. The mistake we see most often is leaders underestimating just how much groundwork is needed before any advanced AI can be safely deployed. Companies rush to buy AI software without upgrading the underlying infrastructure to cope with the higher traffic, compute, connectivity and security demands AI brings with it. They also tend to overlook how messy fragmented data can be, and the work involved in bringing teams up to speed on new security protocols and governance models. AI investment can’t stop at the applications layer. It must include the foundations: the network, the security architecture, the data management and the skills to scale all of it responsibly.

TECHx: Infrastructure readiness is highlighted as the top barrier to AI scaling. From your perspective, what defines AI-ready infrastructure in 2026, and what gaps are still most prevalent today?

At its core, AI-ready infrastructure is about being able to handle high-volume, latency-sensitive data flows securely and reliably. It’s no longer a question of raw compute power alone. What organizations really need is a modernized, highly observable network that connects edge devices, data centers and multi-cloud environments without friction. And this is exactly where many organizations still fall short. Our CEO study found that 53% of CEOs fear infrastructure limitations will hold back their AI progress, which creates a real disconnect between the ambitions set in the boardroom and the day-to-day reality in the IT department. In practical terms, that infrastructure must be scalable, secure, automated and observable, so teams can actually see how AI workloads are moving across the business and step in before performance, security or compliance issues surface.

TECHx: Security and control of AI agents is now the top concern among CEOs. How should enterprises think about governance as AI agents become part of everyday workflows?

Now that security and control sit at the top of the list of CEO concerns, governance must be far more than a compliance checklist. As autonomous AI agents start carrying out tasks and making decisions inside everyday workflows, governance needs to become something dynamic and operational. That starts with embedding security by design, weaving safeguards directly into the fabric of the network rather than bolting them on afterward. It means clear policies around identity, access, permissions, auditability, monitoring and escalation, especially when agents are touching sensitive systems or data. And just as importantly, it means setting ethical guardrails and keeping humans in the loop, so that even as AI drives productivity, accountability and judgment stay firmly with people.

TECHx: Data fragmentation continues to slow down AI progress. What are the most practical steps organizations can take to build more unified and AI-ready data environments?

Data fragmentation comes up for a simple reason: AI models are only ever as good as the information feeding them. To break down those silos, the most practical first step is a deliberate data readiness strategy. Organizations need modern data architecture platforms that can pull in and organize information from scattered sources into one clean, unified format. But readiness isn’t only about centralizing data. It also means improving data quality, access controls, interoperability, visibility and governance, so the right data reaches the right systems in the right way. By prioritizing a cohesive data fabric, companies can move away from disconnected legacy systems toward an environment where high-quality data is accessible, transparent and ready to power responsible AI across the business.

TECHx: The research indicates that most CEOs expect humans to remain in control of AI systems. How do you see the balance between human oversight and automation evolving over the next few years?

The narrative that humans will simply be replaced is giving way to something far more collaborative. We’re moving toward a future where AI feels less like a piece of software and more like an active teammate. Over the next few years, AI systems will take on more complex and autonomous workflows, but always within frameworks shaped by human judgment. That mirrors what we found in our research, where 72% of CEOs expect AI to support or execute under human direction, judgment or governance. This is about augmenting what we can do, not taking it away from us. And it will be guided by the need for security, ethical oversight and the simple, enduring value of human intuition when the stakes are high.

TECHx: The Cisco AI Readiness Index highlights a clear gap between ambition and execution. What differentiates organizations that are successfully scaling AI from those that are still in early stages?

The real difference is that the successful ones build the foundation before they launch the applications. Early-stage companies tend to rush AI tools onto fragile networks and fragmented data, whereas the organizations scaling successfully put their energy into security, infrastructure, governance, skills and data readiness first. Our UAE AI Readiness Index is a good regional example of this. It shows organizations in the UAE moving with real urgency, with nearly all of them reporting increased pressure to deploy AI and 64% already having a strategy in place to roll out AI-powered solutions. And their investment priorities sit exactly where they should for scalable adoption: cybersecurity, IT infrastructure and data management. That blend of ambition, strategy and foundation-building is what carries organizations beyond pilots and into genuine scaling, while others stay stuck in early experimentation.

TECHx: Finally, how is Cisco supporting enterprises, particularly in the Middle East and Africa, in addressing challenges around infrastructure, security and data readiness?

For us, it really comes down to helping the region match its digital ambition with the right safety and security behind it. Organizations across the Middle East and Africa are genuinely ambitious, and our regional AI Readiness research shows strong momentum in markets like the UAE and Saudi Arabia, where companies are preparing to make far greater use of AI agents over the next 24 months. But because so many of these projects sit in highly regulated sectors like government and finance, you can’t deploy AI without clear controls around security, governance, compliance and data residency. That’s why we’re expanding our regional capabilities, including cloud services data centers in Saudi Arabia for cloud-delivered security services and Webex, while working alongside partners on AI infrastructure initiatives that support national digital ambitions. Cisco AI Defense plays a part too, helping organizations strengthen visibility, protection and policy enforcement across AI applications and agentic workflows. By bringing together secure infrastructure, advanced networking, security capabilities and hands-on skills training, we’re helping businesses across MEA scale their AI goals safely and with confidence.

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