CNME Editor Mark Forker spoke to Anirban Mukherjee, Director, Solution Architecture, MENA for RedHat, to learn more about its open hybrid cloud portfolio, the need for digital sovereignty, and what intelligent automation looks like at the edge.
The MENA region is experiencing rapid digital transformation, with significant investments in cloud and AI. How does Red Hat position its open hybrid cloud portfolio to cater to the diverse cloud strategies of MENA organizations?
Most organizations in the region aren’t running a single-cloud strategy: they’re blending private infrastructure, sovereign clouds, and hyper-scalers depending on data gravity, cost, and compliance.
IDC shows hybrid cloud adoption in MEA crossing 60% as enterprises modernize regulated workloads. What Red Hat brings to the table is this: any model, any accelerator, any cloud.
That means a consistent cloud operating model so teams can build once, deploy anywhere, and move workloads without lock-in. For example, one of the largest banks in the United Arab Emirates, Emirates NBD, partnered with Red Hat to standardize on one platform layer across multiple clouds, which allowed them to scale new digital services faster while keeping regulated data in-country.
A Dubai-based air-services group used the same architecture to modernize cargo applications on-prem while selectively bursting non-regulated services to the public cloud, improving resilience and cutting deployment cycles from weeks to days. The outcome customers care about is speed, portability, cost efficiency, and risk reduction.
MENA also faces unique challenges, including a diverse regulatory landscape, varying levels of digital maturity, and a strong emphasis on digital sovereignty. How does Red Hat address these nuances?
The region’s regulatory diversity and sovereignty focus means technology decisions are increasingly policy driven.
Governments and large enterprises want to know exactly where data lives and how AI models are governed, and whether platforms can be audited and isolated to prevent hallucination or pursue a misaligned goal.
We lean heavily into open architecture so organizations can inspect, validate, and govern the full stack.
A good example is a banking customer that built their digital banking and payment system on a shared hybrid infrastructure, allowing them to innovate faster while aligning to local regulatory oversight and keeping data residency fully controlled.
On digital maturity, we see customers in very different phases, so our strategy is to adapt to customers’ maturity levels and help them move from experimentation to production, modernise what exists, automate it, then embed AI where it improves productivity and drives measurable outcomes.
For instance, a telecom operator automated network fault remediation, modernized their application platform to deploy digital 5G services and are leveraging AI to boost productivity for their call centre operations.
With edge computing becoming more critical for sectors like energy, logistics, and telco, how is Red Hat enabling real-time decision-making and intelligent automation at the edge?
Edge is mission-critical tied to revenue and safety outcomes in sectors like energy, ports, logistics, and 5G networks because the data is generated far from central clouds.
We enable industrial automation by providing a durable, consistent platform that runs disconnected, automates locally, and syncs centrally. I have a few examples for you. An energy company in the region deployed automated inspection workloads across remote rigs, processing sensors and vision data locally for anomaly detection.
This resulted in improved equipment uptime, and shortened incident response from minutes to seconds which is critical in hazardous environments.
In logistics, a major airport cargo provider used edge automation for conveyor orchestration and predictive load balancing, cutting package processing delays by 30%.
A regional mobile operator is running intelligent network automation at tower edges, enabling self-healing configurations, which directly improved uptime and lowered costs.
What initiatives, partnerships, or educational programs is Red Hat implementing to foster local talent development, upskill the workforce, and build a strong open-source community with the MENA countries?
The talent opportunity in the region is massive, but the gap is real. In UAE only, according to a recent Red Hat survey, 76% of businesses agree there is an urgent AI skills gap, with agentic AI skills most in demand (57%).
In GCC, governments are pushing national skilling programs at scale: PwC predicts AI-related GDP impact in the Middle East to reach 2.6% by 2030, but only if workforce readiness keeps pace. At Red Hat investment has been to build structured enablement paths so students, developers, and IT professionals can move from consumers to contributors.
We align directly with the human capability goals of regional national visions through programs that integrate open-source curricula directly into universities across the UAE, KSA, and Egypt.
We’ve been working with partner ecosystems to incentivise them to develop local talent on cloud native technologies and AI so that they can develop new revenue streams and help our customers in their journey.
The strategy isn’t just workforce upskilling: it’s ecosystem building, job creation, and long-term digital competitiveness.
What are Red Hat’s strategic priorities and investment areas in the MENA region for the next 3-5 years, and how do you foresee the open-source landscape evolving in this dynamic market?
Over the next 3-5 years, the priorities are clear: sovereign hybrid infrastructure, large-scale automation, and AI that can be governed, optimized, and run cost-efficiently.
The open-source landscape here is shifting to strategic imperative, especially as governments mandate data sovereignty, transparency, model provenance. I see AI becoming embedded inside broader digital platforms rather than standing alone.
We anticipate the landscape will evolve toward “Agentic AI,” where autonomous agents interact across enterprise applications to complete end-to-end workflows.
A UAE bank we are working with is already combining hybrid cloud consistency, automated DevSecOps governance, and internal AI inference for fraud detection and customer support.
The future winners in MENA will be the ones that standardize the core, automate relentlessly, and treat AI as an accelerator.
Open source will win here, because organizations want innovation they can scale, inspect, govern, and localize on their own terms.
