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Building for scale: The technology priorities of 2026
From operational Artificial Intelligence to autonomous systems, what will matter most in the year ahead
- PUBLISHED: Sat 7 Feb 2026, 8:00 AM
Technology adoption across the region has accelerated in recent years, with AI, automation and digital platforms becoming embedded in everyday operations across sectors. Tools that were once tested in limited pilots are now supporting core business functions, from logistics and payments to customer engagement and workplace productivity.
In 2026, the focus is shifting away from experimentation towards execution. Organisations are paying closer attention to how these technologies influence decision-making, operational efficiency and risk management, as well as how they scale under real-world conditions. Security, governance and resilience are increasingly part of the technology conversation, alongside performance and cost.
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Against this backdrop, leaders across the UAE and the wider region are reassessing their technology priorities. The next phase of growth will be shaped not only by new innovations, but by how effectively existing systems are integrated, managed and trusted over the long term.
From experimentation to operational AI
For many organisations, the promise of AI is no longer theoretical. The challenge now is ensuring that AI systems deliver consistent value once they are embedded into daily operations. Junwei Yang, General Manager of Keeta Drone, says this distinction is critical. “When AI is treated as an enabler of operational excellence, it can deliver immense value to the business,” he explains.
At Keeta Drone, generative AI supports TBOS, the company’s trajectory-based operating system, which dynamically creates three-dimensional routes, mesh networks and backup plans in real time. “It turns last-mile delivery into real-time improvisation instead of a pre-written script,” Yang says. In 2026, he expects generative AI, 5G-Advanced and solid-state batteries to transform low-altitude logistics into fast, scalable delivery networks capable of operating at large scale and low cost.
A similar shift from pilots to system-level deployment is taking place across industries. Amr Kamel, General Manager of Microsoft UAE, describes 2026 as a turning point. “This is the year AI fully leaves the lab and embeds itself into the real economy,” he says. According to Kamel, the next phase of growth will be defined not by who builds the most advanced models, but by who deploys AI most effectively across healthcare, education, government and core industries.
He points to the UAE’s position as a global leader in AI adoption, noting that nearly two-thirds of the working population already uses generative AI tools. “What we are seeing is a move from pilots to system-level deployment, where AI is reshaping workflows, decision-making and service delivery at scale,” he says.
The rise of pragmatic and sector-specific AI
While enthusiasm around AI has grown rapidly over the past two years, many organisations are now confronting a more practical reality. Gopinath Polavarapu, Chief Data and Analytics Officer at JAGGAER, says 2026 will mark a shift toward what he describes as “pragmatic AI”.
“After a year or more of experiments, pilots and proofs-of-concept, most companies are realising they aren’t as ready as they thought,” he explains. “AI can’t transform anything if the data underneath it is messy, siloed or outdated. Impressive demos don’t mean much when they meet real-world processes.”
For many enterprises, the coming year will involve addressing these structural gaps by improving data quality, governance and integration across systems before scaling AI more widely.
Polavarapu also expects to see growing momentum around sector-specific models rather than large, general-purpose systems. “A model built specifically for financial compliance or clinical records will always outperform something generic, because it speaks the language of that domain,” he says. Smaller, tightly trained models designed for specialised tasks are already proving more effective in real operational environments.
Another emerging shift is what Polavarapu describes as the early stage of the “Physical AI” era. Robots and intelligent machines are increasingly acting as endpoints powered by compact models that manage perception and decision-making locally, while relying on cloud or on-premise infrastructure for broader orchestration. As these systems expand across factories, warehouses and operational environments, organisations will need technology architectures that work seamlessly across cloud, edge and sovereign systems.
He also notes that while the concept of fully autonomous AI agents coordinating complex workflows is attracting significant attention, most enterprises are still approaching it cautiously. “Task-specific agents are already delivering value in narrow areas such as contract analysis or supplier onboarding,” Polavarapu says. “But the idea of multiple agents orchestrating complex workflows independently is still early. The frameworks behind this need further refinement before organisations fully trust them in compliance-sensitive environments.”
Low-altitude logistics and autonomous delivery networks
Logistics is one of the clearest examples of how automation is moving beyond confined environments into broader operational ecosystems. In 2026, drone delivery, autonomous coordination and predictive planning are converging into what Yang describes as an intelligent, low-altitude logistics layer.
At Keeta Drone, the company’s Drone-as-a-Service model supports multi-drone coordination, smart route management and continuous replanning. “Automation now extends beyond warehouses into fully autonomous delivery networks,” Yang says. Sustainability is also a central consideration, with electric and energy-efficient delivery models designed into operations from the outset.
As logistics systems become more autonomous, reliability and safety become defining factors. “Ultimately, logistics leaders will be defined by reliability, safety and seamless customer experience,” Yang adds.
Security, sovereignty and governance
As AI and automation become embedded across organisations, the supporting digital infrastructure is under greater scrutiny. Magdalena Konig, General Counsel at Sirius International Holding, says the region is undergoing a mindset shift in how technology is viewed. “Technology is being recognised as strategic infrastructure,” she says. “AI is no longer something organisations test. It is foundational.”
She notes that the same applies to data platforms and cybersecurity. “As more of daily life moves onto digital rails, intelligence and trust have become our modern currency,” Konig says. In her view, the next wave of innovation will depend less on speed and scale, and more on resilience, transparency and security by design.
This emphasis on trust is particularly pronounced in the UAE, where digital infrastructure and governance frameworks are evolving together. Konig also highlights the importance of keeping people at the centre of technology systems. “There is a growing recognition of the need for ‘human in the lead’, not just ‘human in the loop’,” she says, adding that adoption depends on systems feeling safe, fair and trusted.
AI agents and the rise of non-human identities
As organisations deploy more autonomous systems, a new challenge is emerging around identity and access. Roland Daccache, Senior Manager of Sales Engineering, says 2026 will see an explosion of AI agents and non-human identities across the enterprise.
“These agents will operate as privileged super-humans, with OAuth tokens, API keys and continuous access to data,” he explains. While this creates efficiency, it also introduces risk. “They will become the most powerful and potentially most dangerous entities in an environment.”
Daccache argues that traditional identity security models are not designed for this shift. In 2026, security teams will need real-time visibility, rapid containment and full traceability of agent actions. “When an AI agent wires money to the wrong account or leaks intellectual property, ‘the AI did it’ won’t be an acceptable answer,” he says.
Humanoid and autonomous systems
Robotics is also entering a more practical phase. Dr. Chaouki Kasmi, Chief Innovation Officer at the Technology Innovation Institute, says humanoid systems are moving beyond research prototypes into purpose-built deployments. “The real shift is not about mimicking humans,” he explains, “but about enabling safe, adaptive interaction in human-centric spaces.”
In 2026, Kasmi expects gradual integration of humanoid and autonomous systems in controlled environments such as logistics hubs, industrial sites and disaster zones. The emphasis, he says, will be on utility rather than spectacle, with reliability and safety guiding adoption.
Post-quantum readiness moves up the agenda
Alongside automation and AI, cybersecurity concerns are becoming more forward-looking. Kasmi highlights post-quantum cryptography as an emerging priority. While large-scale quantum attacks may still be years away, he notes that sensitive data is already at risk through “harvest now, decrypt later” tactics. “Post-quantum cryptography is a strategic safeguard that must be adopted proactively,” he says, particularly for government, national security and critical infrastructure systems where long-lived data must remain secure.
Payments through hybrid digital, physical journeys
In payments, innovation is increasingly focused on blending digital convenience with physical trust. Hennie Du Plessis, SVP for Middle East and Africa Payment Services at IDEMIA Secure Transactions, says the UAE is setting the pace for the next phase of payments growth.
Digital wallets, in-app payments and tap-to-pay have become mainstream, with physical cards continuing to play an important role. “The next growth phase will be defined by hybrid payment journeys, where digital and physical experiences work together,” he explains.
The workplace becomes more intuitive, less visible
As digital tools proliferate, attention is also turning to how technology feels to employees. Peter Oganesean, Managing Director for HP Middle East and Africa, says the smartest workplace tools will feel less like software and more like support embedded into the flow of work.
“As work becomes more distributed and expectations rise, people will increasingly fall out of sync with systems meant to support them,” he says. In 2026, successful tools will align technology, leadership and culture, creating environments that enable people rather than overwhelm them.
The convergence of AI and quantum computing
Looking further ahead, the convergence of AI and quantum computing is beginning to influence enterprise planning. Sergio Gago, CTO at Cloudera, says that beyond 2026, quantum and AI pipelines will gradually integrate, particularly in optimisation, simulation and materials discovery. High-performance computing and AI are already moving toward hybrid architectures, bringing together GPUs, CPUs and eventually quantum simulators under unified orchestration.
“Quantum can act as an accelerator and help solve problems that were previously impossible,” Gago says.
For organisations, the challenge lies in preparing data architectures that support this convergence. Gago emphasises the importance of a true data fabric that enables access across cloud, data centres and the edge, while embedding governance and traceability. “The future is not about choosing sides,” he says, “but about bringing systems together under a common architecture based on trust, efficiency and intelligence.”
As a passionate storyteller and content writer, Kushmita Bose loves weaving narratives that inform, inspire, and entertain. Whether she's unraveling tech revolutions, dissecting industry reports, or bringing a brand’s journey to life, Kushmita thrives on transforming ideas into captivating stories. When she’s not busy crafting content, you’ll probably find her daydreaming about her next travel adventure.