Page updated on January 15, 2026
Author: Mark Lydon, Senior Content Manager
As we look to 2026, the latest AI trends are not only shaping the way consumers interact with devices, but also transforming enterprise infrastructure, manufacturing, and urban environments.
Artificial Intelligence (AI) is entering a new chapter in 2026. The past few years have brought immense excitement around generative models, new hardware, and enterprise adoption, but now the spotlight is shifting. In 2026, success in AI will be defined less by headline-grabbing demos and more by real-world delivery, infrastructure maturity, and intelligent scaling across sectors like telecom, infrastructure, and manufacturing.
Below, we break down the most important AI trends for 2026 that business leaders, developers, and strategists should be tracking.
Table of Contents
1. On-device AI in smartphones will face a reality check
2. Neoclouds will struggle to unlock enterprise AI at scale
3. Physical AI will attract new investment and innovation
4. Smarter AI building management will expand use cases
5. AI will help manage the grid, not control it
6. AI will renew extended reality interest
7. Open standards will reshape AI data centers
On-device AI in smartphones will face a reality check
Smartphone makers spent much of 2025 hyping new models as “AI-powered.” Google, Samsung, Apple, and Huawei all released handsets with chips capable of running AI models directly on the device. While the hardware is impressive, the software has not kept pace.
Features like AI photo editing, voice assistants, and real-time translation are common across models but are not meaningfully different from existing tools. Consumers are not yet seeing the kind of daily utility that would justify upgrading to a premium AI-enabled device. Without stronger use cases, on-device AI will not be the main driver of premium smartphone adoption in 2026.
Smartphone vendors must move beyond check-the-box AI features. To sustain demand, they will need to focus on delivering experiences that improve daily tasks, preserve privacy, and reduce friction in meaningful ways.
Neoclouds will struggle to unlock enterprise AI at scale
Among the most emerging trends in AI, neoclouds represent a new layer of infrastructure that aims to bring cloud-like AI compute to enterprises without high upfront costs. Neoclouds offer Graphics Processing Unit (GPU) Infrastructure-as-a-Service to enterprises eager to adopt AI. These neoclouds promised a way around high upfront costs for hardware and data centers. But their business models face serious challenges in 2026.
Capital intensity has soared, with some neocloud players investing two to three times more than revenue to remain competitive. To survive in this market, ABI Research Principal Analyst Leo Gergs suggests that neoclouds need to tap into the enterprise domain. He says, “With these dynamics playing out, neoclouds will be forced into a rapid and unavoidable repositioning.” He continues, “To monetize their heavy investments, they must move aggressively closer to enterprise verticals and position themselves as embedded partners within manufacturing floors, clinical systems, financial operations, and energy grids.“
In other words, neoclouds must offer not just compute power, but also vertical-specific applications, integration support, and proven templates for Return on Investment (ROI).
The key hurdle remains the same. Around 95% of enterprise AI projects never move beyond the pilot stage. Neoclouds must demonstrate real value and build trust with enterprise customers over time, which makes 2026 a year of hard pivots, not broad deployment.
Physical AI will attract new investment and innovation
AI is no longer just about data centers and chatbots. In 2026, momentum continues to build behind Physical AI, the integration of machine intelligence into robotics, logistics, and real-world operations.
Semiconductor companies are expanding their offerings for edge compute. At the same time, robotics partnerships are making it easier for System Integrators (SIs) to bring solutions to market. Amazon, Honeywell, and others are working with AI-first robotics firms to build systems that can learn from video, simulate operations with synthetic data, and adapt more quickly to new environments.
ABI Research Senior Analyst George Chowdhury takes note of the rising role of China’s robotics manufacturers in physical AI. He states, “China’s robotics Original Equipment Manufacturers (OEMs) will continue to win ground over incumbent vendors. Increased competition will see FANUC, KUKA, ABB, and Yaskawa attempt to penetrate greenfield market verticals in search of renewed demand. Life science, healthcare, hospitality, and retail will become target markets.“
Smarter AI building management will expand use cases
Energy efficiency and predictive maintenance are pushing AI adoption in buildings. In 2026, AI platforms will continue to grow in environments where uptime is critical, including industrial sites. From there, the technology will spread to offices, public buildings, and retail locations.
This is part of the broader wave of latest AI trends where predictive insights and automation are being adopted across physical infrastructure and mission-critical environments.
Instead of full-system overhauls, most deployments will focus on targeted use cases like Heating, Ventilation, and Air Conditioning (HVAC) optimization or adaptive lighting based on occupancy and weather. Smarter sensors will play a critical role, capturing richer data with fewer devices and enabling more precise predictions.
Success in this space will depend on the ability to manage real-time data, integrate systems, and apply AI in a way that saves energy and improves building performance.
AI will help manage the grid, not control it
The surge in AI workloads has created a massive strain on power grids. Data centers and industrial users are consuming more energy than existing infrastructure can support. In 2026, governments will increasingly encourage companies to shift AI workloads to off-peak hours or explore self-sufficiency through private power generation.
While AI is straining the grid, it can also be used to reduce electricity usage. It will help utilities monitor grid health, forecast failures, and optimize load balancing. However, ABI Research Distinguished Analyst Michael Larner cautions that human operators will remain in control. “2026 will not witness AI taking control of the grid entirely. Human oversight will be required at all times, especially with regard to load balancing. AI tools will surface insights, but will not be acting autonomously.”
Larner stresses that regulatory and government approval will be needed before grids can act autonomously.
AI will renew extended reality interest
One of the most profound trends in AI is how it accelerates development in Extended Reality (XR) by enhancing real-time interactions, content generation, and user personalization. After years of stalled growth, the XR market is finally gaining traction in 2026 through innovative AI integrations. In tandem with lighter headsets, improved battery life, and better connectivity, there is a revitalized interest across both enterprise and consumer XR technologies.
AI enhances spatial understanding, supports real-time interaction, and enables adaptive content generation. Qualcomm, Samsung, and Apple are pushing XR innovation forward with advanced chipsets and dedicated software platforms. New devices from Meta, Pico, and Alibaba are also setting new benchmarks for latency and performance.
In addition, Generative AI (Gen AI) is reshaping how XR content is created. Applications range from travel assistance to virtual training to cooking tutorials. By 2030, ABI Research expects annual XR hardware shipments to surpass 80 million units, up from just over 11 million in 2024.
Open standards will reshape AI data centers
As AI workloads scale, the need for flexible, modular infrastructure becomes critical. In 2026, open standards will play a larger role in shaping AI data centers.
Projects like the Open Compute Project (OCP) and Ultra Accelerator Link Consortium (UALink) are making it easier for operators to build systems that combine accelerators, networking, and storage from multiple vendors.
ABI Research Senior Analyst Paul Schell emphasizes the importance of interconnect solutions to support AI data centers. He tells us that “There will also be significant activity in the interconnect space, as several new standards have emerged over 2025, alongside the maturation of existing challengers to NVIDIA’s proprietary NVLink, such as UALink.” He goes on to say, “This includes Broadcom’s Scale-Up Ethernet (SUE), unveiled in conjunction with the Tomahawk Ultra switch Application-Specific Integrated Circuit (ASIC), which competes with InfiniBand and NVLink.”
This push for interoperability will lower costs, reduce lock-in, and create more options for enterprises looking to deploy AI at scale.
Final Thoughts
The AI trends shaping 2026 reflect a clear pattern: real value is replacing hype.
Technology vendors must move from marketing narratives to solving real problems. Enterprises are demanding proven AI tools, not prototypes promising vague benefits. Infrastructure needs are pushing boundaries in energy, hardware, and software.
Whether in robotics, smartphones, buildings, or data centers, AI will thrive where it works seamlessly in the background. The winners in 2026 will be those who treat AI not as a buzzword, but as a system-level capability with measurable outcomes. Technology providers must provide industry-specific case studies and data-driven gains (e.g., % of energy savings), while mapping AI solutions to operational challenges.