Industry executives and experts share their predictions for 2026. Read them in this 18th annual VMblog.com series exclusive.
By Faye Ellis, Principal Training Architect, Pluralsight
In 2026, AI and the cloud will continue to evolve hand in hand, shaping the next wave of digital transformation. Today’s AI innovation is deeply intertwined with cloud infrastructure as developers and researchers rely heavily on platforms like AWS, Azure, and Google Cloud to experiment, prototype, and scale ideas at speed. These services have democratized access to powerful computing resources, enabling even small teams to build sophisticated models without needing to own expensive hardware. Much of this groundwork has been laid in recent years, but as we look ahead to 2026 and beyond, the challenge is no longer about proving what’s possible, it’s about delivering on the hype and turning promise into practical value and ROI.
There’s been ongoing debate about whether the AI bubble will burst, and 2026 may be the year that question is answered. Over the past few years, organizations have poured billions of dollars into AI initiatives, driven by the belief that these technologies will make everything easier, faster, and more efficient. While AI has certainly improved aspects of daily work, including automating repetitive tasks, enhancing analytics, and enabling smarter decision-making, the reality is that human input remains essential. Current tools are not yet seamlessly embedded into workflows, and they often require significant effort to integrate and manage. The dream of a “super assistant” that anticipates needs and executes flawlessly is still aspirational, but the momentum suggests we’re inching closer. Personally, I’m excited to see that vision come to life.
Looking forward, I expect the next phase of AI development to focus on sophistication rather than novelty. We don’t need more chatbots or gimmicky features that add complexity without real value. Instead, the emphasis should be on making AI an invisible yet powerful layer within the tools we already use. This means moving beyond the trend of shoehorning AI into existing products for marketing appeal and instead embedding intelligence in ways that feel natural and intuitive. When AI becomes so well integrated that its presence is almost imperceptible but its impact is obvious, that’s when we’ll know it has matured.
One way this will happen is through deeper partnerships between AI companies and established software platforms. Rather than building standalone solutions, vendors will collaborate to infuse intelligence into widely adopted tools, creating ecosystems where AI augments rather than disrupts. Imagine a project management software that reallocates resources based on predictive analytics, or CRM systems that proactively suggest strategies for client engagement based on historical patterns and sentiment analysis. These enhancements won’t feel like separate “AI features,” they’ll simply become part of how work gets done.
Another critical development will be the rise of domain-specific AI. General-purpose models have dominated headlines, but their limitations are clear when applied to specialized tasks. In 2026, expect to see more tailored solutions designed for industries like healthcare, finance, and manufacturing, where accuracy and compliance are non-negotiable. These models will leverage cloud-based training pipelines and federated learning to ensure scalability without compromising security or privacy.
Finally, the conversation around responsible AI will intensify. As integration deepens, questions about bias, transparency, and accountability will move from theoretical debates to operational imperatives. Organizations will need robust governance frameworks to ensure AI-driven decisions are ethical and explainable. Cloud providers will play a pivotal role here, offering compliance-ready environments and tools for monitoring and auditing AI systems.
In short, 2026 will be about making AI truly useful, trustworthy, and ubiquitous. The winners will be those who focus on integration, usability, and impact rather than chasing headlines or operating AI models without clear strategy and purpose. The cloud will remain the backbone of this evolution, powering the infrastructure that turns AI from a buzzword into a business-critical capability. The next year promises to be a defining moment in proving whether AI can live up to its potential, and I believe we’re on the cusp of that reality.
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ABOUT THE AUTHOR
Faye Ellis is Principal Training Architect, specialising in AWS, responsible for the AWSCertified Developer Associate, SysOps Administrator Associate and Security Specialty courses. Her other courses include Hands-On Troubleshooting With AWS, Hands-On Chaos Engineering, and EKS Basics. She also researches, writes and presents AWS This Week, a YouTube show designed to summarise the latest AWS updates. Faye has worked in the IT industry for around 20 years, working in SysOps, DevOps and Architecture roles with mission critical systems across a wide range of industries including financial services, telecommunications, government and healthcare. Faye is super passionate about cloud technology and understands firsthand how important it is to keep your skills up to date so that you can get to work on the coolest projects out there.
