Content Map
#1. The Rise of AI Agents
#2. Computer Use Agent Applications as Digital Hands
#3. GenAI Becomes a Core Organizational Capability
#4. Physical AI Brings Intelligence into the Real World
#5. Scaling AI Through Smarter Hardware
#6. Taking Control with Specialized and Sovereign AI
#7. Building Trust, Control, and Identity in AI Systems
Artificial intelligence has reached a turning point. The surprise-filled early days, when each new chatbot or model release seemed to rewrite headlines, are behind us. In 2026, the story is different. AI is now entering a more mature phase, defined by the practical reality of getting work done. Leaders are no longer asking if AI will matter, but how it will reshape enterprise strategy, operations, and competitive advantage.
This year, we’re seeing AI trends that reflect this shift: models are becoming agents, automation is developing into collaboration, and competitive advantage now depends on how successfully leaders get people to work and AI systems to work together. From AI superfactories to domain-specialized models and machine-led discovery, the trend shaping 2026 will determine who leads and who falls behind.
Need more proof? Let’s break down the top 7 AI trends that matter most this year and why they represent the next wave of transformation across every industry.
The most important shift is the move from “Copilot” (which requires constant prompting) to autonomous agents. Unlike traditional AI tools that respond to single prompts or perform narrow and complex tasks, Agentic AI can plan, act, and adapt across multiple steps to achieve a goal. These systems can redesign workflows, managing the entire flow, including scheduling meetings across teams, conducting market analyses, handling procurement, or even driving parts of customer engagement from start to finish. In a recent survey by PwC, 69% of senior executives admitted to adopting agentic AI in their companies. 73% of survey participants say that effectively using AI agents will give them a major edge over competitors in the next year.
A marketing agent is a case in point. It doesn’t just stop at writing a plan for a marketing campaign like a chatbot, but can also actually execute it. It can log into your CRM, research leads, send personalized emails, and schedule meetings on your calendar, all without you needing to prompt it at every step.
AI agents operate alongside human teams, taking on repetitive or time-consuming tasks while leaving human judgment for important decisions.
For leaders, this transformation impacts the entire organization. Agentic AI changes how work gets done, how teams are structured, how decisions flow, and how performance is measured. Companies that clearly define agent responsibilities, set strong governance and guardrails, and design processes where humans and AI agents collaborate effectively are the most successful ones.
Another rising star of the coming year is Computer-Use Agents – systems that can operate software interfaces just like humans do. Instead of needing APIs or custom integrations, these agents watch, click, type, drag, and navigate tools on their own. It’s like a digital worker who can use Excel, Salesforce, or Notion in your team.
To make it clear, here is how “computer use” works:
This technology will be the future of AI applications for many reasons. Business tasks require jumping between different tabs and apps. Instead of automating one system at a time, they can automate entire processes from end to end, from entering data, generating reports, updating CRM entries, scheduling meetings, or sending follow-up emails.
Early adopters are using these agents to free up employees from digital busy work, reducing hours spent on admin tasks. It also reduces integration costs. There is no need to hire developers to connect apps together. If a human can do it by clicking, AI can do the same.
Bloomberg predicts that the GenAI market could reach $1.3 trillion within 10 years, highlighting the potential for huge industry growth. In the early wave of AI adoption, large language models and generative models were treated as experimental tools. They’re useful for brainstorming, content creation, or quick automation wins. In 2026, generative AI shouldn’t be a collection of isolated tools. It will become a central organizational resource that everyone can use, similar to cloud services or internal platforms.
This change is happening because businesses are learning where the real business value comes from. GenAI works best when it’s connected to core systems, company data, and everyday workflows. Leading organizations are creating internal GenAI platforms that support many teams at once, while also meeting security, privacy, and compliance requirements.
We mostly think of AI living only in apps or dashboards, powering chatbots, content tools, or decision engines. But this year, things will change. AI is now built into machines that can see, move, and act, such as robots, drones, vehicles, and smart equipment. And we call it Physical AI.
What is Physical AI? Physical AI is what happens when you give an AI “brain” a physical body. Unlike traditional factory robots that are programmed to do the exact same movement thousands of times, Physical AI systems can see, feel, and learn from the world around them. They can independently move materials and adjust production lines. In healthcare, robots assist doctors during surgery or provide patient support. In 2025, the global physical AI market reached $55.13 billion and is expected to soar to $68.54 billion by 2034, growing at an annual rate of 33.5%.
This technology doesn’t just lie in research labs. Amazon is deploying robots that can handle “high mix” items. They can pick up a heavy textbook, a soft t-shirt, and a fragile glass bottle all in the same shift without being re-programmed.
This big change brings practical and measurable value to businesses. These systems can improve safety, reduce labor shortages, and increase efficiency where software alone is not enough. However, they still come with new challenges, including higher costs, safety standards, and the need for close coordination between humans and machines.
In the past decade, AI progress depended on bigger models and larger datasets. However, things have changed. Building bigger models isn’t the only way to grow your capabilities. Energy costs, chip shortages, and environmental targets have forced us to shift to hardware-aware AI.
This is a positive sign as AI will become more affordable and predictable, unlocking wider adoption without runaway costs or dependencies. The smaller the AI models become, the lower the price of running them is. So, organizations can expand AI without ballooning operational expenses.
Not just stop at saving money; it’s also about saving the planet. Smarter hardware and energy-optimized models mean companies can scale AI initiatives while staying aligned with ESG and carbon-reduction commitments.
Because the models are becoming smaller, you can run them on your own “Edge” hardware. Hence, your data stays in your building, and you aren’t dependent on a giant tech company’s cloud.
2026 is no longer the time for general-purpose AI, like the early versions of ChatGPT, because of risks to privacy, security, accuracy, and inadaptability. Many organizations are investing in specialized and sovereign AI systems.
Specialized AI knows everything about your business or industry since it’s built on specific data and domain knowledge. We now have “Vertical AI” built specifically for fields like Law, Medicine, or Manufacturing. Also, these models focus on a narrow field; they are likely to make fewer hallucinations. They understand the specific jargon, rules, and “physics” of their industry. It doesn’t just “chat” but uses your company’s unique history and data to help you make better, faster decisions.
At the same time, sovereign AI allows companies and governments to have greater control over their data and technology. Sovereign AI runs on local or dedicated infrastructure and follows regional laws and regulations. That’s why the UAE, India, and the UK are building their own AI systems to ensure their data stays within their borders and follows their own laws. Plus, sovereign models are trained in local languages and cultural norms. For example, an AI developed in Japan or Saudi Arabia understands local business practices and social expectations much better than a model built in Silicon Valley.
As AI is embedded deeply in every business and AI-generated content and autonomous agents are becoming part of our daily lives, companies can’t treat responsible governance and trust as afterthoughts.
First of all, it’s about digital provenance. It’s not enough to simply post a video or a report; you must prove its authenticity. Most professional AI content now includes a digital “birth certificate” (provenance tag). This allows users to see exactly which AI generated a file and whether a human edited it, helping to combat deepfakes.
Another consideration is the use of Digital IDs for AI agents. Just as employees have ID badges, AI agents now have Digital IDs. When an agent tries to book a flight or access a database, it must present a “Know Your Agent” (KYA) credential. This confirms that the agent is authorized by a specific company and has set spending limits.
Governance isn’t paperwork anymore; its protection is built into every part of the AI system. If an AI makes an unethical suggestion, the system automatically blocks it in real-time. In case an AI rejects a loan or a job application, it is now legally required to provide a clear, human-readable reason for that decision.
The changes we see in 2026 show that AI is moving beyond the “curiosity” stage. People won’t be amazed by what I can do; we now rely on what it does.
For business leaders, the lesson is clear: having the flashiest AI or the biggest budget isn’t enough. Success now depends on how well you manage AI agents, run secure sovereign AI, and build trust with clear, transparent governance.
As AI moves out of screens and into real-world applications, the focus isn’t just “digital transformation.” The goal is to create a hybrid organization where humans and machines work together smoothly. The future isn’t coming. It’s already here.
Contact us today to explore how your organization can turn these top AI trends for 2026 into a real business advantage.
Content Map #1. FPT.AI #2. Neurond AI #3. VinAI #4. VNG #5. CMC Corporation #6. VinBrain #7. Tiki AI #8. MobiFone AI #9. ELSA Speak #10. MoneyLover Moving beyond a global trend, artificial intelligence is becoming one of Vietnam’s strongest technological frontiers. Over the past decade, Vietnam has rapidly proved to be a rising AI […]
Read More >
