“As of March 29, 2026, artificial intelligence systems outperform humans in general computer use tasks.”

Early results show even the most advanced systems still struggle — revealing a surprisingly large gap between AI performance and true expert-level knowledge. 'When AI systems start performing extremely well on human benchmarks, it's tempting to think they're approaching human-level understanding,' Nguyen said. 'But HLE reminds us that intelligence isn't just about pattern recognition -- it's about depth, context and specialized expertise.'

So it is quite possible that LLM accuracy surpasses human accuracy in 2026 for many enterprise tasks. The key thing to remember is that as frontier LLMs get more capable, their accuracy will continue to improve, while human accuracy will likely be unchanged. 'The automation of knowledge work using LLMs is the key focus of many enterprise generative AI pilots.'

Comparing AI to individual intelligence misses something essential about what human intelligence is. Our intelligence doesn’t operate primarily at the level of isolated individuals. It is social, embodied and collective. Once this is taken seriously, the claim that AI is set to surpass human intelligence becomes far less convincing. AI systems, by contrast, do not cooperate, negotiate meaning, form social bonds or engage in shared moral reasoning.

Advances in AI are rapidly rippling across society. UC researchers and the patients they work with are showing the world what's possible when the human mind and advanced computers meet.

OpenAI’s recently released GPT-5.4 “Thinking” model scored 83.0% on the GDPVal benchmark, placing it at or above the level of human experts on economically valuable tasks. Morgan Stanley predicts 'Transformative AI' will become a powerful deflationary force, as AI tools replicate human work at a fraction of the cost.

OpenAI also gave GPT-5.4 “native computer-use” skills- it can navigate software UIs by interpreting screenshots and issuing mouse/keyboard commands. In practice this means agents using GPT-5.4 can browse websites, fill forms and manipulate documents on their own, improving automation. In internal benchmarks (the GDPval test of real-world job tasks), GPT-5.4 achieved a new state-of-the-art 83.0% success rate versus 70.9% for GPT-5.2.

AI is changing work by absorbing routine effort, reshaping collaboration, and sharpening the importance of human judgment. The first bucket of tasks are those that AI can handle fully—tasks that are about quick summarization, analysis, or the first draft of content.

After years of fast expansion and billion-dollar bets, 2026 may mark the moment artificial intelligence confronts its actual utility. The era of AI evangelism is giving way to an era of AI evaluation, demanding rigor over hype and more work around designing human-centered AI systems.

Improved handling of dynamic UI elements, modal dialogs, and multi-step form completion made computer use more viable for production RPA-style workflows. Updated computer use capabilities reduced error rates on desktop application interactions by approximately 40% compared to the initial release.

Google introduced major updates to Gemini within its Workspace productivity suite, allowing the AI assistant to generate documents, spreadsheets, presentations, and other files by pulling information from across a user's emails, chats, files, and the web. AI assistants embedded in workplace platforms are becoming execution engines that assemble finished outputs from enterprise data.

By 2026, we are poised to shift from “What can AI do?” to “How well and how safely can it do it?” AI Agents Become Collaborative Teammates. Rather than isolated tools, AI systems will act more like digital coworkers – autonomous agents that can plan, execute, and complete tasks with minimal human oversight. AI will not simply replace jobs – it will reshape them. By handling repetitive or analytical work, AI can empower humans to focus on creativity, strategy, and emotional intelligence. The narrative is shifting from “AI vs humans” to “AI + humans” working together.

Elon Musk stated at the World Economic Forum in Davos that, at the current pace of AI development, AI's intelligence level will surpass that of any single human individual by the end of 2026.

AI agents can perform impressive tasks in controlled environments. They struggle when integrated into actual business workflows. The evidence suggests transformation rather than elimination, with agents handling routine tasks while humans focus on judgment, strategy, and relationship management.

Tasks that had become routine with AI suddenly felt harder without it. John Nosta, founder of innovation and tech think tank Nosta Lab, calls this the "AI rebound effect" — when better performance masks declining ability. "The skill set actually falls below baseline," he said. The danger isn't only dependency — it's regression. Because AI systems deliver fast, polished answers, they can also distort how people judge their own abilities.

When it comes to AI, people have a greater appetite for using the technology as a collaborative tool to assist humans, rather than a replacement for them: Some 94% of respondents favor using current-day AI to augment human work. That percentage rises to nearly 96% when the survey described a more advanced version of AI that may emerge in the future.

AI is powerful—but it is narrow intelligence, not general human understanding. In 2026, there are domains where AI already outperforms humans decisively, such as data processing and repetitive cognitive tasks. However, humans still dominate in creativity with purpose, leadership and influence. The most important shift in 2026 is not AI replacing humans, but AI augmenting human intelligence.

As of early 2026, no AI system has achieved artificial general intelligence (AGI) capable of outperforming humans across all general computer use tasks; leading models like GPT-5 or equivalents excel in narrow domains but fail in novel, creative, or multi-step reasoning requiring human-like generalization.

Two years of production AI deployment have produced real data on where AI genuinely surpasses human performance and where human capabilities remain superior.

As Milojicic noted, literally every prediction was related to, influenced by or directly driven by AI. Six fall under the heading of applied AI.