In 2026, AI will advance significantly with the rise of multimodal models capable of real-time video understanding, widespread adoption of AI agents in business, and the emergence of humanoid robots achieving product-market fit. While AI-driven automation may accelerate job displacement amid economic challenges, these technologies are poised to become integral to various industries, marking a pivotal shift toward more sophisticated and practical AI applications.
In this update, David Shapiro shares insights gathered from extensive conversations with industry insiders as he works on his book, “The Great Decoupling,” focusing on AI trends expected in 2026. He highlights that the biggest technical advancement will be the rise of multimodal AI models, which will move beyond text and images to include real-time video understanding and generation. This expansion into video-native models marks a significant evolution from language-based AI, as tokenization techniques improve and broaden to encompass various data types, setting the stage for more sophisticated AI capabilities.
Shapiro also discusses the ongoing development of benchmarks used to measure AI performance. While benchmarks continue to saturate incrementally, he cautions that overfitting to benchmarks can lead to weaker models, as seen with some current AI systems. He anticipates a tipping point where AI technologies transition from experimental novelties to production-ready tools across a wider range of tasks. Additionally, he points to the emergence of world models and interactive real-time AI, particularly in gaming engines, where early toolkits and proofs of concept will appear, though fully AI-native game engines are unlikely to be mainstream in 2026.
On the business front, 2026 is expected to be the year when AI agents gain widespread recognition for their practical value. Many companies are already experimenting with AI agents, especially in HR and legal departments, as well as industry-specific applications. Shapiro compares this moment to the evolution of virtualization technology and the smartphone revolution, suggesting that AI agents will reach a critical mass of usefulness and adoption, becoming integral to business operations. He emphasizes the importance for developers and businesses to stay at the cutting edge of agent technology to capitalize on this shift.
Regarding employment, Shapiro addresses concerns about job displacement due to AI. While headline unemployment rates appear stable, underlying issues such as the rise of gig work, precarious employment, and youth unemployment paint a more concerning picture. He predicts that an upcoming recession could accelerate AI adoption as companies seek to reduce costs by replacing human labor with AI agents, leading to a “jobless recovery.” This pattern mirrors the rapid adoption of remote work technologies during the pandemic, suggesting that AI-driven automation will become a key strategy for businesses navigating economic downturns.
Finally, Shapiro turns to humanoid robots, forecasting that 2026 will be the year these robots achieve product-market fit. After years of proof of concept and minimum viable products, several companies—including Tesla, Boston Dynamics, and various Chinese firms—are poised to deliver robots whose capabilities justify their cost, leading to increased demand. He also touches on potential short-term squeezes in power and chip supply due to rising AI infrastructure demands but remains optimistic that market forces and investments will resolve these issues. Overall, Shapiro paints a picture of 2026 as a pivotal year for AI technologies becoming more integrated into both business and daily life.