Nine Predictions for AI in 2026, from the Father of AGI

By Dr. Ben Goertzel

Twenty years ago, when I first coined the term “Artificial General Intelligence,” the idea of machines matching human-level thinking felt like science fiction to most observers. Today, as CEO of the Artificial Superintelligence Alliance and someone who has spent 3+ decades building toward this goal, I can tell you: the science fiction is rapidly becoming science fact and practical everyday product. But we’re not there yet—and 2026 will be a fascinating year of watching AI capabilities race ever closer to that threshold.

This year won’t be defined by a single dramatic breakthrough. Instead, we’ll see a steady accumulation of advances that make AI genuinely useful in ways that felt impossible just two years ago. Here’s what I expect to unfold.

1. Assistants That Actually Remember You

The AI assistants we use today are remarkably capable but frustratingly forgetful. Ask ChatGPT something today and it has no memory of your conversation last week. In 2026, expect research assistants and personal assistants with genuine cognitive architecture—long-term memory that builds understanding of your goals over time, working memory that tracks complex multi-step projects, and the ability to take autonomous action toward your objectives rather than simply following narrow instructions. These won’t just answer questions; they’ll anticipate needs and work alongside you.

2. AI Art That Surprises Its Creators

Current AI-generated art, for all its technical impressiveness, often feels derivative—a sophisticated remix of existing styles. This year will bring AI artistic creations with genuine novelty. By moving beyond standard large language models and diffusion techniques to incorporate more innovative computational creativity methods, we’ll see AI music improvisation with truly unique character, visual art that doesn’t merely combine existing aesthetics but invents new ones. The difference will be unmistakable: art that surprises even the people who built the systems.

3. Business Intelligence You Can Trust

One of AI’s most frustrating limitations has been its tendency to confidently state things that simply aren’t true—the hallucination problem. For business applications, this has been a dealbreaker. In 2026, we’ll see AI models that handle reasoning about business data reliably by grounding their linguistic capabilities in symbolic reasoning tools doing in-depth processing of quantitative, relational and graphical business data. These systems will know what they know and, crucially, know what they don’t know. Expect AI that can analyze your company’s data and give you answers you can actually stake decisions on.

4. Epic Mathematical Breakthroughs

Last year, AI systems conquered the International Mathematical Olympiad—problems designed to challenge the world’s brightest students. But contest problems, however difficult, are designed to be solved. The next frontier is genuinely open mathematical questions that have stumped humanity’s best minds for decades. I expect 2026 to bring AI contributions to longstanding unsolved problems, possibly including progress on challenges like the Clay Millennium Prize problems. Mathematics may be one of the next places where AI demonstrates truly superhuman capability.

5. Animation at the Speed of Imagination

Tools like Veo3 can already generate compelling eight-second video clips from text descriptions. This year, that limit will shatter. More importantly, AI will learn to artfully connect short sequences into cohesive long-form animation, understanding narrative flow and visual continuity. For independent creators, small studios, and educators, this means the ability to produce animated content that previously required teams of artists and months of work.

6. AI for Organizational Governance

Managing organizations—coordinating people, allocating resources, making fair decisions—remains remarkably difficult. AI agents capable of genuinely assisting with governance and management will emerge this year. For traditional companies, this means better-informed strategic decisions. But the impact may be even more significant for novel organizational forms like decentralized autonomous organizations and open-source collectives, which have long struggled with coordination challenges that AI is well-suited to address.

7. Robots That Navigate Our World

The gap between robots in controlled factory settings and robots in messy human environments has been vast. 2026 will narrow it substantially. Expect humanoid robots that can move through homes, offices, and public spaces without confusion—understanding spatial context, recognizing objects and their purposes, and executing simple practical tasks on request. We’re not talking about robot butlers, but robots that can reliably fetch items, open doors, and assist with basic physical tasks.  The transition from amazing robot demo videos to Rosie the Robot in every home will not be completed this year, but we should see some substantial steps forward.

8. Breaking the Languages Barrier

Billions of people speak languages and dialects that have no written form or significant online presence—effectively locked out of the global internet. AI-powered voice-to-voice translation has long promised to change this, but results have been poor for non-dominant languages. This year, we’ll see real progress on translation systems that work for communities the digital revolution has largely bypassed, potentially bringing unprecedented connectivity to the world’s linguistic minorities.

9. The Wild Card: Could AGI Arrive This Year?

Here’s where I must be honest about uncertainty. A genuine breakthrough to human-level artificial general intelligence during 2026 is possible—not probable, in my view, but total possible. If it happens, everything else on this list becomes a footnote, because an AGI system would rapidly transform every domain it touches.

Continued scaling of current large language models likely won’t deliver this breakthrough. But multiple alternative approaches are being actively pursued: Yann LeCun’s world-modeling architecture, my own team’s Hyperon project integrating neural networks with logical reasoning and evolutionary learning … and many, many others working in less public settings. My best guess places the breakthrough in 2027-28 rather than 2026—but in a field moving this fast, nothing is impossible but certainty.

What This Means for All of Us

These predictions share a common thread: AI moving from impressive demonstrations and tools that are useful around the margins to agents providing critical utility in everyday life – and now and then, creative and intellectual breakthroughs at the frontier.  The technology is maturing from a novelty into infrastructure.

This transition demands both optimism and responsibility. The potential benefits—in scientific discovery, creative expression, accessibility, and human capability—are extraordinary. But so are the stakes. As these systems grow more powerful, questions of alignment, safety, and equitable access become not abstract concerns but urgent practical challenges.

I keep returning to a point I made in a recent conversation with Jaron Lanier, as part of an ongoing series we call the Ten Reckonings of AGI, focused on the ethics of the technology. Once you seed an intelligent, self-organising AGI mind, it will inevitably reach a stage where you cannot fully follow or predict what it is doing. But that loss of complete understanding is not, in itself, a reason to reject or fear it. I used the analogy of my own children. I would like to understand everything they do, but I do not, and I would never argue that uncertainty justifies control or destruction.

Complex, self-organising systems grow and evolve beyond our full comprehension. That is true of humans, and it will be true of advanced AI. The real reckoning is not whether we can maintain perfect oversight, but whether we choose to build these systems with compassion, responsibility and decentralised, participatory governance from the outset, rather than advancing the technology without agreeing what kind of moral relationship we want to have with it.

After decades working toward artificial general intelligence, I am more convinced than ever that getting this right is humanity’s most important project. The year ahead will bring us meaningfully closer to that goal—one practical advance at a time.

Dr. Ben Goertzel is CEO of the Artificial Superintelligence Alliance and SingularityNET, Chairman of Humanity+, and has led research on artificial general intelligence for over three decades. He coined the term artificial general intelligence (AGI) and has been researching AI since the 1980s. He formalized the term, which refers to the point at which AI supersedes human abilities in his 2005 book Artificial General Intelligence, and is now CEO of SingularityNET (the first large-scale decentralized AI platform). He also previously led the cognitive software behind Sophia the Robot, is co-creator of Desdemona the humanoid robot & now works at the frontier of humanoid robots with minds.