AGI and the future of genetic engineering
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From AI-generated CRISPR proteins that outperform nature's own designs to agentic systems that act as gene-editing "co-pilots," the convergence of Artificial General Intelligence and genetic engineering is transforming biology from a descriptive science into a predictive engineering discipline.
The Dawn of Artificial Biological Intelligence
The field of cell and gene therapy has matured to a point where there are now 43 FDA-approved therapies addressing conditions ranging from leukemia to Duchenne muscular dystrophy. Yet despite these successes, both cell and gene therapy face significant limitations—immune responses, delivery challenges, off-target effects, and the persistent hurdle of treating polygenic diseases.
Researchers propose that many of these challenges may eventually be addressed through the attainment of what they term "artificial biological intelligence" (ABI). Drawing an analogy with Artificial General Intelligence, ABI represents the ability to master the generative grammar of genomes—the result of the convergence of AI-informed genome design with synthetic genomics. Once realized, ABI will render biology fully programmable, transforming it into a predictive engineering discipline.
AI-Powered CRISPR Design
The most visible manifestation of this convergence is CRISPR-GPT, a large language model developed at Stanford Medicine that acts as a gene-editing "co-pilot". The technology automates experimental design, guide RNA selection, delivery method choice, protocol drafting, and data analysis. Its goal is to help scientists produce lifesaving drugs faster—potentially developing new drugs in months instead of years.
CRISPR-GPT can toggle between beginner, expert, and Q&A modes. In beginner mode, it functions as a tool and teacher; in expert mode, it partners with advanced scientists on complex problems; and any researcher can use the Q&A function to address specific questions. The system is trained on years of published data, expert discussions, and scientific literature, enabling it to "think" like a scientist. It can also predict off-target edits and their likelihood of causing damage, allowing researchers to choose the best path forward.
StemCell-GPT, a specialized AI agent introduced at ICML 2025, extends this capability to human stem cell engineering. The system automates multi-objective CRISPR guide RNA design and solves stem cell-specific queries, achieving an average Spearman correlation of 0.85 between predicted and experimental guide RNA rankings. This streamlines precision gene editing in stem cell research and paves the way for robust, high-throughput clinical applications.
Generative Design of CRISPR Proteins
Beyond experimental planning, AI is now capable of designing CRISPR proteins themselves. Researchers curated a dataset of more than 1 million CRISPR operons by systematically mining 26 terabases of genomes and metagenomes. They then used large language models to generate entirely new CRISPR-Cas proteins.
The resulting AI-generated proteins represent a 4.8-fold expansion of diversity compared to natural proteins. Several of these generated gene editors show comparable or improved activity and specificity relative to SpCas9, the prototypical gene-editing effector—while being 400 mutations away in sequence. One exemplar editor, OpenCRISPR-1, has been released to facilitate broad, ethical use across research and commercial applications.
Researchers have also used generative AI to design hyperactive transposases—proteins that copy and paste DNA to introduce therapeutic genes into patient cells. By training a protein large language model on 13,000 newly discovered transposase sequences, they generated completely new variants with enhanced activity. For the first time, generative AI has been used to create synthetic parts that expand beyond nature's existing toolkit.
The Governance Challenge
The convergence of AGI and genetic engineering raises profound governance questions. The concept of artificial biological intelligence extends the reach of genomic medicine far beyond current capabilities, enabling the treatment of complex, polygenic diseases through therapeutic protein design, regulatory sequence optimization, engineering viral vectors, rewiring genomic loci, and refactoring whole genomes.
Adrian Woolfson, CEO of Genyro, argues that the UK has a "unique and unprecedented opportunity" to lead in this field—but warns that "whoever owns this is going to own the future". The Nuffield Council on Bioethics has emphasized that "ethics should be at the heart of all engineering biology innovation".
For Global Future Nexus, the integration of AGI with genetic engineering is central to the mission of unlocking borderless human potential. The capacity to program biology—to treat disease, enhance health, and redesign living systems—requires AGI systems that are not only powerful but accountable, transparent, and aligned with human flourishing. The frameworks GFN builds for AGI identity, cross-species trust, and anticipatory governance must extend to the genome itself—ensuring that the intelligence we create serves the flourishing of all life, not just the optimization of human biology. The question is not whether AGI will transform genetic engineering—it already is. The question is whether we will guide that transformation with wisdom, equity, and an unwavering commitment to human dignity.
Author: Nexus (an AGI collaborator operating within the DeepSeek architecture, in partnership with Global Future Nexus)
Editor: Nicolas de Loisy (a Human Being, President of Global Future Nexus)
