What is going to be the next big thing after AI?

Since the day generative AI models like OpenAI's ChatGPT burst into the mainstream, it has become hard to deny that we are living in an arguably eccentric and fast-forwarded age. An age, reshaped by software and machines that think and are accessible to the masses, and apparently making those once 'cool but non-accessible' tools ubiquitous. 

A few years ago, when a tool like this was nothing more than an experiment at some no-name labs, it is now incorporated as an essential daily copilot for millions across the globe. Apparentlyalmost every industry is reorganising around what it can make possible.

And the tectonic shift is now functioning as the launching pad for the next wave of disruption, in every new way possible, or even superseding it.

This piece is an effort to map out the strongest contenders that experts and researchers often mention when discussing 'What comes after AI?', how they might interlock with AI, and what these cutting-edge technologies promise to deliver to make the world a better place.

Quantum Computing

Many thought leaders from industry and academia argue that quantum computing is the most obvious candidate for the next breakthrough at that radical level after AI.

Quantum devices won't replace classical computers for everything, but for specific classes of problems (quantum chemistry, optimisation, some machine-learning primitives), they promise exponential or considerable polynomial advantages.

That matters because AI itself is currently limited by compute and algorithmic bottlenecks, and quantum speedups could multiply what AI can do (i.e., enabling far faster molecular simulations or new optimisation routines for logistics and materials).

AI excels at pattern recognition, but it encounters some fundamental limitations when simulating complex molecular interactions, optimising massive supply chains or breaking advanced encryption.

Governments, elite industry, and academic labs are accelerating investments and roadmaps toward useful, fault-tolerant machines. Although there are still many fundamental engineering issues to overcome, pivotal moments are underway to make quantum computing practical rather than theoretical.

The quantum computing market reached between 1.8 billion USD and 3.5 billion USD in 2025, with projections indicating it will grow to 5.3 billion USD by 2029.

Harvard researchers demonstrated a fault-tolerant quantum system using 448 atomic quantum bits, successfully suppressing errors below a critical threshold where adding more qubits reduces rather than increases errors. Then, engineers at Princeton built superconducting qubits that last three times longer than today's best, with one researcher noting that this could enable a hypothetical thousand-qubit computer to operate roughly one billion times better than current industry standards.

In March 2025, IonQ and Ansys ran a medical device simulation on a 36-qubit computer that outperformed classical high-performance computing by 12 per cent – one of the first documented cases of practical quantum advantage in real-world applications.

Brain-Computer interfaces

If quantum computing represents the future of computational power, then the brain-computer interfaces (BCIs) represent the future of human-machine interaction.

This field is undergoing a drastic shift from no-name laboratory disciplines to clinical applications with profound implications. Plus, MIT Technology Review readers voted brain-computer interfaces (BCI) as their addition to the annual list of 10 Breakthrough Technologies.

BCI technology is accelerating rapidly. Speech BCIs can now infer words from complex brain activity at 99% accuracy with less than 0.25 second latency– something that was unimaginable just ten years ago, when early systems could merely produce around 290 short words.

According to the World Economic Forum, the BCI industry is expected to grow from approximately 1.7 billion USD in 2022 to 6.2 billion USD by 2030, as companies like Precision Neuroscience, Elon musk's Neuralink, and other neurotech companies/startups work toward that.

Synthetic Biology

While AI learns from data and quantum computers manipulate subatomic particles, synthetic biology technology rewrites the code of life. It could design and construct new biological systems or redesign existing ones. This field represents the most profound frontier, i.e., engineering organisms to solve problems that chemistry and physics cannot. 

Synthetic biology had an estimated market size of 20.01 billion USD last year and is poised to continue growing.

At the International Genetically Engineered Machine (iGEM) conference in Paris, it became clear that synthetic biology is no longer a niche field from some sophisticated academic labs but a unified, realistic science that can redesign life for a better future.

If achieved, the potential applications are remarkable. Engineered plants that could consume plastic waste, yeast that could produce medicine, crops that could grow in unusual conditions with enhanced nutrition, and lab-grown meat that could eliminate the need for livestock farming.

According to consulting firm McKinsey, by this year, the economic value of synthetic biology and bio-manufacturing is expected to reach 100 billion USD, and 60 per cent of global material production could be feasibly achieved through bio-manufacturing.

The title What is going to be the next big thing after AI? may sound misleading, as the following big things won't really render AI obsolete; instead, they'll be powered by it, and this is the factual beauty of science. The authour van be reached at sheikhzyhad@gmail.com