The escalating power of artificial intelligence and emerging quantum capabilities is poised to reshape global security, regulation and market design in 2026, according to leading figures across the blockchain and AI sectors.
Speaking with Yellow.com, experts points toward a structural shift where governments, enterprises and financial markets will increasingly depend on blockchain-based infrastructure, not for hype-driven adoption, but to withstand the next era of computational threats.
Across industry, concerns are mounting that AI systems and quantum tools have outpaced traditional cyber-defense models.
Blockchain To Become A National-Security Priority
As enterprises accelerate deployment of AI-driven automation, and as prediction markets, business platforms and data ecosystems grow more agent-native, the need for verifiable computation, tamper-proof data, and transparent system design is becoming unavoidable.
Shiv Shankar, CEO of Boundless, says the turning point is already here, describing the landscape as a “sword and shield” conflict in which AI and quantum computing act as offensive capabilities, while blockchain and zero-knowledge cryptography provide defensive guarantees.
“AI and quantum computing are the sword… Blockchain and zero-knowledge cryptography are the shield.”
He argues that tamper-proof ledgers and verifiable computation will become national-level infrastructure because “any manipulation is immediately detectable," he said.
That shift dovetails with a broader transition in how enterprises interact with AI tools.
AI To Reshape Enterprise Workflows And Regulatory Demands
Rather than relying solely on general-purpose chat interfaces, companies are expected to move towards orchestrator systems, AI agents that can set tasks, run workflows, and carry out continuous actions across internal and external environments.
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Titus Capilnean, VP of Go-to-Market at Civic, notes that rising complexity around automation, personalization and compliance will force businesses to adopt explainable AI systems, verifiable models, and identity-backed agent interactions.
He says the next phase of AI adoption will require “memory, personalization, and orchestrators,” alongside privacy-preserving tools like passkeys and zero-knowledge proofs.
Prediction Markets Enter A Fully Agent-Driven Phase
Market design is also entering a new era.
Prediction platforms, once dependent on human liquidity, are beginning to integrate fully autonomous agent economies.
David Minarsch of Olas says the key unlock is not simply better forecasting models, but the ability for agents to run the full lifecycle of prediction markets, creating markets, sourcing information, trading, and resolving outcomes.
That agent-native structure, he argues, allows prediction markets to scale to any question where incentives matter.
At the same time, he warns that trust must be “engineered into the mechanism,” as recent governance failures in crypto prediction markets show that volume alone doesn’t guarantee reliability.
Meanwhile, user attention is concentrating around breakout platforms.
Yu Hu, CEO of Kaito AI, says 2025 revealed an important pattern: even during a market downturn, sectors like perpetual DEXs and prediction markets saw explosive growth.
He points to Polymarket as a leading example heading into 2026, supported by on-chain rails and mainstream user engagement.
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