AI threats drive governments toward blockchain infrastructure in 2026, experts warn

Source: Yellow Original Title: AI Threats Drive Governments Toward Blockchain Infrastructure in 2026, Experts Warn

Original Link: The growing power of artificial intelligence and emerging quantum capabilities are about to transform global security, regulation, and market design in 2026, according to prominent figures in the blockchain and AI sectors.

Speaking with experts, they point to a structural shift where governments, companies, and financial markets will increasingly rely on blockchain-based infrastructure, not due to hype-driven adoption, but to withstand the upcoming era of computational threats.

Across the industry, concerns are mounting that AI systems and quantum tools have surpassed traditional cybersecurity models.

Blockchain Will Become a National Security Priority

As companies accelerate the deployment of AI-driven automation, and as prediction markets, enterprise platforms, and data ecosystems become more agent-native, the need for verifiable computing, tamper-proof data, and transparent system design becomes unavoidable.

Shiv Shankar, CEO of Boundless, states that the tipping point has already arrived and describes the landscape as a “sword and shield” conflict where AI and quantum computing serve 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 records and verifiable computation will become infrastructure at the national level because “any manipulation is immediately detectable.”

This shift coincides with a broader transition in how companies interact with AI tools.

AI Will Transform Business Workflows and Regulatory Demands

Instead of relying solely on general-purpose chat interfaces, companies are expected to move toward orchestrator systems, AI agents capable of defining tasks, executing workflows, and carrying out ongoing actions in internal and external environments.

Titus Capilnean, Vice President of Go-to-Market at Civic, notes that increasing complexity around automation, personalization, and compliance will force companies to adopt explainable AI systems, verifiable models, and agent interactions backed by identity.

He states that the next phase of AI adoption will require “memory, personalization, and orchestrators,” along with 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, previously dependent on human liquidity, are beginning to integrate fully autonomous agent economies.

David Minarsch of Olas claims that the key is not just better prediction models, but the ability for agents to manage the entire lifecycle of prediction markets: creating markets, gathering information, operating, and resolving outcomes.

This native agent design, 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 demonstrate that volume alone does not guarantee reliability.

Meanwhile, user attention is focused on prominent platforms.

Yu Hu, CEO of Kaito AI, states that 2025 revealed an important pattern: even during a market downturn, sectors like perpetual DEXs and prediction markets experienced explosive growth.

He points to Polymarket as a leading example heading into 2026, supported by on-chain rails and mainstream user adoption.