Imagine your investments working around the clock and scanning global markets for the best options – all without having to lift a finger. Sound futuristic? It’s already a reality.
In traditional funding (tradfi), algorithms handle almost 70% of US stock trading. Now Artificial Intelligence (AI) Agents are emerging. These are not only basic bots, but innovative systems that learn, adapt and make real -time decisions. Vaneck predicts that the number of AI agents Skyrocket from 10,000 to over one million by the end of 2025.
What this means to you
AI agents are already working behind the scenes that analyze market trends, balancing portfolios and even control liquidity across decentralized exchange platforms such as Saucerswap and Uniswap. They blur the lines between Tradfi and Decentralized Finance (DEFI), with transverse chain transactions expected to jump 20% in 2025.
Can we really trust AI with our money?
Autonomous funding is not new, but today’s AI agents operate with increased autonomy and sophistication. So can we trust these agents to control billions in digital assets? What protective measures are found when decisions from algorithms come, not humans? Who would be held responsible for market manipulation performed by an agent?
These concerns are valid. As AI agents assume more responsibility, and especially when the convergence between crypto and tradfi accelerates, the concerns of transparency and market manipulation will grow. E.g. Activates some blockchain’s front -headed actions and sandwic attacks that can utilize the blockchain consensus in a process known as maximum extractable value (MEV). These transaction strategies damage justice and marketing time. AI agents at the speed of the machine could AI -agents supercharge these risks.
Enter DLT: Trustlag we need
Trust is key and distributed headbox technology (DLT) offers a solution. DLT provides real -time transparency, immutability and decentralized consensus, ensuring that decisions are traceable and revised. Identity Management Institute reported companies that integrated blockchain identity systems have already cut fraud by 40% and identity theft by 50%. Use of these protection frames on AI-driven funding can counteract manipulation and promote justice. In addition, the use of DLTs with fair order grows quickly, ensuring that transactions are sequenced fairly and unpredictably, relating to MEV concerns and promoting confidence in decentralized systems.
Defai: Where funding is on the way
A blockchain-driven, trust-centric model could unlock a new paradigm, “defai” where autonomous agents can function freely without sacrificing supervision. Open source protocols such as Elizaos, which have blockchain plugins, already enable safe and compatible AI interactions between agents across defi-ecosystems.
Bottom line: Trust defines the future of AI
As AI agents take on more complex roles, verifiable trust becomes non-convertible. Verifiable computer solutions are already being built by companies such as Eqty Lab, Intel and Nvidia to anchor trust on-chain. DLT ensures transparency, accountability and traceability. This is already moving; On-chain agents now operate, offering services ranging from trade execution to predictable analysis. We can trust AI when we have confidence in model input and output.
The question now is not if Institutions will adopt autonomous funding, but whether the framework can develop quickly enough. In order for this revolution to thrive, trust must be embedded in the foundation of the system.
