As AI agents become a bigger topic in crypto, Pranav Ramesh told CoinDesk that Nasdaq has already been using them across several sections of its business and has sharply expanded that use over roughly the past 18 months.

Ramesh, head of options research at Nasdaq and co-founder and CTO of Leadpoet, said the most meaningful shift has been in trust. “AI agents are relatively new, probably being used more and more over the last six months,” he said, arguing that earlier systems hallucinated too often for sensitive enterprise workflows.

He said Nasdaq is using AI agents in areas including market surveillance, compliance, and market microstructure analysis, and pointed to Nasdaq Verafin’s “Agentic AI Workforce,” which Nasdaq says automates “low-value, high-volume compliance processes” in anti-money laundering work.

Ramesh also pointed to Nasdaq’s AI-powered order type. Nasdaq announced in 2023 that its Dynamic M-ELO order type had become the first exchange AI-powered order type approved by the SEC, using an AI model with more than 140 factors to adjust to real-time market conditions.

For Ramesh, that experience informs how he sees crypto. He said crypto trading platforms are likely to move aggressively on AI agents for both internal operations and retail-facing tools, including position analysis, trade suggestions and execution support. “The crypto trading world is actually going to lead the charge on how AI is used within the retail trading environment,” he said.

He did not describe that shift as fully autonomous. Instead, he said the model he sees taking hold is one in which agents handle most of the analysis and workflow while humans retain final approval. In the interview, he said that at Nasdaq, many systems still stop short of full automation, with human review remaining in the last step.

AI and AI Agents will replace a lot of human labor

Ramesh’s views are also unusually blunt on labor. “Yes, it will take a lot of jobs,” he said of AI agents, adding that he believes lower-level software, customer service and analyst roles are already being displaced as systems become faster, cheaper and more reliable. He framed that as an observable trend rather than a prediction.

And he seems to be right as companies, including the most recent being Crypto.com, which laid off 12% of its staff in a push for greater automation and efficiency through AI. Earlier, crypto research firm Messari parted ways with several of its staff and its chief executive as the company transitioned into what the new CEO called an “AI-first company.” Last month, Block, the payments company founded by Jack Dorsey, announced plans to slash 40% of employees, over 4,000 people, citing improved AI models.

The AI trend lead to founding Leadpoet

That thesis also shaped his path into Leadpoet, the startup he co-founded with Gavin Zaentz. According to a February 2026 company fact sheet, the two met at Nasdaq and founded the company after repeatedly encountering the same problem: outbound tools could generate static lists, but identifying real buying intent still required manual research.

Leadpoet describes itself as an AI-powered lead qualification platform that turns web signals and company context into “decision-ready lead recommendations,” emphasizing “precision over volume.” The company says it supports private deployments so customers can score intent and generate outreach on their own data without exposing it to a vendor.

The fact sheet says Leadpoet uses Bittensor, which describes itself as a decentralized, blockchain-powered AI network that allows participants to contribute models and compute while earning rewards. Ramesh said that a decentralized, competitive structure is part of the appeal, because it can improve models faster than a centralized roadmap.

Leadpoet also says it is a member of NVIDIA Inception, NVIDIA’s startup program for AI companies. NVIDIA describes Inception as a free program that offers technical resources, go-to-market support and access to its broader ecosystem.

In the company’s February 2026 fact sheet, Leadpoet says it reached a $1 million annualized run rate in its first quarter after launch and received backing from DSV Fund and Astrid. In that same material, DSV Fund CIO Siam Kidd said Ramesh and Zaentz combine “deep AI engineering expertise with a real understanding of day-to-day sales.”

Ramesh tied the company directly to what he says he saw inside large institutions adopting AI: agents moving from assistants to systems that can handle real operational work. In crypto, he said, that shift is likely to become visible faster than in many other corners of finance.