The World Economic Forum published its AI Playbook for Financial Services earlier this month, noting that the artificial intelligence landscape of 2026 would have seemed implausible just a few years ago, with models that reason across complex problems and agents that autonomously execute multi-step workflows.

“Driven by rapid advances in generative and agentic AI, the pace of change shows no sign of slowing,” the WEF report stated. “AI represents a structural disruption, and its impact on financial services goes far beyond efficiency gains. It is reshaping how work is organized, how decisions are made, how value is created and how institutions compete and collaborate.”

As an SaaS platform provider to the global capital markets industry, Trading Technologies has a vested interest in staying on the forefront of AI. Traders Magazine caught up with Peter Weiler, EVP, Managing Director of Data and Analytics at TT, to learn more about the company’s AI journey, current initiatives, and vision for the future.  

What has been Trading Technologies’ AI journey to date? 

Our AI journey began in 2018 when we brought our trade surveillance solution to market. We pioneered the use of AI with AI-driven machine learning surveillance models that still continue to be a differentiator for us today.

More recently, we’ve deployed AI throughout the firm to accelerate how we’re building software and bringing it to market.

Specific to the Data & Analytics business line, we are in the midst of a proof of concept where we’ve developed an AI agent. If you think about the combination of data, analytics and TCA, it’s a perfect match for AI, because it involves querying data and coming up with patterns and surfacing different historical information. We display data, and with AI we’re able to do that much quicker. 

We’re working on the AI agent as a supplement to the product. We have a PoC client and we expect to extend that PoC to have the agent in production in Q4.

Our AI model will roll out across four progressive developmental stages. The initial phase will serve as a core product FAQ resource, while subsequent updates will expand into handling advanced user inquiries, executing reporting functions and recommending specific trading algorithms.  

What’s the end result in terms of how TT will leverage AI to help clients?

This AI model is going to add significant value across the full spectrum of the trade life cycle, spanning pre-trade, real time, and post trade. 

Pre-trade, you can think about what strategy and tactics to use before you trade and the model can select which algorithms should be used. And this is a little more advanced and down the road, but it can help at trade and during trade, in terms of suggesting changes or adjustments in real time. For post trade, you’ll be able to surface reports for internal or external stakeholders, or for compliance and governance use cases, much quicker. 

And just from an administrative standpoint, there’s a lot of things that the product will be able to do to help people understand the value that a broker or counterparty is providing to a particular buy side client. For example, you can look at who’s providing a better quote under what circumstances, who’s winning, and who’s coming in second and third place – so you can use your wallet based on more quantitative analysis. 

AI is a game changer across the whole trade life cycle, and we’re continuing to be proactive in discussions with clients and in previewing our AI agent.

Publicly traded software firms have declined this year on the perception of an existential threat from AI. What is your take on this?

I think for single-point software companies that just solve for one problem and are more horizontal than vertical, it’s going to be challenging. What wins the day is having a platform, having an ecosystem around the platform, and bringing agents in to do various tasks. 

There has been a reset and valuation multiples are down across the board, but the capital markets business is relatively strong because it’s more regulated, and that enables a wider moat.

How do you see the path forward for AI?

Obviously AI is going to be a strong net positive for productivity. I think it will make legacy platforms stronger, and it will be ubiquitous in the marketplace – everyone will have an agent.

On a human level, it’s important for all of us to be able to use the tool to our advantage. At TT we have enabled AI to permeate the organization – we want everybody to lean into it and ask the right questions because they have the domain knowledge and can apply it not only to our products but also to our own product development workflows. AI is a revolutionary technology and I expect its growth will be exponential.