There’s no shortage of hype in the headlines, but for Amjad the real value shows up where AI genuinely changes how people work, how decisions get made and how long-standing industry problems can finally be tackled in new ways.
That’s the thread running through Toby Babb’s conversation with Amjad Zoghbi, Head of AI at TRG Screen, on Harrington Starr's FinTech FOCUS TV podcast. (Want to jump to the video now? See below!) It’s a discussion grounded in experience and clear thinking, and it offers a practical view of where market data technology is heading next.
Amjad didn’t arrive in the AI seat by accident. His background building Xpansion Financial Technology Services – and the technical vision behind Xmon, one of the first cloud-native platforms for monitoring reference data usage and costs – set the pattern: taking complex, entrenched problems in market data and rethinking how technology can solve them at scale.
TRG Screen partnered with Xpansion to bring Xmon to market, and the success of that collaboration made acquisition the natural next step. Both teams shared the same mindset: start with the real operational pain and build technology that makes expert work easier, faster and more accurate.
For decades, TRG Screen has operated in one of the toughest corners of the financial stack: helping firms understand and control market data spend, usage and compliance. It’s a thorny, high-stakes domain where real innovation means solving the structural complexity that makes market data hard to see, hard to manage and even harder to govern.
With that foundation, AI is a continuation of a long arc of using technology to make market data more visible, manageable and predictable.
Amjad starts with how TRG Screen’s AI journey began internally. Before any client facing features were released, Amjad’s team built an AI assistant to solve a scaling problem inside the business: How do you make deep product knowledge instantly accessible to a fast-growing global sales team without overwhelming the subject matter experts?
Rolled out through Slack, the new AI Assistant quickly became a core part of how teams prepare for client meetings, understand new releases and answer complex product questions in real time. It lifted pressure from specialists and gave everyone faster access to reliable information.
That early experience proved two things:
It also reinforced a core belief that AI works best when it amplifies human expertise, not replaces it.
One of Amjad’s key points is that automation and AI are not the same thing. Traditional automation is rigid and linear, a fixed sequence of steps. Market data operations don’t work like that. They rely on judgment, interpretation, exceptions and an understanding of licensing rules that often sit in the grey areas.
This is where agentic workflows enter the picture. Rather than simply routing tasks from step A to B, AI agents can navigate ambiguity, interpret context and bring the logic of experienced market data practitioners into the system itself – while still keeping humans in control of final decisions.
It’s not about taking people out of the loop. It’s about taking unnecessary friction out of their day so they can focus on the decisions and the work that actually matter.
Without giving the entire roadmap away, Amjad outlines three areas where AI is already reshaping TRG Screen’s products:
1. Intelligent data ingestion that can interpret documents and contracts more accurately.
2. Adaptive workflows driven by agentic logic rather than rigid rules.
3. Insight generation that highlights savings, risks and patterns hidden in the data.
Some of this is already in production; more is coming quickly. As Amjad notes, AI adoption is likely to follow a similar trajectory to cloud but faster, because the value becomes obvious the moment people start using it.
The interview goes deeper into the practicalities of adoption, the role of human oversight, how TRG Screen’s AI Innovation Lab will accelerate future development and why the organization believes AI will always be strategy-led.
If you want to understand how AI will shape the next phase of market data management – in the hands of teams already delivering it – it’s well worth watching.