As artificial intelligence moves from experimentation to enterprise adoption, GBST has appointed Jai Swaminathan as AI Transformation Lead to accelerate the responsible integration of AI across core products and operational workflows, with a focus on measurable efficiency, scalability, and governance. In this People Spotlight, Jai shares what AI transformation really means in practice, how GBST is embedding intelligent automation into Composer, and why trust and governance remain central to innovation in regulated markets.
From experimentation to value
“At its simplest, AI transformation is about improving how work gets done by augmenting people’s capability,” Jai says. “The key shift is moving away from experimentation for its own sake, toward AI that is embedded directly into workflows and delivers measurable operational value.”
At GBST, that means applying AI where it can demonstrably improve productivity, quality or throughput, both internally, and for clients operating complex, high‑volume back‑office environments.
Why GBST, and why now
Jai was drawn to GBST by its long-standing credibility in wealth technology and the opportunity to apply AI in mission‑critical environments.
“Wealth administration is increasing in scale and complexity. Expectations around speed, resilience and personalisation continue to rise, while governance requirements remain non‑negotiable,” he says. “AI provides a way to improve productivity and consistency while maintaining control, but only if it’s designed for enterprise realities from the outset.”
His remit spans four pillars: embedding AI into products, improving internal operational excellence, establishing strong governance, and building long‑term AI capability across teams.
AI as a co‑pilot, not an autopilot
Internally, GBST is deploying governed AI tools to support engineering and business teams. This includes accelerating development, improving quality assurance and documentation, assisting with code modernisation, and reducing repetitive tasks.
“Our philosophy is ‘copilot, not autopilot,” Jai explains. “AI augments human decision‑making rather than replacing it. We combine automation with human review and clear usage policies to maintain enterprise standards.”
What clients will see in Composer
Externally, AI capabilities are being embedded directly into Composer. Near‑term developments include a Composer AI Knowledge Assistant to help users navigate complex information, and agentic AI services that orchestrate multi‑step back‑office processes.
“Agentic automation is about structuring automation, so multiple specialised AI agents work together under explicit orchestration,” Jai says. “This improves accuracy, repeatability and scalability, while preserving oversight. This is critical in regulated environments.”
Trust as differentiation
For GBST, responsible AI is a competitive advantage. AI deployments are anchored in a Responsible AI framework that includes approved‑tools‑only policies, human‑in‑the‑loop controls, rigorous validation, and security‑by‑design governance gates.
“In regulated markets, trust becomes a differentiator,” Jai says. “We only scale AI use cases that meet defined thresholds for quality, accuracy and safety.”
Looking ahead, Jai sees an opportunity to combine GBST’s deep domain expertise with advanced AI capabilities to redefine operational excellence in wealth administration, responsibly, and at scale.
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