TSAM London returned to the Business Design Centre on April 13-14, bringing together senior buy-side leaders for two days of conversation on the forces reshaping asset management.
If there was a single theme running throughout the event, it was this: the ambition is there, the pressure is real, and execution is where firms are getting stuck.
That shift in tone matters. A few years ago, these conversations were about whether to modernise. Now they are about how, and why it keeps being harder than it should be.
Across investment operations, data, AI, and private markets, the same tension kept surfacing in different forms. Firms know their infrastructure is holding them back. They know their data is fragmented, their workflows involve too many handoffs, and their teams are spending time on reconciliation and cleanup that should be going elsewhere. They have heard the case for change. Many have started making it.
And yet the gap between intent and outcome remains wide. The reasons are familiar to anyone running operations at scale: legacy systems that were sensible decisions at the time but were never designed to work together; transformation programmes that stall under the weight of dependencies; and the very real risk of breaking something that, for all its inefficiency, is currently holding the business together.
This is the reality of operating in complex, multi-system environments where the cost of getting it wrong is high and the pressure to keep things running never lets up.
The challenge isn’t whether to modernise. The focus is on how to modernise operating models, move away from legacy infrastructure, and introduce new tools, while keeping day-to-day operations stable and client service uninterrupted.
Sessions focused on sequencing transformation programmes realistically, managing vendor and internal dependencies, and finding a pace of change that does not destabilise day-to-day operations. For many firms, the honest answer is that the roadmap exists but the path through it does not feel clear.
This was one of the liveliest discussions across both days and for good reason. Do firms continue to build a connected ecosystem of specialist tools, or do they move towards a more integrated front-to-back platform model?
The right approach depends on the firm’s size, product mix, internal complexity, and legacy environment. What has changed is that firms now understand the trade-offs much more clearly: data ownership, reconciliation effort, exception handling, flexibility, speed, and long-term scalability. What they are looking for is a practical path forward.
Lotte Tonsberg, Clearwater’s Managing Director for EMEA Hedge Fund and Commercial Asset Management, joined the panel and brought a sharp commercial perspective to the debate, converging on one point. Whatever architecture a firm chooses, it needs a central spine, a single trusted source of data that ensures the front office receives accurate and timely information to make investment decisions.
Most firms cannot start from scratch. The buy side comprises firms of different sizes and varying degrees of legacy complexity, which means a big bang transformation is rarely realistic. What matters is having a clear strategy and partnering with a vendor that can support much of the investment lifecycle on a single dataset — which is exactly what Enfusion is built to do. In a world where AI and technology are moving faster than ever, a trusted core dataset and open architecture are foundational.
As Lotte put it: “Say no to upgrades. Modernise your architecture sooner rather than later, or you will fall behind on efficiency, scalability, and profitability.”
Data quality and governance ran through almost every stream, not as a new topic, but as an unresolved one.
Firms are still dealing with fragmented data estates, positions that drift out of sync, and reporting built on manual workarounds that nobody has had time to replace. Fixing these issues requires the kind of sustained, unglamorous infrastructure work that is hardest to prioritise when operational pressures are constant.
Lineage, governance, and real-time accuracy are not exciting investments. But AI, reporting, compliance, and decision-making all depend on them. Firms that have not addressed the data foundation are carrying more risk than they realise.
AI was a prominent theme, but in a noticeably more grounded way than in previous years.
The conversation has moved on from potential to prerequisites. Firms are asking the right questions, including: where can AI genuinely reduce manual work, improve decision-making, and surface what matters without someone having to go looking for it? And what needs to be true about the data foundation before any of that is possible?
There was also growing interest in agentic AI and workflow-based automation, alongside more serious discussion around control, data readiness, and ownership — areas where Beacon is purpose-built to help.
Agentic AI and workflow automation require something most firms are still building: a data foundation they can trust.
Rising allocations to private credit, secondaries, and alternatives are not just adding complexity. They are exposing the limits of infrastructure that was never built to handle them.
Valuation complexity, capital scheduling, investor reporting expectations, and the challenge of maintaining control while scaling AUM without scaling headcount all came through strongly. This was especially relevant for firms operating across both public and private markets, where the operational model must support very different workflows without losing consistency. For many, the infrastructure was never designed for this — and the gap is widening faster than it is being closed.
The conversations at TSAM were not unique to the firms who attended. The questions worth taking back to your own team include:
Data trust, operational modernisation, AI readiness, and private markets complexity are not separate problems. They are the same problem, showing up in different places. The firms that recognize that and act on it are the ones building genuine operational advantage.
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