The most important due diligence question in 2025 isn’t about headcount or flashy portals. It’s this: Does your administrator own its technology — and have a purposeful AI strategy? Because if the answer is no, the costs and risks fall squarely on investors.

The Trouble with Rented Tech

Third-party software comes with predictable baggage:

• Vendor fragility - platforms pivot, prices spike, or systems collapse.
• Rigid upgrades - innovation moves at vendor speed, not market speed.
• Hidden costs - licensing, integrations, and migrations creep into fund expenses. Industry data shows that reliance on third-party software can inflate total cost of ownership (TCO) by 20-30% due to recurring licensing fees and integration overhead, whereas proprietary systems eliminate these costs over time.
• Compliance gaps - external systems increase exposure for sensitive investor data, with third-party platforms often lacking the flexibility to meet evolving regulatory demands.

Before AI, these were weaknesses. In the AI era, they’re untenable.

Why AI Demands Ownership

AI isn’t a bolt-on feature. Instant reconciliations, anomaly detection, and real-time reporting require AI embedded at the system-of-record level. Without tech ownership, administrators can’t:

• Embed AI at the source (not just dashboards masking manual work).
• Maintain clean, direct data pipelines for reliable training and reporting.
• Innovate at investor speed, not vendor speed.
• Guarantee airtight compliance by controlling every layer of the stack.

In short: no tech ownership = no real AI strategy. Studies indicate that proprietary systems with integrated AI can reduce operational costs by 25-40% compared to third-party solutions, which often struggle with fragmented data and limited customization.

What Investors Gain from Ownership

With proprietary platforms, AI-driven automation, and purpose-built infrastructure, investors receive:

• Faster data - Net Asset Value (NAV) calculations and reporting delivered in real time. AI-powered proprietary systems can reduce NAV processing times from 3-4 hours to under 5 minutes per client, a 99% reduction, enabling near-instant investor updates.
• Lower costs - Streamlined audits and reduced downstream fees. For example, AI-driven contract processing in proprietary systems can cut costs by 75-90% compared to manual or third-party methods, while overall operational efficiency improves by 25-30%.
• Fewer delays - No manual tie-outs clogging distributions. Proprietary AI can shorten reconciliation and reporting cycles by up to 80%, compared to third-party systems where data silos add days to delivery.
• Reduced risk - No vendor dependency threatening liquidity or data security. Proprietary systems lower compliance risks by 80-90% through integrated error detection and secure data pipelines.

These aren’t “nice to haves.” They’re the new baseline investors should demand, backed by metrics like 80-90% faster processing and significant cost reductions that enhance returns and trust.

Beyond Offshoring

The old model of “cheap labor + offshoring repetitive tasks” is obsolete. What replaces it is transformational offshoring — AI-led, innovation-driven, and anchored by product R&D. This approach leverages proprietary AI to automate repetitive tasks, reducing manual workload by up to 70% and boosting profitability through scalable, error-free operations. Jurisdiction isn’t the differentiator anymore. Execution and ownership are.