Insights from InvestOps 2026: Building Scalable Operations

InvestOps 2026: From AI Experimentation to Operational Reality

InvestOps 2026 made one thing clear: the industry is moving beyond discussion and into execution.

Across panels, roundtables, and conversations on the floor, there was a consistent theme. Firms are no longer asking whether AI will transform operations. They are focused on how to deploy it in production, at scale, and with the right controls in place.

As a sponsor of this year’s event, the Alkymi team had the opportunity to engage with asset managers, asset owners, and service providers navigating this shift firsthand.

Private Markets Complexity Is Reaching a Breaking Point

A recurring theme throughout the event was the continued growth of private markets, particularly private credit, and the operational strain that comes with it.

Firms are managing:

• Increasing volumes of unstructured data
• More frequent reporting requirements
• Greater demand for transparency and timeliness
• Leaner operational teams expected to do more with less

Much of the data that drives critical decisions still sits in documents such as capital calls, loan notices, compliance certificates, and financial statements. Extracting and validating this information remains highly manual, time-consuming, and error-prone.

The gap between portfolio complexity and operational infrastructure is widening.

AI Is Moving Into Production, But With Caution

While AI was a central topic across the agenda, the conversation has matured significantly.

Last year, the focus was on experimentation. This year, the focus is on production.

Firms shared that they are:

• Prioritizing high-impact use cases with clear ROI
• Moving away from broad pilots toward targeted deployments
• Placing greater emphasis on governance, auditability, and control
• Evaluating how AI integrates into existing workflows, not just standalone tools

The shift is clear. AI is no longer a side initiative. It is becoming core to operational strategy.

Where We Saw the Most Momentum

From our conversations at the booth and across sessions, a few areas stood out where firms are seeing real traction:

Document-driven workflows
Automating the ingestion and extraction of data from complex financial documents continues to be one of the highest-value use cases.

Data quality and normalization
Firms are recognizing that AI is only as powerful as the data foundation behind it. Structuring and standardizing data is becoming a priority.

Risk monitoring and reporting
There is increasing demand for earlier visibility into portfolio risk, particularly in private credit, where timely insights can be difficult to obtain.

Operational scalability
Teams are looking for ways to scale without adding headcount, especially as portfolios grow and reporting requirements increase.

What We Heard at the Alkymi Booth

The conversations at our booth reinforced these themes.

There was strong interest in:

• Automating complex, document-heavy workflows
• Reducing manual data entry and reconciliation
• Accelerating time-to-data for downstream systems
• Improving visibility into portfolio performance and risk

Private credit, in particular, stood out as an area where firms are actively seeking solutions that can move them from reactive to proactive operations.

Turning AI Into Operational Leverage

The takeaway from InvestOps is that firms are looking for real operational leverage.

• Moving from unstructured to structured data
• Embedding AI directly into core workflows
• Delivering measurable efficiency gains
• Enabling better, faster decision-making

This is exactly where Alkymi is focused.

By transforming unstructured data into clean, actionable intelligence, we help firms automate critical workflows, improve data accuracy, and surface insights that were previously buried in documents.

Looking Ahead

As private markets continue to grow, the firms that will outperform are those that invest in scalable, AI-driven infrastructure today.

The conversations at InvestOps made it clear that the industry is at an inflection point. The question is no longer whether to adopt AI. It is how quickly firms can operationalize it.

See how Alkymi helps turn unstructured data into operational leverage.

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