Hank Boughner is the CEO of Dynamo Software, an end-to-end cloud platform for the alternatives investing ecosystem.
Capital allocation has always been a high-stakes endeavor. But in today’s environment, several market realities are forcing a reckoning for limited partner (LP) investors: outdated processes have become a risk of their own.
A rapidly expanding investment landscape, shifting economic dynamics and soaring talent costs are pushing endowments, pensions and family offices to modernize so they can do more with less.
Some of the modernization forces LPs are exploring include restructuring teams, evolving capital deployment strategies and streamlining operational workflows. But even as early efforts are having an impact, many LPs are seeking faster return on investment (ROI) and higher multiples on invested capital (MOICs). In essence, they’re searching for a force multiplier to accelerate modernization, and AI has the potential to be that force multiplier.
The Hunt For A Force Multiplier Ends With AI
Most LPs feel their tech stack urgently needs a boost. A 2024 private markets survey by my company, Dynamo Software, in partnership with Northfield Information Services, revealed that 57% of LPs planned to increase their technology budgets over the next 12 months, up 8 points from the previous year. The report surveyed more than 100 global LPs and asset allocators between July and August of last year, 80% of whom were located in the U.S. and Canada.
The top two tech priorities cited by LP respondents tell an interesting story. “Creating efficiencies and optimizing workflows” ranked first, followed by “empowering teams to leverage technology.” Apparently, LPs aren’t focused solely on operational improvements. They also see tech as a valuable partner to their people.
This is among the greatest strengths of AI—augmenting human capabilities. Indeed, a core benefit of AI is surfacing insights that account for many more variables than humans ever could.
This is a crucial capability for LPs, who are inundated with high volumes of financial reports and market data. Every deal generates vast amounts of unstructured data from diverse sources and formats, flooding inboxes with can’t-miss information. While Outlook, Excel and PowerPoint have been powerful organizers, they require manual effort that simply can’t keep up with today’s private markets.
Another key dynamic for LPs is the human cost of manual processes. Jeff Bezos famously believes people in high-pressure jobs need to carve out time for critical thinking. Transformative thinking requires protected time, which can be next to impossible when talent is buried in low-value, brain-draining work. AI—and the automation it enables—unlocks the value of those hours.
How AI Is Already Delivering Results
The good news is that AI adoption in private markets is well underway, and its impact is rapidly becoming visible among early adopters.
AI and automation are transforming workflows in meaningful ways. With the assistance of these technologies, LPs can reposition their internal efforts toward value-added activities. Among the results is improved alpha. In a separate survey of 100 LPs and general partner (GP) participants that took place between August and September of last year, 47% of those using AI reported improved portfolio performance.
Beyond a performance optimizer, LPs are also considering AI as an enabler of beating others to a deal. By widening the gap between users and non-users, AI helps LPs capture top-tier deals sooner and deploy capital faster.
Improving Processes Where LPs Need It Most
Crucial to realizing measurable success with AI is deploying it in places where LPs need it most. For now, there are plenty of low-hanging fruit tasks to tackle, including email logging, data gathering and spreadsheet management. Two forms of AI in particular, machine learning (ML) and large language models (LLMs), are well-suited to streamlining tasks without losing nuance and context.
ML is effective at using pattern recognition for managing rule-based tasks. Over decades of iteration, the technology has become superior at probability-driven analysis, using statistical frameworks to do things like capturing key details from an email and adding them to just the right spot in a customer relationship management (CRM) platform.
For their part, LLMs are great at extracting information from unstructured documents, like PDFs, and importing the information into databases. Once data is in a structured format, teams are empowered with expanded functionality and opportunities for analysis.
New LP use cases for AI are developing daily, as private-market players are only getting started with the technology. The private markets survey revealed that 60% of LPs and GPs are just beginning to explore AI.
That said, a growing number of firms are building on early AI deployments. Twenty percent have incorporated AI into some of their standard processes, and 7% are using AI extensively.
Best Practices For Implementing AI In The Investment Process
Integrating AI is not always simple, but the need for the automation it enables is undeniable. For the third year in a row, automating manual processes was named as a top challenge for the LPs who participated in a Dynamo Software survey.
Based on my experience walking alongside LPs enhancing their tech stacks with AI and automation, I’ve observed several best practices:
• Create a data automation/AI team that meets regularly. AI is developing rapidly, and frequent team meetings ensure that technology ROI is being evaluated in real time. Discussion of quick wins (singles and doubles are a great place to start) is critical.
• Use APIs to bridge cross-system gaps. LPs enhance data analysis by adding API-capable platforms, mapping their tech stack and addressing high-friction handoffs. This allows vendors to recommend integrations and configure endpoints aligned with workflows.
• Prioritize security. Automated workflows can pose cybersecurity risks, especially when sensitive data is at play. Partnering with trusted vendors ensures safer data collection, analysis and sharing. Properly managing data deletion, particularly personally identifiable information (PII), is critical.
• Focus on change management. Investment teams often resist change. Applying change management principles, like gaining early buy-in, offering dedicated support and providing proper training, can turn hesitation into enthusiasm and drive successful transformation.
A Call To Adapt And Lead
Success in today’s private markets requires smart, talented people making fast, but informed, investment decisions.
AI and automation are redefining the playbook, accelerating insights with streamlined data and operational workflows. For those ready to adapt and who understand how to do so effectively, the rewards can be significant.
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