The Agentic Allocator

AuumAI

The "manual era" of capital allocation is in its final chapter. The firms still relying on manual data extraction and analysis aren’t failing overnight, but they are falling behind one week at a time. While most of the industry continues to "white-knuckle" through 200-page documents and legacy databases, and manual Excel extraction, a new breed of Agentic Allocators is quietly rewriting the rules. They aren’t just using AI to summarize emails; they are leveraging AI-augmented workflows that intelligently automate parts of their investment and operational processes that were previously impossible to automate. Hosted by Victoria Sienczewski, CEO and Founder of AuumAI, The Agentic Allocator is the "behind-closed-doors" look at how the world's most sophisticated Limited Partners (LPs), allocators and General Partners (GPs) are actually deploying AI, and the hard-won lessons from those building the systems. This isn't a series about high-level theory or technical gibberish. Each conversation features industry leaders, forward-thinking LPs, GPs and experts who are rewriting the rules of capital allocation through agentic AI. Expect real-world case studies, tactical frameworks you can actually use, and moments that challenge outdated norms. You'll come away with a clearer understanding of the critical questions every allocator must ask - about data privacy, team adoption, integration, and governance - before investing in any AI solution. If you're tired of the "black box" and ready to evolve your investment office for what comes next, you're in the right place.

Épisodes

  1. Data Readiness: The Critical First Step for AI Adoption at Makena Capital Management

    -1 J

    Data Readiness: The Critical First Step for AI Adoption at Makena Capital Management

    Breanna Genecov and Kunal Koppula of Makena Capital Management discuss how the firm is rebuilding its data architecture as a prerequisite to AI integration. They detail the transition from fragmented, Excel-dependent workflows to a unified, cloud-based data stack, and explain why institutional investors who skip this foundation will struggle to extract reliable value from AI. Practical guidance on change management, leadership buy-in, and phased execution makes this essential listening for LPs & allocators at the early stages of their own transformation. Makena Capital Management is nearly two decades into its institutional investing history and one year into a deliberate, firmwide data transformation. In this episode, Breanna Genecov (Portfolio Solutions & OCIO) and Kunal Koppula (Data Engineering) explain the technical shift from managing "Keyman risk" in isolated Excel files to building a unified cloud infrastructure. They discuss the practicalities of porting tools into a modern data stack, the necessity of firm-wide upskilling, and the phased roadmap from structured data consolidation toward AI-enabled unstructured data analysis.  The conversation cuts through AI noise: before any meaningful automation or intelligence layer can be built, your organizational data foundation must be sound. The guests detail how siloed Excel workflows, manual data pulls, and keyman risk have constrained the firm's analytical capacity, and how a centralized data stack is changing that. What You'll Learn: -        Why Makena treats data infrastructure as the non-negotiable prerequisite for AI adoption -        How a $22B OCIO moved from fragmented, Excel-based workflows to a centralized, cloud-native data architecture -        What "one source of truth" means operationally and why inconsistent data across teams leads to incongruous decision-making -        How to manage the cultural and skills gap when moving analysts from Excel to SQL and BI tooling, without making data engineering their day job -        The two-phased roadmap: structured data consolidation first, then unstructured data contextualization via AI -        Why "garbage in, garbage out" is the most important AI principle institutional LPs & alloactors aren't taking seriously enough -        What leadership buy-in actually looks like in practice and why without it, transformation stalls   If you enjoyed this conversation make sure to subscribe, rate, and review it on Apple Podcasts, Spotify, and YouTube.  About the guests: Breanna Genecov leads the Portfolio Solutions and OCIO team at Makena Capital Management. Over more than a decade at the firm, she has held roles across manager research, portfolio strategy, and risk management, with a current focus on the design and implementation of multi-asset class portfolios. Kunal Koppula leads Makena's data engineering team. He previously worked as a trader and quantitative developer before joining Makena, where he now oversees all data-related workflows across the organization and is spearheading the firm's transition to a centralized, scalable data architecture. Episode highlights: [00:02:05] The Catalyst for Change  Breanna traces Makena's data evolution from a 2016 platform overhaul with uneven adoption, to the current firmwide initiative driven by leadership. [00:03:16] What the Data Transformation Entails  Kunal outlines the scope: consolidating all data into a single source, replacing keyman-dependent Excel processes with automated cloud workflows, and building a unified data lineage across every team. [00:05:29] The Manual Tax Described in Detail  The guests describe the true cost of legacy workflows: manual PDF and portal extraction, repeated Excel downloads, and the compounding risk of human error across every reporting cycle. [00:08:44] Breaking Out of Silos Across Investment, Operations, and Client Teams  Kunal explains how his role as “connective tissue” across teams surfaces redundant workflows and enforces a single source of truth. [00:14:53] Phase One vs. Phase Two: Structured and Unstructured Data  Kunal distinguishes between the current phase of structured data consolidation, and the emerging phase: making unstructured data (PDFs, manager notes, etc.) accessible and contextualizable via AI. [00:17:20] Advice for Peers Jumping Straight to AI  Breanna and Kunal make the case against skipping the foundation which they say includes covering garbage-in/garbage-out risk, the need for human validation, the importance of the right project lead, and why patience is a strategic requirement. Episode resources: -        Breanna Genecov on LinkedIn -        Kunal Koppula on LinkedIn -        Makena Capital Management Website -        Victoria Sienczewski on LinkedIn -        AuumAI Website

    21 min
  2. The Blueprint for AI-Ready Investment Offices: Lessons from HICO Investment Group

    24 MARS

    The Blueprint for AI-Ready Investment Offices: Lessons from HICO Investment Group

    Chris Hartnoll, CEO and Managing Director of HICO Investment Group, discusses how the firm is approaching AI adoption across its multi-asset class endowment style portfolio and direct investment platform. He explains why preparation, security, and operational groundwork must come before any meaningful AI deployment, and shares early signs of productivity gains and improved risk identification. Practical guidance on experimentation, leadership mindset, and the urgency of starting now makes this essential listening for LPs and allocators considering their own AI journey. Chris Hartnoll operates at the intersection of institutional investing and industrial technology. At HICO Investment Group, he has built a global multi-billion dollar platform that pairs a sophisticated multi-asset class endowment style portfolio with direct investment and incubation of new ventures in sectors like maritime logistics and energy transition. In this episode, Chris unpacks what it means to prepare an investment office for AI: the security considerations, the folder structure decisions, the legal questions around data protection, and the cultural shift required to move from manual processes to AI-assisted workflows. The conversation is grounded in Chris’s background navigating high-stakes environments, from aerospace engineering at Rolls-Royce to Morgan Stanley M&A Advisory to the Royal Marines. He draws a direct line between the discipline of preparation in those fields and the approach HICO has taken to AI adoption: do the unglamorous operational work first, then experiment in discrete, measurable process steps. He argues that the allocator community has been slow to look inward and apply AI to its own processes, despite readily advising GPs and portfolio companies to do the same. What You’ll Learn: Why preparation and operational groundwork are the non-negotiable prerequisites for AI adoption in investment offices How HICO balances an endowment style portfolio with a company builder approach to direct investments and incubation, and what that means for information flow internally Why the allocator community has been slow to adopt AI despite advising portfolio companies and managers adopt AI How to start AI experimentation in discrete, measurable process steps Where early productivity gains are showing up: LPA summarization, manager interviews, and AI-assisted risk identification Why AI-enabled teams will respond faster and make better decisions during periods of rapid market change Why starting now is critical, even if full end-to-end AI integration is years away, and the cost of waiting If you enjoyed this conversation make sure to subscribe, rate, and review it on Apple Podcasts, Spotify, and YouTube.  About the guest: Chris Hartnoll is the CEO and Managing Director of HICO Investment Group, a global investment firm focused on maritime, logistics, and energy transition. Chris built and oversees a multi-billion dollar platform that includes a multi-asset class endowment style portfolio paired with direct investment and incubation of new ventures. Before founding HICO, Chris held roles in aerospace engineering at Rolls-Royce, M&A advisory at Morgan Stanley, and served as a Royal Marine. He holds an MBA from Harvard Business School.Episode highlights: [00:01:46] Background and Approach to Risk Chris traces the thread connecting his Royal Marines experience, aerospace engineering at Rolls-Royce, and Morgan Stanley M&A to how he thinks about preparation and risk management in investing. [00:03:31] Balancing Endowment Style Asset Allocation with Direct Investment Chris explains how HICO balances its capital allocation process and its direct deal-making and incubation activities, and why keeping the processes separate while sharing information has been key. [00:05:17] Why the Allocator Community Has Been Slow to Adopt AI Chris reflects on why investment professionals are quick to advise others on improvement but slow to apply the same lens to their own processes, and why CIOs have been reluctant to disrupt what they’ve built. [00:07:27] The Operational Groundwork for AI Adoption Chris details the unglamorous but critical preparatory work: security guardrails, data privacy, folder structure, legal review of GP document protections, and building the right digital infrastructure. [00:08:55] Early Signs of Value: Productivity and Risk Identification Chris shares where AI is already delivering: summarizing LPA documents, capturing manager interview data, and surfacing new ways of viewing risk. [00:12:57] The Future of the AI-Enabled Investment Office Chris outlines his vision for human-AI collaboration in investing, why private markets will continue to have a human-in-the-loop, and how AI-enabled teams will gain a decisive speed advantage during periods of market volatility. [00:15:39] Advice for Peers on the Fence Chris delivers his core message: be prepared first, then start experimenting immediately, because the learning curve is long and the cost of waiting is compounding. Episode resources: Chris Hartnoll on LinkedInHICO Investment Group WebsiteVictoria Sienczewski on LinkedInAuumAI Website

    18 min

Notes et avis

4,9
sur 5
7 notes

À propos

The "manual era" of capital allocation is in its final chapter. The firms still relying on manual data extraction and analysis aren’t failing overnight, but they are falling behind one week at a time. While most of the industry continues to "white-knuckle" through 200-page documents and legacy databases, and manual Excel extraction, a new breed of Agentic Allocators is quietly rewriting the rules. They aren’t just using AI to summarize emails; they are leveraging AI-augmented workflows that intelligently automate parts of their investment and operational processes that were previously impossible to automate. Hosted by Victoria Sienczewski, CEO and Founder of AuumAI, The Agentic Allocator is the "behind-closed-doors" look at how the world's most sophisticated Limited Partners (LPs), allocators and General Partners (GPs) are actually deploying AI, and the hard-won lessons from those building the systems. This isn't a series about high-level theory or technical gibberish. Each conversation features industry leaders, forward-thinking LPs, GPs and experts who are rewriting the rules of capital allocation through agentic AI. Expect real-world case studies, tactical frameworks you can actually use, and moments that challenge outdated norms. You'll come away with a clearer understanding of the critical questions every allocator must ask - about data privacy, team adoption, integration, and governance - before investing in any AI solution. If you're tired of the "black box" and ready to evolve your investment office for what comes next, you're in the right place.

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