Where AI Fits Into an Emerging Manager's Operation - and Where it Doesn't

A Practical Roadmap for Emerging Managers

For the last three months of this column, I’ve argued that “management” is not a feeling. It’s a discipline - expressed through legal rigor, security governance, and documentation that makes decisions visible and durable. This month let’s apply that framework to the hottest tool everyone is talking about: Artificial Intelligence, or “AI”. 

Consider the following scenario that frequently plays out in emerging manager firms: a CEO discusses ChatGPT, Claude, or another AI tool with a colleague, decides to try it, finds it remarkable, and tells their entire organization to start using it. Marketing. Development. Investor relations. Research. Operations. Accounting. No guidelines. No parameters. No conversation about what should and shouldn’t be entered into a public AI platform.  

Before long, employees or even independent contractors may be entering client information, proprietary work product, financial data, employee details, or sensitive business issues into tools the firm has not formally reviewed. Different departments may be using AI in different ways, with no common understanding of what’s permitted, what’s prohibited, and what must still be reviewed by a human being. 

This is the central problem with how AI is being adopted at the operational level in many firms today. The conversation is almost entirely about capability - what AI can do - and almost never about readiness: whether the organization using it is structured, documented, and disciplined enough to use it well. 

In this way, AI can create both opportunity and risk for emerging managers. 

AI can be genuinely useful. It can draft, summarize, organize, compare, help you ask better questions, and help you better understand complex answers. But it can only become a meaningful productivity tool when it’s used with structure, judgment, confidentiality awareness, and human oversight. The firms that benefit most from AI will not be the ones that use it most casually. 

Paul Das, Founder and CEO of ProFundCom - a platform that helps emerging managers turn investor engagement into capital using institutional-grade marketing, data, and distribution tools - has thought carefully about where AI belongs and where it doesn’t for his firm. “The minute you have a chatbot answer the phones,” he says, “it conveys the message that the caller isn’t worth a real human conversation.” His firm uses AI alongside their product to make data more meaningful, analyzing years of engagement data to help managers improve their outreach and get in front of prospective investors more effectively. Paul’s use of AI includes working with structured data, within defined parameters, in a controlled environment behind a firewall, rather than through casual, open-ended use of public AI tools on the Internet. 

Marc Zuccaro, Managing Principal and Portfolio Manager of Golden Eagle Strategies, uses AI in a similarly disciplined way - accelerating operational tasks like Excel modeling, formula development, database building, and data validation. Work that once took days or weeks now takes minutes. But AI is not integrated into his trading system at all. He doesn’t give it access to PII (personally identifiable information) or proprietary data. The productivity gain is real. The boundaries are firm. 

What both Paul and Marc share is not just a set of rules about what AI can and can’t touch. It’s a management posture. They know their businesses well enough to know where AI fits and where it doesn’t. That clarity doesn’t come from the AI. It comes from the organizational discipline that existed long before the AI arrived. 

That’s a posture worth following. Here’s how it maps across the eight key areas of your emerging manager business. 

Operations. AI can be very useful in operations, particularly for firms still building internal infrastructure. It can help draft SOPs (standard operating procedures), checklists, meeting summaries, project plans, workflow maps, and implementation timelines. 

What AI shouldn’t do is invent procedures that don’t reflect how the firm actually operates or replace management’s responsibility to define who owns what. 

Legal. Many small firms delay legal conversations because they’re not sure how to frame the issue or what information counsel will need. AI can help them prepare more thoughtfully. It can also help organize facts, prepare questions for counsel, summarize issues, and translate legalese into plain language. 

While AI can help a manager prepare, it should never be used as legal advice. It shouldn’t be used to draft binding agreements without attorney review, to analyze sensitive legal exposure without understanding the confidentiality risks, or to ever replace the legal conversation itself. 

The danger isn’t merely that AI may be wrong. The danger is that it may yield results that sound confident while being incomplete, outdated, or inapplicable to the specific facts related to your situation. 

Accounting. In accounting and finance administration, AI can help draft invoice follow-ups, summarize budget questions, organize expense categories, and build internal checklists. That can be valuable. 

But AI should never make tax decisions, determine accounting treatment, or replace the judgment of a qualified accountant. While AI can help prepare the information, it should never sign off on the numbers. 

Human Resources. AI can be helpful in human resources because so much HR work involves language, structure, consistency, and documentation. It can help draft job descriptions, onboarding checklists, interview questions, policy outlines, and performance documentation templates. 

But HR is also an area where careless AI use can create serious risk. It should never be used to make hiring decisions, evaluate protected characteristics, generate disciplinary conclusions, or produce policies without legal and management review. 

Security. AI can help create employee reminders, incident-response checklists, vendor questionnaires, and plain-English explanations of security practices that employees and managers are more likely to understand. That’s useful because security is not merely a technical issue. It’s also a management issue. Employees need to understand what to do, what not to do, and when to escalate. 

But AI also creates its own security concerns. It should never be given passwords, sensitive credentials, confidential client information, incident details, or unrestricted access to systems or data. 

Technology. AI can assist with technology planning by helping compare software options, drafting implementation plans, documenting system requirements, and translating technical issues into business language. For emerging managers, this can be useful because technology decisions often sit between technical vendors and business owners. AI can help management ask better questions, organize requirements, and think through implementation steps. 

But AI should never be given the ability to select platforms, approve integrations, manage access rights, or decide what data moves where without technical and business oversight. Technology decisions have consequences - affecting client data, investor communications, cybersecurity, accounting records, compliance obligations, and operational continuity. 

Marketing and Sales. Marketing and sales may be one of the most obvious areas for AI use. It can help draft articles, repurpose content, create outreach language, prepare FAQs, summarize client personas, and brainstorm campaign ideas. 

Paul notes that it also helps managers understand which types of communication get the best results - turning years of engagement data into actionable guidance. 

But marketing is also an area where AI can create reputational risk. What it shouldn’t do is make unsupported claims, invent credentials, overpromise results, or dilute the firm’s voice. Emerging managers should be especially careful in any communication involving investment strategy, track record, performance discussion, investor suitability, or regulatory implications. AI should never be allowed or able to misrepresent. 

Compliance. AI can help build checklists, summarize requirements, organize audit materials, and identify gaps for review. 

But compliance isn’t a casual AI exercise. It should never be treated as the authority on regulatory obligations, filing requirements, deadlines, or compliance conclusions. Compliance requires ownership; someone who must know what rules apply, what records must be maintained, what representations are being made, and what evidence exists to show that your firm is meeting its obligations. While AI can support compliance administration, it should never become your compliance officer. 

The Management Question 

Both Paul and Marc use AI the same way: to efficiently streamline internal processes, not to replace people, judgment, or for decision-making across their firms. 

When asked for advice for emerging managers, Marc was direct: “You need to properly educate yourself on AI. You need to know your own business intimately — all areas of it — and you need to know the limitations of AI.” 

Paul framed it as a set of strategic questions: “Ask yourself: What does AI do for your product? Where is it really useful? You have to understand how efficient you want to be, and then, what will you do with the extra time it affords you?” 

That last question matters more than it might seem. Efficiency isn’t the goal. It’s a means. The extra time AI creates should go toward the work that requires human judgment; the decisions, the relationships, the reviews, the oversight that no tool can replace. 

AI never eliminates the need for documentation, security, legal review, accounting judgment, HR discipline, technology oversight, marketing accuracy, or compliance responsibility. In fact, it increases the need for all of them. And it’s a topic investors are asking about during the due diligence process. 

Every one of the previous articles in this series pointed toward the same conclusion, and AI makes it more urgent, not less. The firms that use it well will not be the ones that adopt it fastest. They will be the ones that were already running with enough structure to know what they were doing — and why they were doing it. 

That structure is called management. And no tool can build it for you. 

Until May! 

Carol R. Kaufman, Founder/CEO of Alternatives TLC, LLC has been consulting to emerging and seasoned alternatives managers and various types of industry businesses since 2005. She performs operational and organizational due diligence, using her Emerging Manager Roadmap, helping firms find the resources they need to successfully scale. Most recently, she performs I-9 training and internal audits, Her first product, InvesTier^®, was acquired by SunGard in 2002. An entrepreneur for over 40 years, Ms. Kaufman’s specialties include public speaking, training, and software/ service-based solutions to organizational problems. She resides in Hawthorne, NJ.