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Callan CEO Greg Allen took the unusual step of publicly explaining how his firm uses artificial intelligence, telling clients in a recent blog that the technology will make employees more productive rather than reduce headcount. Allen wrote that "It is extraordinarily rare for us to write about ourselves." He wanted to discuss Callan's AI strategy to educate clients on how they use these tools and the benefits for their work. Since September 2017, Allen, CEO of the investment consulting firm, outlined a series of "wills" and "will nots" based on an internal survey. This approach shows they are learning from actual usage instead of imposing a firm-wide system before practical use cases are clear. Despite mixed views among pension fund executives on AI's potential impact on employment, Allen emphasized that AI at Callan is not intended to reduce headcount, but to enhance employee productivity for clients. He clarified that AI will not replace investment, legal, or client judgment, nor will it eliminate the need for fact verification. Instead, AI supports subject-matter expertise, allowing it to operate more efficiently. For Callan employees, AI's most significant current use is to reduce repetitive tasks such as processing quarterly investor letters, manager commentary, meeting notes, legal summaries, research papers, and operating instructions. Allen noted that much of Callan’s work involves an overload of text, sources, or repetition, and AI is proving effective in condensing this information into something concise, organized, and easily digestible for clients. Employees describe AI as a valuable assistant, intern, writing partner, coding partner, or a second set of eyes. Addressing concerns about AI creating portfolio risk, Allen stressed that Callan’s use of AI is to support professional work, not to substitute for professional judgment. Callan’s AI applications are still evolving for its 204 employees and over 400 clients, for whom the company oversees more than $4 trillion in assets under administration. Allen concluded that as they continue to refine AI integration and encourage broader experimentation within the firm, and learn from current users, their work for clients is expected to become better, more efficient, and more focused on client inquiries.
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