areas of an asset management firm. Those areas include marketing, human resources, sales, compliance, corporate social responsibility (CSR), and many others. Second, it incorrectly assumes that people with PhDs in mathematics, computer science, or AI are the only ones interested in AI. This assumption is often based on the historical roots of machine learning, when it was viewed as the exclusive toolkit of quantitative investment in legacy firms. That exclusivity is no longer true. Third, this closed, cult-style adherence is extremely dangerous as it assumes that a firm's business model is static. It ignores the fact that fintech start-ups and tech firms are entering the legacy space and architecting their business models with AI—and that responding to such a powerful competitive threat requires a far more strategic approach to AI in finance than the one that comes with quantitative investment only. Fourth, to build a modern firm, you must approach AI as a strategic process that is embedded in the strategic DNA of the firm and as an industrial-scale machine learning operation. To do that, you must have an enterprise-level approach and not just a quant-specific viewpoint.
However, trivializing AI as some fictional, motivational, hyped-up, or management-consulting buzz phenomenon is equally dangerous. That approach can win some near-term contracts but generally leads to disappointment in the long run. Projects fail or fail to deliver the promised value. When Robotic Process Automation (RPA) is sold as AI and AI is sold as a point solution while ignoring the data, it hurts all parties.
The reality is that the asset and investment management world is at the cusp of a major transformation. This transformation is not an ordinary evolution in the normal course of business. It is a revolutionary change that is creating never-seen-before opportunities and threats. It has unleashed an enormous force that is demanding new ways to respond to the challenge.
Thus, AI must not be approached as a toolkit, merely a technology, or a hyped-up technological change. It is pervasive and transformative. It is revolutionary and emergent. Most importantly, this change belongs to everyone and not just a narrow segment of your workforce. To begin with, the C-suites and boards need to understand this change. They are at the helm of their business, and the introduction of AI has altered the strategic maps. They need to rethink how to navigate through these troubled waters. Then, heads of departments of all functional areas—marketing, sales, regulatory and compliance, human resources, procurement, and others—must develop AI-centric transformation plans. Their plans should be consistent with the strategy of the firm. In addition to the support organizations, the investment operation should be approached strategically. The process, incentive systems, organizational setup, and theoretical foundations on how investment organizations are set up should be questioned. The powerful rise of AI and its effect on asset management compel us to rethink our business models.
This book, therefore, is a guide for every person who is in any manner affiliated with the finance industry. From asset managers to investment managers, from marketing heads to IT managers, from strategy professionals to executive teams. And yes, most certainly, quantitative investors can also benefit from this book. This book is fundamentally about transforming your investment management firm or business unit to make it a modern, high-performance, and AI-centric enterprise. It shows you how to build a modern asset management firm and function. It is your guide to move your legacy firm to a modern firm. Use the book as a roadmap to build your firm or to transform your legacy operation to a modern era company.
My goal, as your guide, is to help you think as a strategist for the AI era. Even though I will provide a delicate and intuitive introduction to various models, algorithms, and methods, if you expect to become a data science expert or learn Python from this book, it is not for you. This book is for the leaders of the investment management world who want to build their companies around AI and create a powerful future for their firms.
You cannot write a book on AI for business and keep the business as a constant. AI is not about automating existing business processes. It is about reinventing the business. The reinvention-related change happens on both ends. AI changes business, and business demands change AI responses—so much so that at some point AI becomes business and business becomes AI. In other words, your business is nothing more than your AI strategy, and your AI strategy is your business. Any strategies orchestrated other than the AI-centric planning are futile. Any plans developed outside the AI universe are doomed to fail. Any visions of a future that are not based on AI are useless. The power of an AI-centric transformation is immense.
AI must not be viewed as just another technology. Unlike regular IT solutions, AI is not something that can be simply pushed down to the IT departments. When it comes to business, AI is the new way of life. It is a complete transition to a new way of operating.
Despite the immense power of AI, we tend to be so narrowly focused that we continue to ignore the big picture. Think about placing a camera lens inches away from a rock and taking a picture. Chances are that you will find little information of interest (unless you are a geologist). Now move the camera away from the rock and let the picture of the entire scenery—mountains, trees, lake, clouds, and sky—fill your lens. Suddenly you have something of interest that you can enjoy. When it comes to AI, the situation is completely analogous—we are looking too narrowly and missing out on the big picture. That approach is counterproductive because it can never help create competitive advantage for a firm.
This change in business structure, configuration, and models is also evident in asset management. It is becoming harder to identify what exactly is an asset management firm these days. A strange convergence is taking place, where firms are evolving from a structural perspective. With various business models and structures, from passive to active, retail to institutional, human advisor to robo-advisor, the entire sector is in a self-rediscovery mode. Rest assured, AI will touch and transform everything in investment management. The process has begun. Welcome to the new era in investment management.
Acknowledgments
I WANT TO THANK MY FAMILY for providing immense support during this project. I also want to thank all my colleagues at the American Institute of Artificial Intelligence.
Additionally, I want to thank Anam Khan of TSAM (the Summit of Asset Management). TSAM meetings and conferences in London, New York, and Boston provided tremendous learning and networking opportunities to help understand the practical problems faced by the industry.
I would like to thank Russ Malz, Gary Smith, and Lisa Schoch—people who truly understand the AI solution needs of the industry. Thanks to Dr. Paul Ellwood of the University of Liverpool.
Many thanks to the Wiley publishing team, including Susan Cerra and Sheck Cho. I work with many publishers, and I found Wiley's team extremely professional and helpful.
Finally, thanks to all those whose work I have cited in the book. It is because of their work that we are today shaping a new revolution in investment management.
Chapter 1 AI in Investment Management
FIRMS WITH A HIGHER-LEVEL AWARENESS are not faring any better than those that lack imagination or alertness. When it comes to AI, firms seem to be split between denial and dysfunction. Those in denial view AI as a passing fad, an overly hyped phenomenon, a lustful yearning of large firms, a deviant path to shatter human relationships, and a phase whose efficacy parallels that of other digital technologies. Those in dysfunction are the fearless warriors who want to embrace anything that sounds like AI. They want AI at any cost—even if it means implementing AI without understanding what AI is, knowing how to plan and deploy AI, where and why to implement it, or how to maximize value from AI.
The ones in denial need no plan. The ones in dysfunction have none. Here are some examples of the above mindsets:
If you talk to investment management firms about AI as I do, you may hear something along these
