Artificial Intelligence for Asset Management and Investment. Al Naqvi

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      In the Planning School the combination of planning tools (for example, SWOT) and mission statements of executives and leaders of companies are used to create short-, medium-, and long-term plans for companies. From that perspective, the intelligence-centric planning implies that tools and methods that decipher strategy are applied; however, their implementation will be quite different than in human-oriented strategy development. For example, the strengths, weaknesses, opportunities, and threats need to be analyzed for automated intelligent systems.

      In the Positioning School, unlike the Design and Planning schools, which placed no limits on the number of strategies that a firm can have, Mintzberg et al. explain “only a few key strategies—as positions in the economic marketplace—are desirable in any given industry: ones that can be defended against existing and future competitors.” The emphasis on competitive dynamics clarifies that in the era of intelligent automation, the competitive dynamics are defined based on intelligence in products, production platforms, and interlinked network of systems.

      The Entrepreneurial School is based on vision and vision setting and is usually centered on one leader. In this school the entrepreneur develops a vision, a mental model, and applies skills to create value. AI can assess the quality of vision, execution, entrepreneurial skills, and value creation opportunities.

The Cognitive School is based on analyzing the human mind, as, according to this school, human thinking and experience drive strategies. Understanding human psychology helps understand how strategies are shaped. The reality is shaped by human thinking. In the context of an AI-centric strategy, it implies machines can help decipher the human thinking process and identify our biases. Machines can help understand how we think and what we are thinking. Also, if our intelligent artifacts frame and architect our understanding of the world, and ourselves, the difference in their intelligence level, or even perspective, can make a difference in how we understand strategies and ourselves.

      The Learning School is based on the emergence of strategies as people learn about situations and their firm's capabilities. Learning helps morph behaviors as we recognize what works. From a learning school perspective, the introduction of machine intelligence implies that the emergence happens not only by human agents but also from the interaction of machines with other machines and humans. Such a complex system is based on interactions between agents that are part of the system, as well as agent interaction with other systems outside the system.

      In the Power School strategies come from negotiating and power games that are played in companies. From an intelligence angle, machines can decipher power patterns and even help understand the strategy development from a power struggle perspective.

      The Cultural School emphasizes the strategy formulation process as a cultural process. In the era of intelligent machines, humans can not only study culture with greater accuracy but also develop a deeper understanding of the social phenomena underlying their strategies. Culture is “essentially composed of interpretations of a world and the activities and artifacts that reflect these. Beyond cognition these interpretations are shared collectively, in a social process.”

      In the Environment School strategy is shaped as a response to the environment. A responsive strategy to the environment implies that the entity will adapt and adjust. A nonadaptive entity will be wiped out. From an intelligence perspective, the ability to study and track changes in the environment and also to formulate responses to the challenges unleashed by the environment can be enabled by intelligence.

In the Configuration School the strategy comes from structures, configurations, and states. The configuration is the state of an organization in the context of its surroundings, and strategy leads to change in state. From an intelligence perspective, the configuration school implies that the structures and states of a company are measured better, and the transformation strategy is tracked more effectively. The product, production platform, and interlinked network participate in determining the state of the system (the firm), and reconfigure, transform, or transition to a new state when change events happen.

THE INTELLIGENCE SCHOOL

      The intelligence era connects all ten schools into one—the intelligence-centric competitive advantage. In doing so the competitive advantage is shaped by factors such as:

       Intelligent machines are deployed to help understand internal and external environments, the existing states, the competitive dynamics, the cultural and social dynamics, and the set of opportunities and threats.

       The product itself, the production platform, and the interlinked network become the source of strategic information.

       The system creates awareness about its own states and transitions to a new state with awareness that a change event has transpired calling for transition.

       The system is viewed as a learning system and is composed of interactive agents that interact with each other and with external systems forming a complex system.

      Now let us evaluate what this means for an investment firm:

       Humans and Machines: Investment strategies will result from the interactive and collaborative efforts of machines and humans.

       Products: On the investment strategy side, learning machines (intelligence) will enable us to:

      1 develop new investment strategies;monitor the investment environment better;understand our own biases in formulating portfolio or asset selection strategies;predict outcomes;understand metacognitive structures in the markets—for example, stories, narratives, and alpha signals that are not easily detectable;respond quickly to opportunities and threats; anddesign, develop, and offer new products faster.

       Production Platform: On the production platform side, learning machines will help us improve regulatory and governance requirements, help identify and onboard new clients, help us develop and strengthen relationships with institutional clients, increase assets under management (AUM), deploy powerful marketing, provide excellent customer service, give clients powerful insights, enable value added services, introduce new products, and support all other services that are necessary for operations and production.

       Interlinked Network: This means that learning machines help build greater understanding of partners, suppliers, regulators, channel partners, and all other entities with whom the firm interacts.

      The competitive advantage of a firm is therefore architected based on the above factors. It is from these factors that firms understand how they will compete and win. It is also across those dimensions that differentiation of a firm would materialize. None of the above factors can be ignored by a firm.

      Note that the above discussion focused on intelligence of machines and the resultant augmentation of human capacity to understand our environment and make better decisions. Intelligence, in that context, is one side of artificial intelligence. The other side is automation.

INTELLIGENCE AND ACTIONS

      For business purposes, I define intelligence as being able to successfully perform work by displaying goal-directed behavior in situations of uncertainty. When machines display intelligence, they perform work and resolve uncertainty in accordance with goal-directed behavior. It can also be viewed as an attribute of an artifact by which it accomplishes work by successfully tackling uncertain situations in accordance with its goals.

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