Artificial Intelligence: Building Blocks and an Innovation Typology

This article provides a comprehensive overview of Artificial Intelligence (AI), focusing on its fundamental components and offering a framework for understanding its impact on business innovation. It aims to bring clarity to the broad and often complex discussions surrounding AI by defining its core elements and providing managers with analytical tools.

The Six Building Blocks of AI

The authors identify six essential building blocks that constitute the foundation of AI systems:

Structured Data: Organized data that can be easily processed and analyzed by algorithms.
Unstructured Data: Data that does not have a predefined format, such as text, images, and audio, requiring more advanced processing techniques.
Pre-processes: Steps taken to prepare data for AI algorithms, including cleaning, transformation, and feature engineering.
Main Processes: The core AI algorithms and models that perform tasks like learning, prediction, and decision-making.
Knowledge Base: A repository of information and rules that AI systems use to reason and solve problems.
Value-Added Information Outputs: The actionable insights, predictions, or automated actions generated by AI systems.

An Innovation Typology for Managers

To help managers navigate the strategic implications of AI, the article introduces a typology that categorizes AI-enabled innovations based on two key dimensions:

Boundaries of Innovation: This dimension differentiates innovations based on whether they primarily affect a firm's offerings or its operations.
- Product-Facing Innovations: These innovations directly influence the products or services a company offers to its customers. Examples include AI-powered recommendation engines or personalized product features.
- Process-Facing Innovations: These innovations focus on improving internal business operations, such as supply chain management, customer service, or manufacturing processes, through AI.
Effects on Organizational Competencies: This dimension examines how innovations impact a firm's existing skills, knowledge, and capabilities.
- Competence-Enhancing Innovations: These innovations build upon and augment existing organizational skills and knowledge, allowing employees to perform their tasks more effectively or to develop new capabilities. For instance, AI tools that assist designers or analysts.
- Competence-Destroying Innovations: These innovations render existing skills and knowledge obsolete, requiring significant organizational change and reskilling. An example might be AI automating tasks previously performed by human experts.

Strategic Implications and Applications

By applying this typology, managers can gain a structured understanding of:

Market Assessment: Evaluating the competitive landscape and identifying emerging opportunities and threats driven by AI.
Strategic Decision-Making: Making informed choices about where and how to invest in AI technologies to achieve strategic goals.
Organizational Adaptation: Understanding the potential impact of AI on workforce skills and planning for necessary training and development.

The article emphasizes that a clear grasp of AI's building blocks and the strategic implications of AI-driven innovations is crucial for businesses seeking to leverage AI effectively in today's rapidly evolving market.

Illustration of AI building blocks and innovation typology

Key Takeaways:

AI is built upon six core components: data (structured and unstructured), pre-processing, main AI processes, a knowledge base, and output.
A typology helps managers analyze AI innovations based on whether they affect products/services or operations, and whether they enhance or destroy existing competencies.
This framework aids in strategic planning, market assessment, and managing the impact of AI on organizational capabilities.

Publication Date: March 15, 2020 Source: Business Horizons Product #: BH1030 Pages: 9

Related Topics: AI and machine learning, Strategic planning, Product development, Organizational learning, Disruptive innovation.