Lets look at the most dominant types of AI algorithms and assign them to 6 different modules that an ideal AGI system capable of running a company should be composed of.

The systems needs to obtain sources of data, detect entities and features, predict future developments, understand trends, make decisions, allocate resources and coordinate them, try novel configurations and setups and communicate with humans.

AGI Modules according to Function

Entity Detection and Monitoring Module

This module would handle structured and unstructured data in order to identify and classify all kinds of events, objects and their features. It would be able to detect all important pieces that will then be used in other modules for prediction, optimization, or decision-making.

• Company Departments: Marketing, Product Management, Customer Service, Security
• Analyzed Processes: Sales trends, competitor analysis, product features, innovation, market insights, customer behavior, security checking
• Task examples: Customer Segmentation, Fraud Detection, Quality Control, Predictive Maintenance, Sentiment Analysis, Feedback Topic Clustering, Object Detection on an Image
• Types of AI: Classification using Boosted Trees (XGBoost), Neural Networks (NN) and Graph AI (eg. GNN), Clustering, Computer Vision

Predictive Analytics Module

This module would handle numerical data analysis, and predictive modeling. It would be able to understand patterns in data, learn from the environment, and model cause-and-effect relationships, enabling accurate predictions and informed decisions.

• Company Departments: Business Intelligence, Data Analytics, Finance, Marketing Performance, Product Performance
• Analyzed Processes: Financial forecasts, sales performance, customer metrics, product adoption
• Task examples: Customer Churn Prediction, Credit Scoring, Demand Forecasting
• Types of AI: Prediction using boosted trees (XGBoost) and Causal AI (Causal Inference, Bayesian Structural Time Series)

Strategic Decision-Making, Optimization and Resource Allocation Module

This module would handle all kinds of decision-making based on the collected information, contextual understanding and predictive modeling. The use-cases would be business strategies, resource allocation, and long-term planning.

• Company Departments: Strategic Planning, Executive Leadership, Senior Management, Marketing
• Analyzed Processes: Long-term planning, resource allocation, competitive strategy
• Task examples: Portfolio Optimization, Designing Customer Policies and Strategies, Optimizing Marketing Tactics
• Types of AI: Cognitive AI, Optimization Techniques, Evolutionary Algorithms, Inverse Reinforcement Learning

Autonomous Operations, Coordination and Adaptation Module

This module would manage and coordinate autonomous systems, simulate decentralized decision-making, align departments and teams for efficient task execution, and adapt business processes based on changing circumstances. The use-case would be synchronization of all child agents performing activities on behalf of the organization.

• Company Departments: Operations, Supply Chain Management, Cross-functional Teams, Project Management
• Analyzed Processes: Inventory management, production scheduling, logistics, cross-team collaboration, project execution, emergent team behaviors
• Task examples: Complex Manipulation Robots, Self-Learning Industrial Robots, Autonomous Vehicles, Optimizing Energy Consumption, Adaptive Trading Strategies in Finance, Fine-Tuning Industrial Processes for Maximum Efficiency, Adaptive Traffic Management and Optimization, Disaster Response Planning and Coordination, Self-Organizing Drone Swarms for Environmental Monitoring
• Types of AI: Reinforcement Learning, Multi-Agent Systems, Swarm Intelligence

Research and Innovation Module

This module would explore unknown configurations to perform basic and applied research in order to increase the range of options available. The use-cases would be explore solution spaces and adapt option features over time.

• Company Departments: Research and Development, Engineering, Design, Information Technology
• Analyzed Processes: Discovering new materials, testing network architectures, website user experience design, AI model hyperparameter fine tuning
• Tasks examples: Creating Innovative Architectural Designs, Evolving Materials for Advanced Manufacturing, Evolving Drug Molecules for New Pharmaceuticals
• Types of AI: Evolutionary Algorithms (Genetic Algorithms, Co-evolutionary Algorithms)

Human Communication and Experience Module

This module would understand and generate language to interact with customer and stakeholders. The use-cases are to communicate, offer personalized guidance, enhance customer experience, ensure positive human-machine interactions, and monitor human well-being.

• Company Departments: Customer Service, Marketing, Public Relations, Human Resources
• Analyzed Processes: Customer inquiries, marketing campaigns, brand perception, employee development
• Task examples: Communication via Chatbot, Machine Translation, Question Answering, Social Media Content creation, Product Recommendation to Users, Tailoring Content to User Interests, Enhancing User Experience in Social Media Feeds, Recommending Career Paths based on Individual Strengths
• Types of AI: Language AI (Large Language Models, Named Entity Recognition, Word Embeddings), Recommendation Systems and Emotion AI

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