Intro
Preface
Contents
About the Authors
1: The AI-Enabled Enterprise
Motivation
Current State
Decision-Making in the Face of Uncertainty
Software Architecture for Continuous Adaptation
Automated Compliance with Minimal Exposure to Risk
Democratized Knowledge-Guided Software Development
Continuously Adapting Software
Coordinated Continuous Digital Transformation
The AI-Enabled Enterprise
Illustrative Example
References
2: Decision-Making in the Face of Uncertainty
Introduction
Current Practice
Decision-Making as an Optimization Problem

Model-Based Decision-Making
Human-Centric Decision-Making
Solution
Decision-Making Meta-Model
Digital Twin
``In Silico ́́Experimentation Aid for Decision-Making
Technology Infrastructure
Specification Language
DT Construction
DT Validation
Illustrative Real-World Applications
Case Study from Telecom
Maximizing Throughput of Sorting Terminals
Optimizing Shop Stock Replenishment for a Retail Chain
Prediction and Control of Covid-19 Pandemic in a City
Helping Organizations Transition from Work from Home to Work from Office Mode
Summary and Future Work

References
3: Regulatory Compliance at Optimal Cost with Minimum Exposure to Risk
Introduction
Regulatory Compliance
Current Practice
Tenets of a Desirable Line of Attack
AI-Aided Model-Based Automated Regulatory Compliance
Technology Infrastructure to Support the Line of Attack
AI-Based Model Authoring
Validating the Authored Model
Automating Compliance Checking
Benefits of the Proposed Approach
Illustrative Use Cases of Automated Regulatory Compliance
Assurance of Hygiene
Business Problem
Scope
Approach
Benefits

Compliance Hygiene and Change Impact Management
Business Problem
Objectives
Scope
Approach
Benefits
Compliance Checking
Business Problem
Current Practice
Objectives
Scope
Approach
Benefits
Change Management
Business Problem
Scope
Approach
Results
Benefits
Summary and Future Work
References
4: Continuously Adapting Software
Introduction
Digital Twin(s)
State of the Art
Modelling Twin Systems
Case Study
Twin System Execution
Twin Policies
Implementation: TwinSim
Training for Multiple Eventualities

Prototyping as Part of the Development Process
Research Roadmap
References
5: Democratized Hyper-automated Software Development
Introduction
Current Practice
Typical SDLC Today
Model-Driven Development
Low-Code/No-Code Platforms
AI-Powered SDLC
AI-Powered Requirements
AI-Powered Testing
AI-Powered Coding
Proposed Line of Attack
Knowledge-Guided, AI-Aided Refinement of Business Requirements into Software Requirements
Domain Ontology
Systems Knowledge
AI and NLP
Digital Twin(s)
Knowledge-Guided, AI-Aided Refinement of Software Requirements into Software Specifications