Automated Decisioning & AI Decision Intelligence
Decision Intelligence (DI) allows for the codification of human expertise and knowledge into trustworthy AI models that automate complex decision making.
DI replicates human reasoning and produces decisions that are transparent, auditable and explainable.
It can make real-time recommendations, use “human-in-the-loop” so your team can review reasoning and approve or reject a decision, or take action autonomously. The model can also learn from every decision made.
- Make faster, better decisions
- Reduce risks
- Increase efficiency and scale
- Automate fraud detection, credit, tax, law, claims – almost any kind of decision
“Knowledge graphs” are used to encode the different factors, concepts and considerations that your subject matter experts weigh up when making a decision. It is used to replicate human reasoning and produces decisions that are transparent, explainable – and auditable.
The goal of AI Decision Intelligence is to empower organisations to make data-driven decisions more efficiently, accurately, and consistently by leveraging the power of AI technologies. It aims to augment human decision-making capabilities rather than replace them entirely.
AI Decision Intelligence finds applications across various industries, such as retail (optimising inventory, pricing, and marketing strategies), manufacturing (improving supply chain and production processes), finance (risk assessment, fraud detection, and investment decisions), and healthcare (diagnosis, treatment planning, and resource allocation).
The integration of AI in decision-making is not just a competitive advantage; it’s becoming a necessity in the modern business landscape.
Decision Intelligence / Business Rules Engine
Automated Decision Making (ADM)
The potential applications for ADM are vast, and include:
- Government Services: Streamlining processes like tax collection and social services.
- Healthcare: Assisting in diagnosis and treatment plans.
- Business: Enhancing customer service through chatbots and personalised recommendations.
- Transport: Managing traffic flow and optimising routes for delivery services.
Automation is no longer just about robots making things: increasingly, it involves computers making decisions. We rely on computers to process data, make predictions, apply rules, choose actions and determine outcomes. Automated decision-making comprises an expanding array of intelligent technologies – from deep learning to blockchains – which promise to solve challenging problems across many sectors, from healthcare and social services to transport and media.
Julian Thomas, Director, ARC Centre of Excellence for Automated Decision-Making and Society
Technology Partners
We work closely with leading AI and Intelligent Automation software companies
