Market drivers for decision intelligence

Often, the emergence of new technologies or concepts has been marked by tipping points that accelerate market attention. What do we identify as potential drivers in this market?

• Industry-specified success cases to centralized decisioning platform

  Decision Intelligence is neither a single technology nor standalone solution. The AI market has historically grown on the back of singular technologies such as deep learning, reinforcement learning, and generative AI. In contrast, Meta-Intelligence represents a framework wherein businesses and technologies are tightly interconnected. Furthermore, each industry has its own unique KPIs, processes and decision subjects. Therefore, industry-specified success cases become key disruptors that attract significant attention across various sectors.

  
  

  Although enterprises are encouraged to adopt a cross-organizational decisioning structure and platform, a business use-case accelerator is expected to be the initial step most companies will take. 

  
  

• Challenges in the role, authority, and control of Agentic AI

  Agentic AI has emerged as one of the most talked-about concepts in the AI field. It is expected to autonomously perform tasks, make decisions, and take actions with minimal human intervention. However, the presence of unknown ethical or commercial risks makes it challenging to implement AI agents in actual business operations.

  
  

  Decision Intelligence encompasses the entire decision-making structure, includes business goal, constraints, processes also the role of both AI and human experts. It also retains the history of decision outcomes over time. This pre-defined structure and operational history provide a rich source of information to train AI agents, clearly delineating their roles, authority, and control within the organization.