Why agentic AI is poised to transform multiple industries

The artificial intelligence industry is entering a new phase with agentic AI, a technology that promises to transform business operations by enabling autonomous decision-making and execution of complex tasks.

Current state of AI adoption: Organizations are heavily invested in generative AI despite mixed results in generating tangible value from existing solutions.

• A comprehensive NTT DATA study reveals that 97% of CEOs anticipate material impact from AI technology
• Nearly all surveyed organizations (99%) plan to increase their GenAI investments
• Only 43% of C-suite executives strongly agree that current AI solutions meet their expectations

Understanding agentic AI: This advanced form of artificial intelligence represents a significant evolution beyond basic generative AI capabilities, offering autonomous operation and decision-making capabilities.

• The technology can independently execute tasks within workflows based on real-time analysis
• Unlike current AI systems limited to question-and-answer interactions, agentic AI can make and implement decisions autonomously
• 95% of organizations recognize AI’s role in driving innovation and creativity

Practical applications: Agentic AI is beginning to emerge across multiple sectors with specific use cases demonstrating its practical value.

• Healthcare providers can utilize AI-powered diagnostic tools for medical image analysis and disease detection
• Insurance companies can implement end-to-end workflow management for customer interactions
• Autonomous vehicles and automated trading systems represent other key applications of this technology

Implementation framework: NTT DATA outlines five critical factors for successful agentic AI deployment.

• Integration must occur across the full technology stack to deliver meaningful outcomes
• Strategic alignment between AI initiatives and business objectives remains crucial, though currently only achieved by 49% of organizations
• Data readiness and governance need to be addressed alongside business process transformation
• Mature AIOps and human oversight are essential for maintaining and improving AI models
• Strategic partnerships can accelerate innovation and provide access to smart-agent ecosystems

Looking ahead: Industry implications: While agentic AI remains in its early stages, its trajectory suggests rapid adoption across sectors.

• Organizations should begin identifying specific use cases that align with their business objectives
• The technology’s ability to autonomously execute tasks could fundamentally reshape workflow automation
• Success will likely depend on establishing strong partnerships and maintaining robust governance frameworks