AI trends and predictions from IDC’s Ritu Jyoti

Agentic AI is poised to create a massive $22.3 trillion global economic impact by 2030, representing approximately 3.7% of worldwide GDP, according to new IDC research. This emerging technology goes beyond today’s generative AI capabilities by combining autonomous decision-making with goal-setting abilities, enabling systems to independently identify problems and implement solutions without human oversight. Understanding the distinction between these AI approaches will be crucial for organizations seeking to capture the projected $4.80 in indirect ROI for every dollar invested in AI solutions.

The big picture: Agentic AI represents a fundamental evolution beyond generative AI by enabling autonomous systems that can set goals, plan, reason, and take independent actions without human direction.

• Unlike current AI assistants that require explicit instructions, agentic AI systems can identify problems, formulate solutions, and implement them with minimal human intervention.
• This technology is poised to transform customer experiences through complex decision-making abilities, moving AI from advisory roles to autonomous problem-solving agents.

Economic impact: IDC projects AI will contribute $22.3 trillion to the global economy by 2030, representing approximately 3.7% of worldwide GDP.

• Research indicates organizations can expect $4.80 in indirect ROI for every dollar invested in AI solutions.
• These economic benefits will likely accelerate as agentic AI capabilities mature and expand into more business functions.

Real-world application: Agentic AI in customer service demonstrates its transformative potential through end-to-end problem resolution without human intervention.

• In a retail scenario, an agentic system could identify a clothing exchange problem, locate alternative store inventory, propose a solution, and even offer a refund for customer inconvenience.
• This level of autonomous problem-solving represents a significant advancement over current AI systems that require human oversight for decision implementation.

Strategic recommendations: Technology leaders should focus on building high-value use cases while developing policies that enable effective human-machine collaboration.

• Organizations need to adopt AI with a balanced approach emphasizing speed, precision, and trust.
• Proper measurement frameworks will be essential for evaluating agentic AI’s effectiveness and ensuring alignment with business objectives.

Looking ahead: Agentic AI development will be accelerated by parallel advancements in complementary technologies.

• Progress in data management, cloud computing, and edge computing will create the infrastructure necessary for more sophisticated agentic systems.
• Future technologies including Artificial General Intelligence (AGI), quantum computing, humanoid robotics, and physical AI will further extend agentic capabilities.