Enterprise Use of AI Agents on the Rise
According to Deloitte’s Global 2025 Predictions Report, enterprise use of AI agents is on the rise, with 25% of enterprises using generative AI forecast to deploy AI agents in 2025, growing to 50% by 2027.
Autonomous Generative AI Agents
Deloitte defines autonomous generative AI agents, also known as agentic AI, as software solutions that can complete complex tasks and meet objectives with little or no human supervision.
Interesting Predictions
- Women’s Adoption Gap in Gen AI Usage is Closing Quickly: By 2025, women’s experimentation and usage of GenAI are projected to meet or exceed that of men, but tech companies still should improve trust, representation in training models, and diversity in the AI workforce.
- Gen AI is Driving Data Center Energy Consumption Surge: Electricity consumption by global data centers is forecasted to double to 4% (1,065 terawatt-hours) by 2030 as power-intensive Gen AI consumption grows faster than other uses and applications.
- Gen AI is Set to Make Devices Smarter: In 2025, the share of shipped Gen AI-enabled smartphones could exceed 30%, in addition to about 50% of laptops with local Gen AI processing capabilities.
Characteristics and Capabilities of Agentic AI
- Built on Foundation Models: Foundation models like LLMs enable agentic AI to reason, analyze, and adapt to complex and unpredictable workflows, making them more flexible than RPA and expert systems.
- Acts Autonomously: While the degree of autonomy varies, agentic AI can be trained to plan and execute complex tasks largely on its own.
- Senses the Environment: Agentic AI can perceive the environment, process information, and understand the context of the tasks it is given.
- Uses Tools: Agentic AI interacts with tools and systems to complete tasks, such as software, enterprise applications, and the internet.
- Orchestrates: Agentic AI can direct the participation of other systems and bots to complete a task.
- Accesses Memory: Agentic AI can access short-term memory to maintain context while performing a specific task, and long-term memory to learn and improve from experience.
Conclusion
As agentic AI continues to evolve, it is essential for businesses to understand its capabilities and limitations. With the ability to complete complex tasks and meet objectives with little or no human supervision, agentic AI has the potential to revolutionize the way we work. However, it is crucial to address the challenges and concerns surrounding its adoption, such as ensuring trust, representation, and diversity in the AI workforce.
FAQs
Q: What is agentic AI?
A: Agentic AI is software that can complete complex tasks and meet objectives with little or no human supervision.
Q: What are the characteristics of agentic AI?
A: Agentic AI is built on foundation models, acts autonomously, senses the environment, uses tools, orchestrates, and accesses memory.
Q: What are the benefits of agentic AI?
A: Agentic AI has the potential to revolutionize the way we work, completing complex tasks and meeting objectives with little or no human supervision.
Q: What are the challenges of agentic AI?
A: Ensuring trust, representation, and diversity in the AI workforce are crucial challenges to address when adopting agentic AI.
