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, according to Deloitte’s Global 2025 Predictions Report. Focusing on the impact of Gen AI on technology, media, and telecommunications industries, Deloitte’s report defines autonomous generative AI agents — aka, agentic AI — as software solutions that can complete complex tasks and meet objectives with little or no human supervision.
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Here are a few of Deloitte’s more interesting 2025 predictions regarding generative AI and agentic AI:
- 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. In 2023, women’s use of Gen AI was just half that of men.
- 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.
A deeper look into the AI agent adoption forecast from the report notes the following: “The growth of AI agents will be fueled by innovation from both start-ups and established industry leaders identifying new revenue opportunities. Built on large language models, these AI agents will offer greater flexibility and a wider array of use cases compared to traditional machine learning or deep learning methods. While the ultimate aim is to achieve autonomous and dependable agents, Deloitte expects significant improvements in their capabilities in 2025 as these technologies rapidly advance, with agentic AI moving past pilots and proofs of concepts in some markets and for some applications in 2025.”
Also: Agentic AI is the top strategic technology trend for 2025
According to Deloitte, agentic AI has these common characteristics and capabilities:
- 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. LLMs are improving rapidly, with enhanced reasoning and the ability to break tasks into smaller steps among the most recent breakthroughs.
- Acts autonomously: While the degree of autonomy varies, agentic AI can be trained to plan and execute complex tasks largely on its own. By introducing reasoning tokens, chain-of-thought models can solve more complex challenges than previous LLMs.
- Senses the environment: Agentic AI can perceive the environment, process information, and understand the context of the tasks it is given. Advanced agentic AI can process multimodal data, such as videos, images, audio, text, and numbers.
- 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. With multiagent systems, this means collaborating with other autonomous generative AI agents.
- Accesses memory: LLMs are stateless. Each interaction is processed independently, and information is not retained when an interaction is complete. With the addition of retrieval mechanisms and databases, 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.
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According to Deloitte, Gen AI chatbots and co-pilots are sophisticated; they can interact intuitively with humans, synthesize complex information, and generate content. However, they lack the degree of agency and autonomy that agentic AI promises.
Deloitte highlights the key distinction between co-pilots and chatbots vs. AI agents. Per Deloitte’s definition, “Agentic AI has ‘agency’ — the ability to act and to choose which actions to take. Agency implies autonomy, which is the power to act and make decisions independently. When we extend these concepts to agentic AI, we can say it can act on its own to plan, execute, and achieve a goal — it becomes ‘agentic’. The goals are set by humans, but the agents determine how to fulfill those goals.”
Salesforce’s State of AI Connected Customer research reveals that one-third of consumers would prefer working with AI agents for faster service. Many consumers are happy to communicate with an AI agent but also want to know when that conversation is happening.
Also: Sticker shock: Are enterprises growing disillusioned with AI?
In addition, agentic AI is the top strategic technology trend for 2025 according to Gartner. Companies will invest heavily in AI agents as the world of work changes forever. Research suggests one executive is the key to unlocking value from these transformations. The accelerated adoption of generative AI and agentic AI is creating great pressure on IT organizations. CIOs must also serve as chief AI officers, according to a Salesforce survey. Even though the majority of CIOs believe AI is a game changer, only 11% say they’ve fully implemented the technology, citing security and data infrastructure as their top impediments.
To learn more about generative AI and agentic AI future trends by Deloitte, you can visit here.
Artificial Intelligence
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