Capgemini Forecasts Autonomous AI Workers to Communicate by 2025

Key Insights:

• Autonomous AI agents collaborating in multi-agent systems will revolutionize task management and workflow automation by 2025, predicts Capgemini.
• Capgemini reports 82% of billion-dollar companies plan to adopt AI agents within three years, enhancing automation and reducing repetitive tasks.
• Generative AI adoption surged from 6% to 24% in one year, with larger companies leading the charge, reveals Capgemini’s latest research.

Capgemini, a technology services company, has forecasted the advent of autonomous AI workers capable of intercommunication by 2025. According to the firm, these AI-powered agents will collaborate to solve tasks within a “multi-agent AI” system, marking a significant leap in artificial intelligence applications.

Pascal Brier, Chief Innovation Officer at Capgemini, stated in an interview with CNBC that numerous companies are already exploring these agent technologies. He indicated that by next year, the integration of multiple autonomous agents in various applications is expected to become a reality.

Types of AI Agents and Their Functionality

Capgemini describes AI agents as technologies designed to operate independently, plan, reflect, and execute complex workflows with minimal human oversight. These agents are set to manage tasks behind the scenes, acting on behalf of human workers.

Brier explained that there are two main types of AI agents: individual agents and multi-agent systems. Individual agents perform tasks independently, while multi-agent systems involve agents interacting with one another to accomplish goals. For instance, a marketing-focused AI agent creating an ad campaign could autonomously collaborate with another agent in the legal department to ensure compliance with regulations.

The adoption of AI agents is on the rise, with Capgemini’s research indicating that 82% of surveyed companies plan to integrate these agents within the next one to three years. Only 7% of the surveyed companies have no plans for integration. The research surveyed over 1,100 companies, each with revenues exceeding $1 billion.

The United States is reportedly leading in the development and implementation of these technologies, while Europe is trailing. This rapid adoption is attributed to the potential benefits of AI agents, including automation and the reduction of repetitive tasks, enabling human workers to focus on more value-added functions such as enhancing customer experience.

Generative AI Adoption Trends

Capgemini’s report, titled “Harnessing the Value of Generative AI,” highlights a significant increase in the adoption of generative AI. In 2023, only 6% of organizations had integrated generative AI into their operations. This figure has surged to 24% in the current year, demonstrating a fourfold increase.

However, the adoption rates vary significantly between large and small companies. For instance, 10% of firms with annual revenues between $1 billion and $5 billion are implementing generative AI. In contrast, 49% of companies with annual revenues of $20 billion or more are adopting these technologies. Brier noted that larger companies have more resources to invest in generative AI, allowing them to conduct more experiments and achieve faster results.

Industry-Specific AI Adoption Rates

The adoption of generative AI also varies across different industries. The aerospace and defense sector leads with 88% of organizations investing in generative AI. In the retail sector, the adoption rate is lower, with 66% of companies implementing the technology.

This disparity in adoption rates is partly due to the scale at which larger companies can conduct generative AI experiments and measure results. Bigger companies have the advantage of investing more resources into these technologies, enabling quicker and more substantial advancements compared to smaller firms.

The next wave of AI, as described by Brier, involves the integration of AI agents capable of understanding, interpreting, adapting, and acting independently. These agents are expected to either replace or assist human workers in various tasks. The evolution from the initial understanding of prompts and large language models to the development of these sophisticated AI agents represents a significant advancement in the field of artificial intelligence.

Editorial credit: JeanLucIchard / Shutterstock.com

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