Agentic AI Platforms Gain Momentum
Multiple companies have launched or funded AI platforms described as "agentic," designed to automate complex business tasks. Bluecore unveiled a "marketing agent" for retail that acts as both an analyst and operator, while Jampack AI raised $3.2 million for its platform automating CPG wholesale operations. Outsourcer WOW24-7 also launched a new department focused on agentic AI for customer experience.
- Agentic AI systems are designed to go beyond passively responding to prompts; they can perceive their environment, set goals, create step-by-step plans, and execute tasks across different applications with minimal human intervention. This autonomous nature is their key differentiator from other types of AI like generative AI, which focuses on content creation. - The core technology behind agentic AI combines large language models (LLMs) for reasoning and natural language processing, with machine learning to enable a continuous loop of perception, planning, action, and learning from the results. This allows them to handle more complex and judgment-based work that has traditionally been done by people. - In marketing, agentic AI is being used to deliver hyper-personalized content at scale by analyzing customer data to create unique user journeys. These systems can autonomously decide on and execute marketing actions in real-time based on customer behavior. - A key feature of agentic AI is its "chaining" ability, which allows it to perform a sequence of actions from a single request. For instance, a single prompt to an AI agent to "create a website" could result in the agent writing the code, populating the pages with content, designing visuals, and testing for responsiveness. - Several major companies are already deploying agentic AI for various business functions. For example, LinkedIn uses an agentic hiring assistant to help recruiters with tasks like drafting outreach messages and sourcing candidates, while Delivery Hero has a data analyst agent. - For financial services analysts, agentic AI can automate the time-consuming process of aggregating data and generating reports, freeing up analysts to focus on strategy and insights. In payment processing, it can help review and correct transaction details, a task that can often take operators significant time. - The adoption of agentic AI is expected to grow significantly. By 2026, it's predicted that up to 40% of enterprise applications will include task-specific AI agents, a substantial increase from the 5% seen in 2025. - Looking forward, the integration of agentic AI is expected to become a standard part of daily work, with businesses being partially run by AI, while humans focus on oversight, correction, and optimization. This shift is anticipated to redefine employee roles and the skills required in the workforce.
