Study: 76% of Firms Use Agentic AI
A new benchmark study on AI adoption in B2B go-to-market functions found that 76% of organizations are deploying agentic AI. The technology is being used for a range of tasks including campaign management, lead scoring, and content creation. This data indicates a decisive shift from AI experimentation to embedding autonomous agents into daily workflows.
- Agentic AI systems are distinct from other forms of AI because they can operate autonomously to achieve goals with limited human supervision. Unlike reactive AI that responds to prompts, agentic AI can proactively plan, make decisions, and take multi-step actions to complete complex tasks. - The adoption of this technology is growing, with one Gartner prediction stating that 33% of enterprise software applications will include agentic AI by 2028. Early adopters of agentic AI for lead generation have reported as much as a 50% increase in marketing-qualified leads. - In B2B marketing, agentic AI is being used to manage multi-step tasks such as lead acquisition and personalizing campaigns across different countries. For sales and marketing, it can interpret social media signals to understand buyer intent, optimize campaigns in real-time, and monitor competitors. - The core architecture of an AI agent includes perception systems to gather data, reasoning engines for analysis and decision-making, and action mechanisms to execute tasks. These systems use large language models (LLMs) as a "brain" to perform actions through various tools. - For small and medium-sized businesses, 63% of those who have adopted AI use it daily. A significant portion of these businesses report saving over 20 hours per month and between $500 to $2,000 monthly. - Key challenges in implementing agentic AI include the need for large volumes of high-quality data and ensuring compliance with privacy regulations like GDPR and CCPA. AI agents can also be prone to "hallucinations" or making confident decisions based on flawed data.
