Agentic AI: The Top 5 Challenges and How to Overcome Them
Blog post from Confluent
Agentic AI, an advanced form of generative AI, is transforming how organizations automate processes by allowing AI agents to autonomously perform tasks, interact with systems, and make decisions, potentially revolutionizing industries by 2028. These AI systems engage in multi-step processes, providing benefits such as increased efficiency and cost savings, yet they also present challenges related to trustworthiness, security, and data privacy. Companies must address these issues by anonymizing data and using technologies like data streaming platforms to ensure high-quality outputs, while also investing in new infrastructure and talent to support these AI models. Despite privacy concerns and the need for significant initial investments, agentic AI is expected to proliferate, offering greater business impacts than current generative AI tools, as seen in examples like Microsoft Copilot's evolution from simple code automation to more autonomous functions.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| AI Agents | 19 | 1,991 | 303 | 121 | +71% |
| LLM | 2 | 4,013 | 569 | 191 | -13% |
| AI Coding Assistant | 1 | 862 | 116 | 63 | +24% |
| AI Model Fine-tuning | 1 | 643 | 171 | 88 | -36% |
| Real-time | 1 | 3,875 | 964 | 250 | -11% |
| Secrets Management | 1 | 662 | 132 | 64 | -5% |
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