{"id":54767,"date":"2024-11-27T07:40:39","date_gmt":"2024-11-27T12:40:39","guid":{"rendered":"https:\/\/centricconsulting.com\/?p=54767"},"modified":"2024-11-26T14:42:25","modified_gmt":"2024-11-26T19:42:25","slug":"an-executives-crash-course-in-ai-agents_ai","status":"publish","type":"post","link":"https:\/\/centricconsulting.com\/blog\/an-executives-crash-course-in-ai-agents_ai\/","title":{"rendered":"An Executive\u2019s Crash Course In AI Agents"},"content":{"rendered":"

In this segment of \u201cOffice Optional with Larry English<\/a>,\u201d Larry gives an overarching look and what executives need to know about AI agents.<\/h2>\n
\n

OpenAI launching agents in 2025. Salesforce\u2019s CEO announcing AI agents as the third wave of AI. Microsoft adding agent capabilities to Copilot.<\/p>\n

The message here is clear: AI agents are going to be big, and leaders need to begin strategizing now about how to incorporate this powerful technology into their organizations.<\/p>\n

If you\u2019re not sure what AI agents are, you\u2019re already behind the AI curve. You\u2019re also not alone \u2014 AI is developing at a dizzying pace, and most leaders are struggling to keep up.<\/strong> \u201cInnovation is happening faster than you can imagine or adapt to, and large organizations are racing against time to move from data to value to insights to action,\u201d notes Abhas Ricky, chief strategy officer at Cloudera, a hybrid data platform.<\/p>\n

Read on for an AI agent crash course, including a definition of this new technology and answers to questions about security, team impact and the investment required for leaders to get their organization caught up.<\/p>\n

What Are AI Agents?<\/h2>\n

AI agents are advanced AI systems that can complete complex tasks and make decisions on their own. They can analyze data, make predictions, offer insights, converse, solve problems, create strategies and more. They learn over time and adjust to real-time data, offering a high level of accuracy, efficiency and agility.<\/p>\n

How are AI agents different from ChatGPT and other LLMs? AI agents work independently, following instructions to use a variety of tools to complete tasks.<\/strong> ChatGPT doesn\u2019t do anything on its own \u2014 humans must enter a question or prompt to get a response.<\/p>\n

Like any tool, AI agents aren\u2019t going to magically solve every business problem. But they are extremely powerful \u2014 especially when you combine agents together to create agentic workflows, which allows them to accomplish complex tasks.<\/p>\n

Answers To 7 Burning Questions About AI Agents<\/h2>\n

Any new technology brings with it a wave of concerns, fears and excitement. AI agents are, of course, no different. Here are some answers to top questions from leaders about the technology:<\/p>\n

Are AI agents just fancy chatbots?<\/h3>\n

Nope. This is a common misperception. During a recent webinar on AI agents<\/a> my company Centric Consulting hosted we asked attendees what they thought AI agents were. Nearly 20 percent responded with \u201cchatbots.\u201d Chatbots are reliant on user input, whereas agents use AI and natural language processing. AI agents<\/a> can have a conversational interface \u2014 just like a chatbot \u2014 but it\u2019s not a requirement.<\/p>\n

How do I minimize security risks when handing over entire processes to AI?<\/h3>\n

Agents should have clear rules around what they\u2019re allowed to do. Agents that try to be all things to all people tend to fail spectacularly.<\/strong> Once the agent is live, actively monitor inputs and outputs during the initial use phase. This helps provide transparency and explainability, creating an audit trail so you can have confidence in the technology. As you scale, you can transition out to passive monitoring to flag anomalies.<\/p>\n

\u201cIn the first phase of deploying agents, you need to put humans in the loop all the time,\u201d says UiPath CEO Daniel Dines.<\/p>\n

Is there any data yet on how AI agents will impact organizations?<\/h3>\n

One study predicts that agentic AI will achieve 60 percent productivity gains<\/a> for organizations. AI agents are most powerful when combined to create agentic workflows. Compared to single, one-off AI agents, agentic workflows can tackle more complex tasks, solve more complex problems and achieve greater boosts in efficiency and productivity.<\/strong><\/p>\n

What do agentic workflows look like? Ricky shares an example of agents working together to achieve tax invoice reconciliation and loan underwriting in an autonomous fashion. \u201cImagine agent one is reading tax documents, agent two is extracting additional sources, agent three is benchmarking the tax data, agent four is writing the memo for you, agent five is fact-checking the memo and agent six is formatting the memo,\u201d Ricky says. \u201cThere\u2019s potential for 99 percent productivity improvements, as well as vast improvements in consistency.\u201d<\/p>\n

OK, but how are companies using AI agents in real life?<\/h3>\n

Some forward-thinking organizations have already deployed AI agents<\/a> successfully. The technology is making inroads across many industries, including insurance, marketing, manufacturing, customer service, financial services, supply chain and healthcare.<\/p>\n

For example, my company recently helped a healthcare technology organization build an AI agent to analyze and extract demographic data from disparate sources (patient charts, pharmacy orders, hospital discharge notes, etc.) to help manage prescriptions. The tool reduced manual labor by 82 percent and increased accuracy to nearly 100 percent.<\/p>\n

To share just a few more quick examples:<\/strong><\/p>\n