Agentic AI: The AI Agents That Will Change Our Companies E182
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Introduction
Today, I'm excited to discuss an emerging trend in artificial intelligence known as agentic AI. Though the phrase may sound unusual, the core concept is simple: AI large language models are evolving from mere conversation partners into capable agents that can take action on our behalf. This transition marks a significant shift from traditional large language models to large action models.
The Shift to Action
In our daily and professional lives, chatbots and AI systems are becoming increasingly prevalent. With agentic AI, these systems will be connected to various applications, allowing them to perform tasks such as sending transactions, drafting emails, or creating documents. Essentially, these agents will function like employees, carrying out repeatable tasks that benefit organizations.
For example, consider an Learning and Development (L&D) professional who needs to create a training course. Typically, this process involves several steps: gathering content, collaborating with subject matter experts, constructing the course material, launching it, and monitoring its effectiveness. An AI agent could streamline this entire process by communicating with experts, gathering material, designing and publishing the course, and tracking engagement—all automating tasks that were once manual and cumbersome.
A Specific Use Case in L&D
When building a course, an agent can perform many tasks that would historically require human intervention. It could send emails to gather information from subject matter experts, consolidate that information into a usable format, receive feedback from stakeholders, and automatically publish the course content into a Learning Management System (LMS). This not only saves time but also ensures that no step is overlooked.
Agent Management in Recruitment
Another practical application of agentic AI is in recruitment. The recruitment process involves many complex steps, such as writing a job description, reviewing resumes, and conducting interviews. An AI agent can help draft job descriptions by gathering information from hiring managers, posting job ads, screening applicants, conducting preliminary interviews, and even short-listing candidates based on qualifications. This allows human recruiters to focus on more qualitative aspects, like cultural fit.
The New Workplace Landscape
With agentic AI, organizations will see a transformation in their technology architecture. Traditionally, companies use various applications, from HR systems to sales platforms, leading to fragmented data management. Agentic AI acts as an interface that interacts with these multiple systems, consolidating data and performing tasks without manual input from employees. Rather than navigating various software individually, employees can simply ask their agents to retrieve information or complete transactions, thus simplifying the overall user experience.
Agents as Digital Employees
The concept of treating these AI agents as digital employees, as suggested by Sarah Franklin, CEO of Lattice, might initially seem controversial. However, it reflects the reality that organizations will need to onboard these agents, training them on company culture, workflows, and expectations. Managing AI talent will become a new frontier, where humans will be tasked with fine-tuning the abilities of their AI colleagues.
Governance and Collaboration Between Agents
As these AI systems become commonplace, governance will become essential. Each agent must be trained adequately to avoid errors, security issues, or information leaks. Moreover, the potential for agents to communicate with one another offers exciting opportunities for task automation across departments, enhancing efficiency and productivity.
Measuring AI Impact
Despite concerns about the high costs associated with implementing AI infrastructure, agentic AI is expected to drive significant ROI by automating processes and enhancing productivity. Companies are beginning to offer services based on the value generated by these agents rather than traditional licensing models, indicating a shift towards productivity-based metrics.
Conclusion
Agentic AI is poised to revolutionize the workplace, transforming how we interact with technology and redefining the roles of employees and AI agents alike. As we venture deeper into a world driven by these intelligent systems, it is crucial for organizations to understand and adapt to the inevitable changes in their operations and technology landscapes.
Keywords
- Agentic AI
- Large language models
- Learning and Development
- Recruitment
- Employee experience
- AI agents
- Automation
- Productivity
- Data management
FAQ
What is agentic AI?
Agentic AI refers to artificial intelligence systems that not only respond to queries but also perform tasks and take actions on behalf of users.
How can agentic AI improve the recruitment process?
Agentic AI can automate various recruitment tasks, such as drafting job descriptions, screening candidates, conducting interviews, and compiling reports, allowing human recruiters to focus more on candidate relationships rather than administrative tasks.
What role do AI agents play in Learning and Development?
In L&D, AI agents can streamline course creation by gathering content, managing feedback, publishing material, and tracking engagement, thereby simplifying the training process.
How does agentic AI change the technology landscape of organizations?
Agentic AI acts as a single interface connecting various organizational systems, enabling easier access to data and performing complex tasks without requiring employees to interact with multiple software platforms.
Why is governance important for AI agents?
Governance is crucial to ensure that AI agents operate correctly, protecting sensitive information, avoiding errors, and continuously improving through proper training and management.