In today’s fast-paced business world, efficiency and adaptability are key pillars for success. Automation has been a key tool in this regard. In its evolution, Agentic Automation emerges as an innovative approach that combines the best of RPA automation with the advanced capabilities of artificial intelligence.
What is Agentic Automation?
Agentic Automation represents a significant advance in the field of automation. It is based on the use of software agents driven by large-scale language models (LLMs) and other advanced AI technologies to perform actions autonomously. These agents are able to perceive their environment, reason about it, formulate questions and execute a set of actions to achieve specific goals.
Unlike traditional automation systems, which follow predefined paths and lack adaptability, agents in Agentic Automation can evaluate contexts and probabilities, dynamically adapting to changing situations. This enables them to handle complex tasks that previously required human intervention, such as interpreting unstructured data or making decisions in real time.
Differences between deterministic and nondeterministic automation
To fully understand the relevance of Agentic Automation, it is crucial to distinguish between deterministic and nondeterministic approaches to automation.
Deterministic automation is based on algorithms that follow a set of predefined rules. Given a specific input, they will always produce the same output. An example of this type of automation is RPA, which automates repetitive, rule-based tasks such as data entry or invoice processing. These systems are accurate and reliable in environments where tasks are predictable and require no adaptations.
On the other hand, nondeterministic automation employs algorithms that do not follow a single predefined path. Instead, they evaluate multiple factors and contexts to determine the most likely outcome. AI agents powered by LLMs are an example of this approach, as they can interpret context, learn from previous interactions and adapt to new situations, offering responses and solutions that are not strictly hard-coded.
Agentic Automation is able to leverage RPA through the use of artificial intelligence.
The convergence of RPA and AI Agents: a hybrid ecosystem
Although RPA and AI agents represent distinct approaches, their combination can offer more robust and versatile solutions. This hybrid ecosystem leverages the strengths of both worlds:
- Hybrid use cases: In processes such as insurance claims management, RPA can handle structured tasks such as extracting policy details, while an AI agent could interpret customer emails to detect intent and urgency.
- Division of labor: RPA excels in the execution of repetitive and precise tasks, while AI agents provide analysis and adaptation capabilities, enabling efficient collaboration between the two systems. The idea is to enable each to perform the part of the job in which they are optimal.
- Scalability and flexibility: Enterprises can use RPA to ensure stability in predictable processes and deploy AI agents to address dynamic challenges, striking a balance between efficiency and innovation.
Benefits of Agentic Automation
The implementation of Agentic Automation offers multiple advantages for organizations:
- Adaptability: AI agents can handle ambiguous situations and adapt to changes in real time, which is essential in dynamic business environments.
- Continuous learning: These systems improve over time, learning from each interaction and optimizing their future responses and actions.
- More human interactions: By interpreting contexts and nuances, AI agents can provide more personalized responses, enhancing the customer experience, as they are even able to detect feelings.
- Operational efficiency: By automating complex tasks and reducing the need for human intervention, companies can optimize resources and reduce operating costs.
Implementation of Agentic Automation in the company.
To successfully integrate Agentic Automation in companies, it is important to consider the following steps:
- Process assessment: Identify which tasks and processes can benefit from Agentic Automation, especially those that require adaptability and real-time decision making.
- Selecting the right tools: To choose a platform that offers specific Agile Automation solutions. For example, UiPath has developed a platform that allows converting intermittent workflows into end-to-end automations by integrating agents, robots and people.
- Education and training: It must be ensured that the team is trained to work with these new tools, understanding both their capabilities and limitations.
- Monitoring and continuous improvement: Establishing clear metrics to evaluate the performance of AI agents and making adjustments as needed to optimize their effectiveness is a key factor that ensures continuous improvement during implementation.
Conclusion
Agentic Automation is emerging as a natural and necessary evolution in the field of business automation. By combining the precision of deterministic systems with the adaptability of artificial intelligence, it offers organizations a powerful tool to address current and future challenges. Adopting this approach not only improves operational efficiency, but also positions companies at the forefront of technological innovation.
At Devol, we are committed to implementing advanced automation solutions that drive our customers’ competitiveness and efficiency. Contact us to discover how Agile Automation can transform your business processes and take them to the next level.
