Key takeaways from the blog
Enterprise automation takes different forms according to the business requirements. As automation evolves with the advent of new cutting-edge technologies, such as AI and GenAI, business scenarios that were simply unthinkable in the past are now covered under the automation purview. However, as a business user, one must be clear about the different AI-driven automation terminologies and the scope of each technology.
Artificial Intelligence or AI is an umbrella term for technology that uses human-like intelligence for continuous learning and decision-making at each node of the automation workflow. It extends automation solutions beyond the scope of contemporary automation and transforms the business landscape. It is a kind of black-box that requires purposefully built explainability at different nodes that may act as speed-breakers for the process. But that is Responsible AI – taking responsibility for the overall good!
Generative AI or GenAI is a specialized AI skill in the overarching AI technology umbrella and focuses on generating new text, code, graphics, and audio by referring to specialized AI-models or Large Language Models or LLMs that are trained with a specific purpose by using existing data. GenAI inherits its continuous learning capabilities from AI technology, identifies patterns and trends from enterprise data, and generates new content based on the trained AI models. It produces more accurate and explainable results and references while using well-trained AI-models.
Agentic AI is a highly specialized AI skill that achieves pre-defined process goals while adapting to inputs from a changing ecosystem. It provides a high level of process autonomy without referring to humans at key decision-making nodes, as in the case of other automation technologies, such as RPA. Its smallest working units are referred to as AI Agents that work independently of human intervention while collaborating with other AI Agents to achieve pre-defined goals.
Both RPA and Agentic AI are part of the automation continuum. Basic RPA is rules-driven and waits for human intervention in case of exceptions. Agentic AI is powered by continuous learning AI-models for working towards pre-defined targets or goals with a higher degree of autonomy.
AI and GenAI can be looked upon as skill sets that power self-learning models that underpin the automation solutions to bring out a varying degree of process autonomy. AI is a wider term that uses algorithms for automating different tasks in specific domains. GenAI specializes in creating new content. AI and GenAI have their own specific use. Where the AI skill brings in more intelligence to a process, GenAI focuses on creating new content based on the AI models trained on existing data.
AI brings higher speed, precision, and accuracy to process automation across many business areas across industries. Some of the areas are –
GenAI generates new content by referring to LLMs that are trained exclusively on huge volumes of existing content. Some of the prominent areas for GenAI-led automation include –
Agentic AI is target-oriented. It compares different pre-defined logic and splits the task to achieve the target at top speed, without human intervention. Some of the critical Agentic AI use cases are –
With the advent of new age technologies, such as AI and GenAI, the automation continuum is maturing at hyper-speed. Each technology brings with it a set of capabilities that augment contemporary automation solutions to evolve them further along the automation continuum, for example Agentic AI. The new age technologies augment the automation solutions to fulfill a diverse set of use cases that require higher levels of precision.