Agentic AI : What is this term all about? How it is different from traditional bots?

The Truth About Artificial Intelligence (AI)

Unlike what you might have seen in sci-fi films or read online, AI isn’t on the verge of taking over the world—or even replacing your customer service role. However, it is set to transform many aspects of our lives, as you’ll discover in this unit.

But what exactly is artificial intelligence? At its core, AI refers to programming machines to mimic human thinking. You can spot AI in action all around you. For instance, if you’ve ever placed an order through Alexa or asked Siri for restaurant suggestions, you’ve experienced its advantages firsthand.

AI isn’t a groundbreaking new idea—we’ve had theoretical models for decades. What’s changed is the ability to make it a reality, thanks to the surge in available data and the decreasing cost of powerful computing resources.

Understanding Machine Learning

Machine learning is the driving force behind AI. It involves using algorithms to uncover meaningful patterns in data without the need to write code tailored to every specific problem. In simpler terms, it allows computers to learn from data with minimal programming effort.

Instead of crafting detailed code, you provide the machine with data, and it creates its own logical framework based on that information.

Now that I have highlighted the pillars of Agentic AI, let's talk about what the fuss is all about?

The Foundation of Machine Learning: Data

So, how does machine learning actually work? It all begins with training data—a collection of information provided to the model to help it learn. The more data you supply, the more precise and effective the model becomes.

When this training data is introduced, it comes with various attributes and characteristics. The model’s job is to figure out how to interpret and make sense of these details. But how does it decide which attributes are the most important for creating the best model? This is where algorithms come in—they evaluate and weigh different features to find the optimal combination that, when put together in an equation, solves the intended problem.

Since machine learning relies heavily on data, maintaining data quality is crucial. Clean, well-organized data ensures a smoother AI implementation. Conversely, if your organization has poor data management—like incomplete customer records or duplicate entries—it can make the process much harder. In such cases, manual effort is needed to clean the data before it can be used for training. However, this investment in data cleaning will lead to a more accurate and effective AI system in the end.

Agentic AI : Ehh?

Agentic AI is a type of artificial intelligence that can make its own decisions and take actions to achieve specific goals without needing constant instructions.

Imagine a smart home system that not only follows your commands but also learns your habits and preferences. For instance, it can adjust the thermostat based on your daily routine, turn off lights when rooms are not in use, and even order groceries when it detects that supplies are running low. This system makes decisions and takes actions on its own to make your life more convenient.

How is an AI agent different from a chatbot?

Traditional chatbots require pre-determined conversation trees to respond to enquiries. In contrast, agents are dynamic. They can adapt to human language and conversation and they have the ability to reason. They make sense of the conversation, build a plan to address it, understand the tools available to them and then take the best course of action.

Agents use large language models (LLMs) to analyze and understand the full context of customer interactions or an automated trigger, then decide the reason through decisions on the next steps autonomously.

These agents generate responses that are consistent with your company’s brand voice and guidelines using trusted business data.

These agents are capable of operating 24/7 across various platforms like self-service portals and messaging channels,  within set guardrails. When faced with complex issues beyond their scope, they can escalate the matter to human agents, ensuring that queries are resolved efficiently and accurately.

Salesforce’s Agentforce : The Path breaking Agentic AI

Agentforce is a tool within the Salesforce ecosystem designed to enhance sales processes by acting as an AI teammate. Agentforce is an autonomous AI agent that can perform tasks across various business functions such as sales, marketing, customer service, and commerce. The AI agents operate independently, utilizing real-time data to make informed decisions and take actions without human intervention.

You can also create a custom agent, because if you can describe it, agentforce can do it by taking a natural language description of the job you want your agent to do and then using that description to find semantically similar resources in the metadata. Once created, the agentforce will work within the guardrails you have established. They also have built-in mechanisms for harm and toxicity detection, ensuring they avoid engaging in inappropriate or harmful activities.

To know more about Agentforce, feel free to reach out to me!