Salesforce has launched Agentforce which is a code platform to facilitate the creation of personalized AI agents for organizations. AI agents accelerate the scaling of AI adoption. Enterprises cannot leverage the value of Copilots. It is a hit and miss world.
Agentforce facilitates the streamlining of business processes, delivers insights and enhances productivity.
Copilots do perform basic tasks. However, they are inefficient. That led to AI agents. It is in fact next iteration of deep learning models. AI agents go beyond and take actions on behalf of the users.
Organizations spend money on third party models — either as APIs or in the cloud. These are fine-tuned for specific uses.
Salesforce intends to democratize AI adoption. It conveys a message — do not build but buy. The pricing could be consumption-based.
Indian companies such as Mahindra and Mahindra, Tata Consumer and TVS are Saleforce customers.
When you build the model, you are required to enhance its capabilities continuously to create an ecosystem. However, when you buy the model, you depend on the vendor who keeps developing its product.
Agentforce is powered by Atlas, advanced AI reasoning engine. It simulates human thinking and planning abilities. Atlas analyzes data autonomously. It makes decisions. It completes complex tasks across business functions. Atlas can deploy custom made agents for specific needs. Agentforce makes decisions based on the most current and pertinent data by its integration with Salesforce’s Data Cloud and other systems.
These AI agents automate simple tasks first. Later they will be able to address complex tasks.
Agentforce has the underlying foundation of Data Cloud. It is a customer data platform (CDP).
To optimize their usage, AI agents must have access to all the data points of the organization. Data Cloud enables that. Even unstructured data is brought on record. It is crucial for AI agents.
AI Agents and RPA
Software companies are offering software-as-a-service (SaaS). AI companies too bet on this. However, automation being promised is akin to Robotic Process Automation (RPA). Such automation relies on software robots.
There is a difference between AI agents and RPA.
RPA automates repetitive and tedious tasks, e.g. transferring data between systems (APIs are not involved). Autonomous AI agents process information like humans (adapting to situations on account of changing conditions). This results into an efficient and effective workflow.
Autonomous agents may not kill RPA. RPA will be used for repetitive and tedious tasks. AI agents will be used for complex tasks. Both can co-exist.