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It may feel like you’ve just got to grips with predictive AI and generative AI, but now there’s an even newer ‘kid on the block.’ Enter agentic AI.
Not only does this brand-new “AI agent” generate content, it can also learn autonomously (without the need for human prompts) to make decisions and adapt to changes. What makes this tool so useful is that it doesn’t just take its information from large data sets; it can also assess its own environment and learn from feedback.
In business, this is helping to change the game by automating workflows, improving customer experiences, increasing efficiency, and reducing costs.
Salesforce Agentic AI is at the forefront of this shift, offering tools that can help you to boost productivity, streamline operations, and personalize customer experience with its digital labor platform.
In this article, we’ll give an in-depth look at how agentic AI is changing the game, including outlining the three stages of AI agents and exploring new tools that will help you to scale AI with ease.
The Emergence of Salesforce Agentic AI
Autonomous AI agents have some incredible use case in the business landscape. Not only does it automate and handle a wide range of routine tasks, it also centers on AI systems working collaboratively alongside human teams. Think of it as the next step in AI evolution—one step greater than GenAI—where AI actively works with people to make their jobs easier and more efficient.
Salesforce AI is the perfect example of this. Salesforce’s foray into AI began with Salesforce Einstein, a machine learning tool that was integrated with the Salesforce CRM. Now, Einstein has evolved into Salesforce Agentic AI, which builds on this foundation to offer new capabilities like real-time insights and take over routine tasks. This allows Salesforce users to focus on work that really matters to them.
Let’s put this into context. Imagine a sales team usually spends hours sifting through customer data for leads and sending follow-up emails. Now, with Salesforce Agentic AI, this can all be automated, freeing the team up to focus on building customer relationships.
Salesforce Agentic AI is designed to improve several areas of business, including:
Productivity: While agents cover all your mundane tasks, you can focus more on creative and strategic work that makes a true impact.
Efficiency: Agentic AI helps to smooth out your workflows to speed tasks up and ensure they run without a hitch.
Decision-making: Using huge amounts of data, agents can make smarter decisions faster, taking the guesswork out of your choices.
Job Satisfaction: Without having to worry about all the repetitive, mundane tasks that usually come with business, your employees can focus on what they enjoy, making work more fulfilling.
To put it simply, if you’re using AI agents like Salesforce Agentic AI, you’re not just implementing new technology — you’re overhauling how work gets done. Want to empower your employees to work smarter and faster? Agentic AI is the way to go.
The Three Stages of Enterprise AI Agents in Salesforce
Over time, AI has evolved from its early stages as a rigid automation tool to a more flexible and adaptive integration. Similarly, AI agents are quickly becoming more advanced. What started out as solo assistants are now developing into true team players.
It’s like us going from dial-up internet to 5G connectivity. Early AI was slow and limited, requiring plenty of manual input. In contrast, agentic AI is the 5G of the business world, seamlessly connecting systems and delivering insights with no lag.
So, how did agentic AI get to where it is today? There were three stages of agentic AI development, each building on the last to produce the nuanced tool we use today.
Stage One: Specialized Contributors
In the initial phases of agentic artificial intelligence, specialized AI systems perform specific tasks within certain industries. They are single-purpose. This is great for getting routine yet important jobs done accurately, but they lack scope.
So, while they can handle repetitive tasks, such as data entry or processing documents in precise areas, they lack the wide range of capabilities of more advanced AI tools. This is because they act in an isolated way, and are unable to communicate and collaborate with other AI systems or human teams.
Although we may dismiss these specialized contributors as being too simple, they formed the foundation of agentic AI adoption.
For example, the Salesforce product suite uses specialized AI to analyze email sentiment and prioritize responses based on their urgency, which can then be used to schedule and send follow-up emails.
And, if this isn’t enough, you can even generate personalized content for upcoming emails.
Although these tasks may have to be performed individually by separate AI agents, this doesn’t take away from the fact that automating these processes frees up time and effort for a sales team that can then be used in more productive ways.
Stage Two: Seamless Collaborators
In “specialized contributor” AI, we had multiple agents performing their specific tasks individually. Now, picture an agent that can coordinate the activities of each specialized contributor. This is a “seamless collaborator” AI.
It’s a bit like how a conductor ensures harmony between all of the different instruments in an orchestra. In this AI, an “orchestrator agent” ensures collaboration between all of the specialized agents within the same company.
This allows each individual contributor to work together towards a shared business goal. But how does this look in practice?
Take this example: Multiple autonomous agents can collaborate behind the scenes to close a deal with a large client. Collaborative AI coordinates several specialized agents to get the job done.
- A sales inquiry agent gathers relevant details from the potential client.
- A product specialist AI puts together some tailored product recommendations and pricing based on the client’s industry and past behavior.
- A contract and compliance agent generates a personalized contract that complies with legal requirements.
- An engagement AI schedules automated follow-ups via personalized emails to keep the client engaged while they make their decision.
The orchestrator agent coordinates all of these inputs to take the manual effort out of making a deal while still making sure the client receives a fast and personalized experience.
Stage Three: The Enterprise Orchestrators
Finally, we reach the current (and ideal) stage of agentic AI Salesforce — The enterprise orchestrators. This form of agentic AI reaches a new level of sophistication by introducing agent-to-agent (A2A) encounters across businesses.
This essentially transforms business relationships. Now, agents can act as intermediaries between businesses and their customers, creating business-to-agent (B2A) and business-to-agent-to-customer (B2A2C) interactions.
For example, this can be transformative for customer service. Imagine a customer’s personal AI agent contacts your business to request a refund or exchange.
In response, your company’s customer service AI agent processes the request and suggests a resolution.
Then, an AI finance agent handles the refund.
And, finally, a logistics AI agent coordinates the product return automatically.
Using enterprise orchestrator AI, agents can work together across business and customer boundaries to automate negotiations and organize cross-company interactions. How can things get more efficient than that?
Building Trust and Accountability with Agentic AI Salesforce
It can’t be denied that agentic AI has a myriad of benefits for businesses. But with great power always comes great responsibility. Thus, it’s essential to maintain two principles when deploying AI: trust and accountability.
Maintaining Trust
AI has always been faced with various ethical concerns, but beyond the usual issues of bias and toxicity, we need total transparency and strict boundaries to uphold public trust in AI.
So, how do we achieve this? Essentially, we can’t just let agentic AI run rampant — it needs to be held by strict rules to ensure that it’s accurate and only works within agreed ethical boundaries. For instance, there need to be universally accepted protocols for AI systems to communicate and collaborate safely.
Additionally, agentic AI should always be self-aware — and no, this doesn’t mean becoming fully conscious à la sci-fi horror films. It just means AI recognizes its own limitations and knows when to ask for human help.
Lastly, agentic AI is bound to continue growing and developing. As such, it’s important that businesses continually strengthen their security to protect against misuse.
All of these measures will help make sure that AI remains a trustworthy collaborator in business, because no one wants a bad business partner.
Keeping Accountability
Agentic AI makes countless decisions each day, and occasionally things will go wrong. Because of this, businesses need to be clear on whom to hold accountable when mishaps happen, and how to remedy a situation.
Here are a few steps businesses should take to ensure accountability:
1: Assign Clear Responsibility: You must always be able to trace AI decisions back to a human. One way to do this is to create new roles, such as an “AI Operations Officer,” who can take responsibility for all AI systems.
2: Detect and Fix Errors Quickly: AI has so many fantastic benefits, but unfortunately it can cause a good deal of damage too if it goes wrong. We must constantly monitor AI to identify errors (such as biases) before they cause harm. Luckily, new AI methods such as Salesforce's retrieval-augmented generation (RAG) are improving AI accuracy.
3: Balance AI Independence with Human Control: It’s not enough for humans to just be “in the know” when it comes to AI. Instead, you should have strict guidelines on ways to step in to keep humans at the forefront of big decisions.
4: Have a Plan for Mistakes: As mentioned, AI does sometimes make errors, such as failing to understand context correctly. As a result, you must have clear steps laid out to fix the issue, let customers know, and prevent the same problem from happening in the future.
5: Stay on Top of AI Regulations: The laws around AI are always being updated, so you should work proactively with regulators to make sure your AI agents are always compliant.
Salesforce’s Agentic AI helps maintain trust and accountability through strict security measures and transparent decision-making. This enables seamless human-AI interaction. What’s more, its advanced RAG technology and built-in compliance framework keep AI actions accurate and ethical.
Scaling Salesforce Agentic AI Faster With New Tools
Many businesses would love to enjoy all of the benefits that agentic AI affords but have no idea how to set it all up. This is understandable, as in the past this has been a long and complex process.
Now, however, new tools are simplifying the building and deployment of AI agents. Take Agentforce, for example. This is Salesforce’s powerful solution to developing and scaling Agentic AI within their platform. It ensures businesses can seamlessly deploy new opportunities for growth without the usual delays.
Why Is Agentforce a Game-Changer?
As mentioned, traditional deployment of agentic AI can be slow and expensive, let alone tricky to scale. Understandably, you may feel you don’t have the time or budget to spend on it.
Agentforce combats this obstacle by offering:
- Speed: Faster deployment of AI allows businesses like yours to test and refine AI agents in next-to-no time.
- Quality: Agentforce tests agentic AI as it’s setting it up, ensuring its agents are reliable and accurate when faced with real-world situations.
- Security: With its built-in compliance framework, you can trust that your agentic AI is operating ethically and legally with Agentforce.
- Scalability: If you’re venturing into agentic AI for the first time, you may want to start small and gradually expand the use of your agents. Agentforce makes it easy to scale your use of agentic AI in line with your needs.
How Businesses Can Use Agentforce
We’ve covered the benefits of Agentforce, but how exactly is it used? In a nutshell, Agentforce allows you to take the development of agentic AI into your own hands. It streamlines the deployment of AI by allowing quick testing, seamless integration of AI agents into Salesforce workflows, and the scaling of agentic AI across teams and departments.
One of the biggest benefits of Agentforce is its ability to integrate agentic AI into existing chatbots, like ChatGPT. These deep integrations help businesses deliver personalized, AI-driven customer service with minimal effort, making interactions more natural and efficient.
Gone are the days of waiting months to implement AI — with Agentforce, agents are poised and ready to enhance customer service, sales, marketing, and more.
The bottom line is that Agentforce helps you to stay ahead of your competitors and future-proof your business by providing faster, smarter, and more scalable AI solutions within Salesforce.
The Benefits of Autonomous Salesforce Agentic AI
Autonomous agentic AI applications, like Agentforce, provide a whole new level of support for businesses. One that’s always on. Say so long to AI that merely reacts to requests — Agentic AI can anticipate your needs to make workflows as smooth as possible and enhance efficiency across departments.
Perhaps the greatest benefit is its 24/7 availability. Rather than waiting for human intervention, AI agents can handle customer inquiries, troubleshoot technical issues, and automate HR tasks (like booking meetings for example) all by themselves. This constant support means response times are lower and customers are altogether more satisfied.
For employees, agentic AI means less time wasted on repetitive, mundane tasks. Take sales, for instance. AI agents can take over on qualifying leads, drafting personalized email responses, updating records, and setting appointments — allowing your employees to focus on sealing deals. The same can be said about other teams too: For example, AI could allow only complex issues to be deferred to customer service, or automate candidate screening and onboarding for HR.
To sum up, Salesforce agentic AI serves to make employees' lives easier, allowing them to work smarter, not harder. It drives efficiency, improves customer experiences, increases job satisfaction, and boosts productivity.
The Future of Agentic AI: Transforming Business and Customer Relationships
As if agentic AI isn’t impressive enough as it is, it has huge potential for the future. In fact, it’s set to redefine how businesses operate and connect with customers.
By handling tasks automatically, AI agents are helping businesses to stay one step ahead of their competition and boost profits. Instead of getting bogged down in repetitive tasks, teams can focus on innovative strategy and creativity — things AI cannot replace.
On the customer side, agentic AI is also breaking new ground by offering hyper-personalized experiences. Imagine contacting support and getting instant, contextual help. AI agents can anticipate customer needs before they even ask for support, bringing a whole new level of satisfaction. It’s not just about faster response times — it’s about creating deeper, more meaningful relationships between you and your customers.
Now, let’s look to the future. According to industry leaders, things are only going to get better, with superiors from companies like BCG and Infosys predicting that AI will transform workflows and unlock employee potential in the next 12 months.
Soon, Salesforce agentic AI could react to human emotions, making interactions feel more personal. It will become more adept at suggesting solutions before problems arise and be able to fine-tune marketing strategies in real time. The exciting thing is that agentic AI is able to learn and grow over time, meaning their decision-making can only improve.
As more organizations take on AI agents, we can expect to see new business models and partnerships emerge that make the most of AI’s unique capabilities. This global collaboration could drive exponential growth and create brand new opportunities for both businesses and consumers.
There are endless possibilities ahead.
How RAW Labs Help Businesses Benefit From Salesforce Agentic AI
With RAW, it couldn’t be simpler for you to make the most out of Salesforce agentic AI. Our Salesforce Case Management Starter lets businesses like yours manage customer support cases directly through chatbots like OpenAI GPT. This means that your teams can quickly build agents, create, update, and track cases using natural conversations with AI, saving time and improving efficiency.
With our Data API Integration services, we ensure that Salesforce works smoothly with your other business systems, making it even easier to use agentic AI to get real-time insights and automate tasks.
Reach out for a detailed discussion or a demo, and we’ll show you how these tools can help your team work faster, make better decisions, and improve customer service.
