Agentic AI for B2B Sales

There is a lot of talk about agentic AI workflows and AI Agents these days. To some, this might just seem like the latest flavor of something that will get tossed soon again, but there is real value behind the concept. This article is meant to demystify the term and explore how it can work in B2B sales.

To set the scene, we first need to define the term agentic AI, then I will show some examples outside of sales. Finally we will look into how agentic AI can be used to solve sales problems.

#Defining Agentic AI

In an AI context, “agentic” means having the capacity to autonomously choose goals, decide on actions, and adapt in real time. Instead of rigidly following fixed rules, an agentic system can draw from a set of known tools or strategies, pick the best approach for the situation, and adjust when conditions change.

Note that there is no set definition – there is convergence on what the term means but what is actually going on can differ quite a lot. What matters is that a system autonomously accomplishes a task – be that system labeled as agentic, Plumbus or Rick.

#How to Brew Coffee: Deterministic vs. Agentic Workflows

Let’s illustrate the concept by comparing it with what is called a deterministic or rule-based workflow using a real-life example you are likely familiar with: Imagine you want a machine that makes coffee.

Deterministic (Rule-Based) Workflow

• Check if you have coffee beans. If not, stop.
• Grind the beans.
• Boil water to a preset temperature.
• Brew coffee.
• Serve.

It follows a strict script: if something is missing, it simply fails.

Agentic Workflow

• Goal: “Brew a good cup of coffee.”
• Check if you have coffee beans.
  • If no beans, look for alternative tools or instructions: maybe it goes online and orders beans for future, or finds a nearby coffee pod.
• Check water temperature.
  • If your kettle isn’t working, choose a backup kettle.
• Taste or measure brew strength.
  • If it's too weak, automatically re-adjust settings for a stronger brew next time.

Here, the system still follows conditions (“if no beans, then do something else”) but it can flexibly select from predefined tools or steps to solve the problem rather than just stopping. This means the exact steps don’t need to be known in advance, let alone committed to upfront and that can be a huge benefit if getting things done is what you are primarily concerned with.

#Agentic AI in Action: Examples Outside of Sales

If you want to see other non-sales examples in action, I highly recommend that you try out v0.dev or bolt.new. In fact, why don’t you do that right now? You can create a free account and will be smarter in about 90 seconds (no affiliation with either company).

You can copy this to test and come back afterwards:

create a modern landing page with a button link to narratic.ai/blog/agentic-ai-for-b2b-sales

If you tried it out, the updates you saw on the chat is what is called an agentic workflow. It didn’t know what you would ask it to do and used at least four tools to create the result:

1. Plan what to do
2. Execute the plan
3. Check the result
4. Explain to you what it did

What you just experienced has changed building software for good. There is a long list of developer tools that work in that way and that substantially lowers the bar to build amazing things in a short amount of time – this weekend, for instance?

#Agentic AI for B2B Sales: Supercharge Your Revenue Engine

With all that knowledge under our belt, let’s turn to what you came here for: How the heck will these AI Agents help you get them revenue numbers up?

While good coffee might be a crucial ingredient, we continue with an problem that is a bit closer to the subject. How about this:

“Figure out what your top-performing sales reps do differently than the rest.”

Let’s walk through how that might look:

1. Create a strategy considering available resources: You could analyze meeting notes, call transcripts, emails, or CRM fields to understand the playing field. There’s no single “right” way to go about it—one agent might emphasize call transcripts, another might dive deep into CRM notes. The key is to have a game plan, while still staying open to unexpected angles.
2. Crunch the data: Based on your goals, the agentic system processes all that information, looking for patterns, best practices, or any other insights that could help you improve your sales process.
3. Present results: The AI can compile what it finds into a simple report, a bulleted list of action items, or even a refined pitch template. Think of it as creating a standard operating procedure (SOP) for your most effective sales moves, except that it can be re-created and adapted within a matter of seconds.
4. Iterate and Adapt: A big bonus here is that the AI can repeat this process as conditions change—no more dusty SOPs that become outdated the moment you finalize them and that you won’t be following anyway if you can. That doesn’t mean it can magically handle every situation (e.g. “sell this product” is just too vague), but with a bit of direction, it can save a ton of time and keep adapting to what’s actually happening in your sales cycle and gain compound interest with each step you take.

Yes, you could gather these insights by hand or cobble them together from a half-dozen spreadsheets. But how many hours (days? weeks?) are you willing to invest when you don’t even know the exact format you want from the data? Sales strategies are an iterative process that need constant tweaking, and the faster you see what’s working (or not), the quicker you can refine your approach. Speed combined with flexibility is the real power of going “agentic” with your Sales AI.

#Staying in Control: Boundaries and Guardrails

By design, agentic AI systems explore creative ways to achieve a goal. That’s great for uncovering hidden opportunities—until your agent decides to “increase revenue” by spamming or, worse, blackmailing current customers. Extreme? Yes. Impossible? Not necessarily, if there are no guardrails and the system has access to outward-facing systems.

To avoid any unintended consequences, it’s crucial to ensure humans stay in the loop for important, outward-facing actions. For instance, you might allow the AI to generate suggestions and insights on a rolling basis (like updating a deal risk score each Monday at 8 AM) but require explicit approval before sending customer-facing emails or implementing changes that affect real users. Unlike code that can be rolled back by pushing a button, relationships and reputations aren’t so easily fixed once the damage is done.

In short, agentic workflows thrive under clear guidelines:

• Define Acceptable Boundaries: Make sure the AI knows what’s off-limits. This can be as simple as “never send an email without human review” or as formal as a company policy on ethical sales and communication.
• Require Confirmation for ‘Write’ Operations: Even with repeated workflows, have a final approval step where a human checks that everything still aligns with your brand standards and ethical considerations.
• Monitor and Adjust: Just like iterating on sales data, you can (and should) iterate on your guardrails. If you see questionable outputs, update the rules so the AI doesn’t repeat them.

These measures let you harness the adaptability of agentic AI without losing sight of your company’s ethics, compliance requirements, and brand reputation.

#The Future is Bright: Embracing a New Era of B2B Sales

What we just discussed is just a single example of how a sales process can be enhanced using agentic AI workflows. Given their flexibility, the possibilities are literally endless.

While building our vision of a B2B Sales AI – Narratic AI – we’ve been amazed by what insights can be gained, time and time again. Given the right questions and some data to work with there are endless possibilities and we’ve seen astonishing results with our first users already.

#Conclusion

I hope that this shed some light on practical cases for agentic AI applications. We know that the buzz can be confusing, especially once the herds of LinkedIn influencers and SEO marketers hop on the train.

On that note: I just checked Google and was surprised that there wasn’t a “10 ways to use AI agents to create a successful business” article in February 2025 yet. Rest assured, it will come 😉

PS: We are currently preparing our public launch and we are working with selected companies to solve their revenue scaling issues. If you directly contribute to your companies’ revenue generation process and are looking to apply agentic AI to become more effective, feel free to connect with me on LinkedIn or check out our early access program for more information.