It’s only been a few years since AI tools entered the business landscape, but it’s already difficult to imagine running a company without them. That’s especially true for SMB owners. AI agents for small businesses help them punch above their weight and compete with large companies that have far more resources. 

SMB owners have discovered the value of AI in a variety of use cases, including inventory management, automating billing, invoicing, and financial reporting, customer support, marketing, and sales and lead generation. Gradually, small business owners are overcoming their hesitation about the new technology, and embracing the benefits it brings. 

But innovation never stands still. Now there’s a new type of AI tool that can power even more advantages for small businesses: agentic AI. Agentic AI is more autonomous than robotic AI and more active than generative AI (GenAI). It can understand your goals, analyze data, and take actions that support your objectives. 

In this article, we’ll explain all you need to know about agentic AI, explore its benefits and use cases, and share some agentic AI examples that help you picture how it would fit into your own business ecosystem. 

What is Agentic AI?

Agentic AI is the smart AI system of your dreams. It builds on all the types of AI that already exist, and puts it all together in an autonomous package. Agentic AI platforms can understand your vision and set goals, make decisions, and adapt to changing circumstances like a (smart) human agent. They don’t need step-by-step instructions, and they are flexible enough to dynamically solve new problems independently. 

How does Agentic AI work?

Agentic AI systems involve different technologies and inputs in a four-step process: Perceive, Reason, Act, and Learn. Perceive means that AI agents collect data from a range of sources, like sensors, databases, and your business management platform. They use machine learning  (ML) to identify the meaningful elements in the data, like recognizing an object or understanding customer intent. 

Reason involves a language learning model (LLM) which works out which tasks need to be carried out and finds solutions to challenges. It gives “instructions” to specific AI models that carry out particular functions, like generating content or recommending next steps. It uses a process called retrieval-augmented generation (RAG) to produce accurate and relevant decisions. 

Act means that the agentic AI platform carries out the tasks. It connects with external tools and platforms, like a customer service chatbot or a CRM, to complete the work. 

Finally, Learn means the AI continuously monitors the results to improve its decision-making. It draws on data about its interactions to generate feedback for itself, so it can enhance models and efficiency for next time. 

Agentic AI vs. Generative AI

You might be wondering what makes Agentic AI different from GenAI. Well, there are a few key differences. GenAI is all about creating content, whether that’s text, images, music, or code. Agentic AI is about making decisions and carrying them out. If GenAI produces content, agentic AI produces actions. 

GenAI tools don’t actually understand the content that they generate. They react to your prompt and predict patterns, in a very sophisticated way. Agentic AI understands the information and proactively decides what to do next. Agentic AI is action-oriented, dynamic, and tackles complex multi-step issues, while GenAI is content-oriented, static, and deals with narrow tasks. 

But agentic AI and GenAI work very well together. GenAI can turn data into insights that are easy to read, and agentic AI can use those insights to make smart decisions. Agentic AI can use GenAI content to resolve challenges. For example, an agentic AI customer support system could work out what the real pain point is and decide how to reply, using personalized, GenAI-generated responses. 

What are the benefits of Agentic AI for SMBs?

Because agentic AI is better at cognitive reasoning, it’s extremely good at finding the most relevant data, wherever it’s located, and quick to learn your brand values. This results in much better strategic decision-making that’s grounded in data and aligned with your brand and your goals. 

With this kind of reasoning power in your corner, you can save time and ramp up productivity. Agentic AI can take over complex tasks that previously couldn’t be automated, freeing up your time to focus on creative problem-solving and relationship-building. Greater efficiency also reduces costs and increases profitability 

At the same time, agentic AI brings more ways to improve customer experience (CX). The system can resolve queries faster and more effectively than today’s AI-based chatbots, and do a better job of understanding intent and predicting concerns. Agentic AI can also refine business systems like logistics and supply chain, to reduce friction and disruption. 

Best Agentic AI use cases

Let’s move on to consider what is a real use case of Agentic AI. There are so many ways that you can leverage agentic AI to help your business, but here are the use cases that deliver the most value for small businesses. 

Receptionist/Answering Service

Agentic AI can deliver personalized, smart, and fast resolution for even complex customer queries, going beyond FAQs and automated responses. It can effectively triage callers, patients, or clients so that the most urgent cases are addressed first, and decipher customer intent and anxieties more accurately than existing chatbots. 

Agentic AI can also proactively improve CX by reaching out to customers. For example, it could notice that someone’s delivery is going to be delayed, get in touch to inform them in advance, and offer a discount as an apology. 

Marketing & Content Creation

Agentic AI can transform marketing campaigns for greater ROI and increased revenue. It could track and compare results on different channels, identify the best times to post on social media, and develop strategies for ad campaigns.  

You could use agentic AI to run and refine an email marketing campaign, for example. It would generate email content according to your campaign objectives, send the emails, monitor open and click-through rates, and adjust the content. 

Financial Management

An agentic AI system can manage financial tasks like bookkeeping, expense tracking, invoicing, and cash flow, with minimal human oversight. The system can proactively detect anomalies, suggest cost-saving measures, and automate tax compliance, reducing the risk of errors and fraud.

Because agentic AI continuously learns from financial data, it can also generate real-time insights and strategic recommendations for lowering expenses and optimizing revenue. This is particularly important for small businesses that don’t usually have a dedicated finance team. 

Team collaboration

Collaboration is vital for SMBs with lean teams, and agentic AI can turbocharge this too. It can automate key processes like transcribing meetings, extracting key insights, and generating action items for follow-up, and even assign tasks to the right team members based on workload and expertise. 

Agentic systems can onboard new employees with only minimal human input, by providing personalized training materials, anticipating a new hire’s concerns, and answering questions in real time. They can also enhance workflows by streamlining task management, researching relevant information, and suggesting optimized processes, thereby increasing efficiency and productivity. 

Agentic AI is set to revolutionize the SMB landscape 

Agentic AI offers a lot of promise for small business owners. Smart AI agents for small businesses do more than automate complex tasks and free business owners and SMB employees for tasks that require human warmth and empathy (although they do that too). They proactively optimize processes and workflows, support better strategic decision-making, and expand revenue streams and profits to drive SMB growth like never before.

    Tags: AI