Generative Artificial Intelligence (GenAI) is here to stay, and more companies are exploring its potential. However, the excitement surrounding this technology often clashes with an undeniable reality: without a clear governance framework, the use of GenAI can lead to serious business risks. From privacy and security issues to model biases or poorly controlled technological dependencies, there’s a lot at stake.
According to Analyticae’s CEO, Rocío González “I’ve been working with data for a long time, helping companies transform their strategies through analytics. And if there’s one thing I’ve learned, it’s that AI cannot be a “loose experiment” within a company“. Plus, as she adds, its implementation must be structured and aligned with strategic objectives to ensure responsible and effective use.
What are AI agents and how can they help your business?
Artificial Intelligence (AI) is no longer a futuristic concept or something exclusive to large corporations. Today, medium and small businesses can also harness its potential to improve processes, reduce costs, and make better decisions. One of the most relevant advances in this field is AI agents, and we want to share with you why they are key to the future of any business.
But what is an AI agent? It’s a software program designed to interact with its environment, collect data, and perform tasks autonomously to achieve specific goals. While humans define those goals, the agent makes decisions and chooses the most appropriate actions without the need for constant supervision.
A typical example is virtual customer service assistants. An AI agent can interact with customers, answer questions, search databases, and offer solutions without human intervention. If it detects that a query requires more specialized attention, it automatically transfers it to a human operator. This type of automation not only improves efficiency but also enhances the customer experience.
How do AI agents work?
To understand their usefulness, it’s important to know their key components:
- Architecture: This is the foundation on which the agent operates—whether it’s a chatbot, cloud-based software, or a system embedded in physical devices.
- Information processing: It gathers data from the environment (conversations, sensors, databases) and analyzes it to generate intelligent responses or actions.
- Task automation: It plans, executes, and adjusts tasks based on the data it receives.
- Continuous learning: Some agents use machine learning to improve their responses over time, adapting to new situations.
Why should medium and small businesses adopt AI agents?
AI is no longer a luxury reserved for large corporations. Today, companies of all sizes can implement it to optimize different areas of their business. It’s actually recommended, since AI agents can improve productivity, reduce costs, and help scalability. Here’s how:
- Increased productivity: Delegating repetitive tasks to an AI agent allows your team to focus on strategic activities.
- Cost reduction: Automating processes reduces the margin of error and lowers operational costs.
- Smarter decisions: An AI agent analyzes real-time information to help you make data-driven decisions instead of relying solely on intuition.
- Better customer experience: Fast, personalized, and 24/7 service without the need to expand your human team.
- Scalability: As your business grows, AI adapts without the need for significant additional investment.
Some practical examples are:
- Smart chatbots that handle customer inquiries without human involvement.
- Recommendation systems that personalize product or service offerings based on user behavior.
- Inventory optimization by analyzing demand and anticipating purchasing patterns.
- Marketing automation, sending personalized messages and analyzing results in real time.
Technology without control is not innovation–it’s a risk
However, in Rocío’s experience, companies that achieve real impact with GenAI are not the ones that simply implement it but those that govern it intelligently. Without a solid framework, AI can create more problems than benefits. It’s only through a clear strategy that it becomes a tool capable of driving growth, efficiency, and differentiation.
If your company is exploring the use of GenAI, her advice is clear: invest time in governance before scaling its use to ensure it truly adds value rather than becoming a liability.
Does your organization already have a GenAI governance framework? What challenges have you faced in its implementation?
If you want to know more about the company, check out Analyticae, data science and big data specialists!
