AI agents are trendy, but what does this really mean for companies in the near future?

Invoices are automatically processed, customer interactions are personalized by self-managed AI-powered support agents, and data-controlled insights inspire any business decision. AI agents will become a reality, and the market is expected to grow to 45% CAGR in the next five years, which underlines the immense potential and growing necessity of these technologies.

The quick market growth of AI agents is probably associated with the technology that is a product of “technological jump”. In this case, the development speed in emerging countries means to skip intermediate stages with intermediate technology. For example, Brazil switched directly from bar to immediate digital payments, whereby PIX dealt with the widespread card acceptance.

With regard to the development of business technology, many companies from basic tools such as Excel could pass directly to the automation of AI agents and skip the SaaS implementation phase. This exaggeration creates the possibility that companies benefit from competitive advantages that are available through a faster introduction of AI solutions.

How do you work with intelligent AI agents how to work in storm, what are the frequent misunderstandings and what are two of the biggest applications in business? Let us immerse yourself.

What are AI agents (and what are they not)?

Many companies are perfectly positioned to use AI agents due to their advanced cycle. This means that you collect and process information from your environment and autonomously evaluate and prioritize the actions based on the problem or goal. AI agents then integrate into business and platforms to do their tasks. Even better, you learn continuously from previous interactions and improve efficiency and effectiveness over time.

However, all new technologies are associated with a variety of misunderstandings, and AI agents are no different.

First, they are not AI chatbots. While AI chatbots often process customer support and simple sales transactions, they usually rely on preprogrammed answers with natural language processing for basic understanding.

In the meantime, AI agents carry out more complex tasks, including decision-making, process automation and workflow optimization. They use advanced AI techniques such as machine learning, learning strength and predictive analyzes to adapt, to learn from every interaction and make decisions without human intervention.

While AI agents can act autonomously, people at the top will always be an essential part of success and AI security. The idea is that improvements in the AI ​​will contribute to expanding human potential and preventing time waste in secular, repetitive tasks. They are not people or AI; They are people and AI companies have to use both AI and humans to achieve the best results.

Where companies see the biggest victories: customer service

Salesforce data found that two out of three consumers are frustrated if customer service cannot solve their problems immediately.

Some of the most common problems that customer service staff will be used are are order problems, billing and payment problems as well as product or service support. AI agents can meet these queries because they enable their generative AI neural paths to understand, sort and prioritize the problem, access customer data and business protocols in real time and to escalate the request for the attention of humans if necessary.

In this way, companies can avoid delays due to human bottlenecks, improving the service speed and improving customer satisfaction.

In fact, Gartner predicts that 80% of customer service will use the generative AI technology in any form by the end of the year to improve the productivity and customer experience of the agents.

Where companies see the biggest victories: sales and lead generation

Docusign 2024's digital mature report found that workers spend 12 hours a week for low value tasks. Therefore, 21% of people stated that they left their work. If companies waste the time of their qualified workers with a high volume of repeating tasks, it could be time to use AI agents.

For example, if an online retailer, a member of the sales team does the same task every day when collecting sales information from the day before and manually creates a report, this is not a clever ROI how the employee spends its time. And it is unlikely that job satisfaction for the employee will also increase for the employee.

However, an AI agent could integrate into the retail management system and observe the data collected from the past day in business and online by structuring the data into a standardized report and acting and sharing the report by automatically creating and sharing.

In addition, the research showed that sales employees spent 71% of their time for unsold tasks, which makes it difficult to combine with prospects. A company is based on finding and storing customers. However, if strong leads slide through their fingers due to understaffed or non -existent strategies, AI agents could be ideal.

AI agents can automate the funnel of the lead generation with an Auto-lead rating system. This is done by analyzing various prospect data points such as website visits and e -mail interactions and assigns lead -scores based on your behavior and conversion. Sales teams can then focus on potential customers with the highest conversion rates, increase efficiency and reduce costs.

The Boston Consulting Group stated that in one case “a biopharma company AI -agent used for the lead production, which reduces the cycle time by 25% and the time efficiency for the elaboration of clinical study reports was achieved”.

Although AI agents can be the new children on the block, it is clear that they change the way people do business. By implementing a comprehensive business strategy, AI agents can help employees and companies to improve efficiency and to promote measurable improvements in business performance.

Article by Roberto Peñacastro, CEO and co -founder of Leadsales