What is the difference between chatbots and AI agents? While we are still digesting the word “LLM” we find ourselves faced with yet another buzzword and a new technology to implement.
In his recent speech at CES 2025, Nvidia CEO Jensen Huang defined the “next giant AI application” as the next big application of AI, predicting it will represent a trillion-dollar opportunity. Huang described AI agents as a “digital workforce” capable of revolutionizing various industries, thanks to their autonomy that allows companies to operate without human intervention.
But what are AI Agents? What is the difference between chatbots and AI agents? We talked about it during the recent Athics webinar “Revolution AI Agents” with Riccardo Petricca – Innovation Manager & Cybersecurity Expert and Professor of Artificial Intelligence at the Pontifical Antonianum University, Luca Sambucci – Industry Board Member of the AIxIA (Italian Association of Artificial Intelligence), Pierluigi Sandonnini – Journalist and Senior Web Editor Nextwork360.
What are AI agents?
As Luca Sambucci explains: “An AI Agent is an autonomous system capable of receiving inputs, making decisions and acting accordingly. To do this, it must interact with other business systems or other agents.
At the heart of modern AI agents is an advanced LLM capable of reasoning. When we give it memory to handle intermediate steps, its capabilities expand dramatically: it can send emails, edit documents, access databases, and update customer information after each interaction.
An AI agent can even autonomously report an opportunity to the sales office or take strategic initiatives, going well beyond the simple question-answer interaction typical of a chatbot. AI agents don’t just respond, they act. This is why we talk about “artificial intelligence that does things”.
The difference between chatbots and AI agents: When our AI Agents were just “simple” chatbots
To explain the difference between chatbots and AI agents, let’s take a step back. Before the term “AI agents” came into common use, some advanced chatbots already possessed characteristics now attributed to AI agents.
The Gea presales chatbot, developed with Crafter.ai for Sorgenia and in production since 2020, in addition to taking charge of and independently managing customer requests, carries out operational activities such as retrieving customer data, sending it to CRM, calculating estimates and interacting with a human operator when necessary.
As explained by Luca Sambucci, the further step taken by technology is in the capacity for autonomy and reasoning made possible by the LLM and the architecture that is built around it.
The role of chatbots and AI agents in companies
As reported by Riccardo Petricca, there is already no shortage of results in the organizational field: Microsoft recorded a 9.4% increase in sales thanks to the use of AI agents in the sales team and 25% more agreements thanks to a personalized AI buyer assistance agent.
Gartner predicts that 15% of business decisions will be made by AI agents in 2028.
According to data shared by Pierluigi Sandonnini, large companies such as Microsoft, Johnson & Johnson, eBay and Moody’s are already integrating AI agents into their processes:
- Johnson & Johnson uses AI agents to speed drug discovery.
- Moody’s has developed a multi-agent ecosystem to perform advanced financial analysis
- eBay employs AI agents to generate code and create marketing campaigns.
These examples demonstrate the difference between chatbots and AI agents, where the latter lead to improved efficiency and productivity, reducing working time and optimizing decision-making processes.
Challenges and risks: security and bias
Deploying AI agents is not risk-free. Large companies have already understood the difference between chatbots and AI agents, they know well what to do and have the budget to move. The most innovative companies, or perhaps the most curious employees, “dive in” and start experimenting. However, all this exposes us to the risk of neglecting even the most banal security aspects, such as those linked to uploading confidential documents to ChatGPT.
Can we really download OpenAI and start creating our own personal AI agent or is there a need for some forethought?
As specified by Riccardo Petricca, the main critical issues emerge:
Privacy and data security: Improper use of systems like OpenAI can expose companies to leaks of confidential information.
Cyber attacks: Techniques such as prompt injection can manipulate AI into generating unwanted output.
Bias in AI models: AI models are not error-free and can reflect biases present in the data with which they were trained.
To mitigate these issues, companies must adopt AI governance strategies, invest in staff training and rely on reliable vendors that ensure a controlled environment.
According to Luca Sambucci, AI represents a new attack surface, introducing completely new threats. These include prompt injection, a semantics-based attack that can trick an LLM into revealing sensitive information it shouldn’t share.
One of the most critical issues that have emerged with the adoption of ChatGPT is the tendency of employees to upload sensitive company documents without due precautions. Security teams are only now starting to address the problem, but there is a huge skills gap, and time to fill it is limited.
Addressing these challenges requires a change of mentality and collaboration with reliable partners, capable of guaranteeing safety and protection in an ever-changing landscape.
The impact on work and the need for new skills
According to data shared by Pierluigi Sandonnini, 50% of the workforce will have to be retrained by 2025 (World Economic Forum). Gartner predicts that by 2027, 80% of workers will need reskilling to remain competitive.
According to Riccardo Petricca, the path towards effective reskilling is full of obstacles: the skills required are increasingly transversal, ranging from AI literacy to critical thinking, up to understanding the limits, biases and risks of technology.
Universities are already responding to this challenge by introducing specific courses to prepare new generations for emerging professions. Gen Z and Gen Alpha are redefining the approach to learning: 60% of students prefer STEM courses with AI modules, and over 45% participate in AI for Good projects with a focus on sustainability.
According to Luca Sambucci, there is a growing fear that chatbots and AI agents may reduce the number of jobs, but the reality is more complex: some roles will disappear, others will grow. The advent of AI Agents is accelerating automation, making clear the need for constant retraining.
Many workers are not ready to get back on the books, and the real question is: where will these new jobs arise and who will fill them? Companies must promote this transformation, facilitating the acquisition of new skills and encouraging the flexibility that new technologies impose on us.
ConclusionS
In conclusion, chatbots and AI agents represents a significant transformation. These agents, equipped with decision-making autonomy and advanced interaction capabilities, are revolutionizing various industries, offering companies powerful tools to improve operational efficiency and customer satisfaction.
However, the widespread adoption of AI agents also brings significant challenges. Companies face issues related to data security, privacy and potential biases in AI models. It is essential to implement AI governance strategies, invest in staff training and collaborate with trusted partners to ensure the ethical and safe use of these technologies.
Furthermore, integrating AI agents into the work context requires significant reskilling of the workforce. According to the World Economic Forum, by 2025, 50% of workers will need new skills to adapt to the changes brought about by automation and artificial intelligence. Companies must therefore promote continuous training programs to prepare employees for new challenges and opportunities.
In summary, while AI agents offer extraordinary opportunities to innovate and optimize business processes, it is critical to carefully address the ethical, security and training implications associated with their implementation. Only through a balanced and conscious approach will it be possible to fully exploit the potential of this technological revolution.
