Table of Contents
- What is Agentive AI?
- Relevant Use Cases
- Trust or Distrust?
- Factors that generate distrust
- Factors that reinforce trust
- Salesforce: Trusted AI for a sustainable future
- A double layer of trust for intelligent agents
- Why is this double layer important?
- Beyond communication: certified processes from start to finish
- Conclusion
- Frequently Asked Questions
In recent years, artificial intelligence (AI) has ceased to be a futuristic concept and has become a key tool in the daily lives of companies and consumers. In this context, AI agents – also known as agentive AI –are positioned as one of the most interesting developments: systems capable of making decisions, learning from their environment and acting autonomously to meet specific objectives.
But with their growing prominence comes an essential question: do these agents generate trust or distrust among users? And what can companies do to ensure that the relationship between people and technology is based on transparency, security and real value?
What is Agentive AI?
Agentive AI refers to intelligent systems designed not only to respond to specific tasks, but to act proactively, autonomously and continuously according to defined objectives. These agents can perceive their environment, reason, make decisions and execute actions without constant human intervention.
Unlike traditional AI systems, which tend to be reactive, AI agents function more like active virtual assistants, able to anticipate needs, learn from experience and adapt to new contexts.
| Dimension | Reactive/Traditional AI | Agentive AI |
|---|---|---|
| Mode of Operation | Responds to specific inputs when queried | Acts proactively and continuously toward a defined goal |
| Autonomy | Low; requires human instruction for each task | High; perceives the environment, reasons, and acts without constant intervention |
| Learning | Offline training; does not learn from real-time operation | It can learn from each interaction and adapt to new contexts |
| Examples | FAQ chatbot, recommendation engine, email classifier | Autonomous customer service agent, proactive sales assistant, onboarding agent |
| Use Cases in Banking/Insurance | Credit scoring, fraud detection | Self-service onboarding, proactive renewals, end-to-end claims management |
| Regulatory Risk | Moderate, limited decisions | Higher; requires legal traceability for each independent action |
Relevant Use Cases
- Personalized customer care
AI agents can manage conversations across multiple channels, resolve queries, escalate complex cases and learn from each interaction to deliver an increasingly relevant experience. - Business process automation
From automatic mail sorting to reporting to inventory management, autonomous agents can make decisions that optimize operational efficiency. - Smart Sales and Marketing
Using predictive analytics, agents can suggest the best time to contact a customer, personalize offers, or identify conversion opportunities. They can also help large companies tailor direct marketing campaigns to achieve the best results. - Internal support in organizations
AI agents can assist employees in administrative tasks, offer technical support or help in the onboarding process of new team members. - 24 x7 availability which increases the operational resilience of organizations.
Trust or Distrust?
Despite their usefulness, AI agents also raise legitimate concerns:
- How transparent are they in their decisions?
- How is user data protected?
- What mechanisms are in place to correct errors or biases?
Confidence in AI is not an automatic outcome; it is built. And users today demand more than just efficiency: they want to understand how the technology that supports them works and have the assurance that their data is protected.
Factors that generate distrust
- Lack of transparency in automated decisions.
- Feeling of loss of control.
- Privacy and data misuse concerns.
- Inconsistent or poorly explainable results.
Factors that reinforce trust
- Explainable AI and decision traceability.
- Interfaces that allow human supervision.
- Clear data use policies.
- Ethical and regulatory frameworks respected.
Salesforce: Trusted AI for a sustainable future
In this scenario, Salesforce is positioned as a leader in the development of trusted AI agents thanks to its firm commitment to ethics, transparency and security at every layer of its solutions.
At the core of this proposition is the Einstein Trust Layer: an architecture that provides full control over data, ensuring privacy, compliance and auditability. This layer acts as an active defense so that enterprises can deploy generative AI and autonomous agents with peace of mind:
- Sensitive data is protected by design.
- Corporate governance is respected.
- Models are trained and adjusted without exposing confidential information.
Thanks to the Einstein Trust Layer, organizations can accelerate their innovation without compromising user trust or the integrity of their operations, thanks to its zero-retention policies, bias detection, and the anonymization of sensitive data in queries to various AI systems.
A double layer of trust for intelligent agents
On this journey toward more reliable AI, Unified Comms— a Salesforce partner and part of the MailComms Group—raises the bar by offering a dual layer of trust in the interaction between intelligent agents and end users.
Thanks to CertySign’s native integration with Salesforce, intelligent agents can not only automate and personalize communications but also send certified notifications with legal validity without leaving the Salesforce environment. This is achieved through a direct connection to CertySign, a platform certified and audited by a Qualified Trust Service Provider (QTSP) for certified electronic delivery, in accordance with the European eIDAS Regulation.

| Capacity | What it does | Value for the AI agent | Legal framework |
|---|---|---|---|
| Certified Communications from Salesforce | The agent sends certified notifications without leaving the Salesforce ecosystem | The agent’s autonomous actions have immediate legal standing | eIDAS — certified electronic delivery (QTSP) |
| Qualified Time Stamp | Every communication is recorded with a verifiable timestamp | Auditable traceability of every decision and action taken by the agent | eIDAS — Qualified Time Stamp |
| Electronic Signatures in Automated Processes | Contracts and agreements legally signed by the agent within Salesforce | Automation with full legal validity throughout the EU | eIDAS — Qualified electronic signature |
| Certified Consent Management | Consents obtained by the agent are tracked with evidence | Demonstrable GDPR compliance in automated processes | GDPR Art. 7 + eIDAS |
| Statutory Audit of Sensitive Processes | Every agent decision is accompanied by proof of integrity and date | Reduces the regulatory risk of autonomous automation | ENS, NIS2, DORA, depending on the sector |
Why is this double layer important?
- Intelligent and legally binding automation: agents not only act autonomously, but their actions can also have immediate legal backing (e.g. sending reliable notifications, digital contracts or certified confirmations).
- Full traceability and legal evidence: each certified communication is recorded with time stamp, proof of delivery and auditing mechanisms.
- Seamless and secure experience: everything happens without leaving the Salesforce ecosystem, maintaining operational agility without compromising compliance.
The role of the Trusted Service Provider is key in this process: it provides certainty, integrity and legal validity in an increasingly complex digital environment, functioning as the link that transforms technological efficiency into tangible trust.
With this joint solution, Salesforce and Unified Comms don’t just power artificial intelligence: they make it trusted, legally secure and aligned with the highest standards of digital trust.
Beyond communication: certified processes from start to finish
The Unified Comms legal trust layer can also be extended to many other key processes beyond automated communications:
- Qualified electronic signature in automated processes: contracts, quotes or agreements can be legally signed by AI agents within Salesforce.
- Automated legal notifications: from non-payment notices to contractual changes, agents can generate legally backed communications.
- Certified consent management: ideal for regulated environments such as healthcare, finance or telecommunications, where consents must be traceable.
- Validated digital onboarding: onboarding of customers or employees with certified proof of identity and acceptance of conditions.
- Statutory audit in sensitive processes: any decision of the agent may be accompanied by evidence of completeness, date and traceability.
This makes Salesforce, in combination with Unified Comms, an end-to-end trusted platform, where intelligent automation and certified legality work together to transform the way organizations operate in the digital environment.
Agile AI represents a revolution in the way we interact with technology, enabling a degree of automation and personalization never seen before. But its mass adoption will depend on our ability to make it reliable, transparent and secure.
Betting on Salesforce is betting on AI agents that are not only intelligent, but also reliable, ethical and aligned with the values of each organization. Because true innovation doesn’t just solve problems: it builds lasting relationships of trust.
Frequently Asked Questions
What is agent-based artificial intelligence, and how does it differ from traditional AI?
Agentive AI is a type of intelligent system designed to act proactively, autonomously, and continuously toward a defined goal, without the need for human instruction at every step. Unlike traditional or reactive AI—which responds to specific queries—an AI agent perceives its environment, reasons, makes decisions, and takes action autonomously. It can learn from each interaction and adapt to new contexts.
Why do AI agents inspire mistrust, and how can a company reduce it?
Mistrust of agentive AI stems primarily from a lack of transparency in automated decisions, a sense of loss of control, privacy concerns, and inconsistent results. To reduce this mistrust, companies must implement explainable AI with decision traceability, interfaces that allow for human oversight, clear data usage policies, and ethical and regulatory frameworks that are adhered to. Certifying the agent’s actions through timestamps and legal evidence provides an additional layer of trust.
What is Salesforce's Einstein Trust Layer?
Einstein Trust Layer is Salesforce’s security and data governance architecture for generative AI and autonomous agents. It provides complete control over data through zero-retention policies (data is not stored in AI models), bias detection, anonymization of sensitive data, and built-in regulatory compliance. It enables organizations to deploy AI agents with the assurance that sensitive data is protected by design.
How does CertySign integrate with Salesforce to give AI agents legal validity?
CertySign, a MailComms Group platform certified as a QTSP (Qualified Trust Service Provider) under eIDAS, integrates natively with Salesforce through Unified Comms. This allows Salesforce’s intelligent agents to send certified communications—certified notifications, digital contracts, and legally binding confirmations—directly from the Salesforce ecosystem, without leaving the environment or losing traceability. Each communication is recorded with a qualified timestamp and proof of delivery.
What regulations apply to AI agents in the financial and insurance sectors?
The main regulatory frameworks are: DORA (Digital Operational Resilience Act), which requires operational resilience and traceability in the financial sector’s ICT systems; NIS2, which mandates security controls in critical sectors; the EU AI Regulation (AI Act), which classifies AI systems by risk level and imposes transparency and human oversight requirements; and the GDPR, which regulates the processing of personal data in automated processes. Actions taken by AI agents that affect customers must be traceable, auditable, and verifiable.
