The launch of OpenAI Presence has reignited the debate on the scope of business automation, especially regarding customer support teams and internal operations. This service, designed for large enterprises, allows the deployment of voice and chat conversational agents capable of resolving customer and employee requests, as well as executing actions on IT systems. Although OpenAI has announced that its own English-language phone support channel resolves 75% of issues without human intervention, analysts warn that this figure should not be taken as a universal benchmark. Integration with legacy systems, data fragmentation and compliance requirements can significantly reduce that percentage in other organizations.
From a technical perspective, Presence relies on OpenAI's language model and reasoning capabilities, but its true value lies in task-specific customization. Each deployment is configured for a specific process — billing, insurance claims or IT requests — limiting the agent's access only to the necessary knowledge and systems. This reduces security risks and facilitates governance. Additionally, the Codex tool monitors agent performance and suggests continuous improvements. In OpenAI's internal tests, these suggestions reduced handoffs to humans by 15 percentage points over ten days.
Several companies are already evaluating Presence in real-world contexts. Spanish bank BBVA is testing it for everyday banking support in Mexico, SoftBank is trialing it with Japanese-language interactions, and Australian insurer IAG is analyzing its ability to handle demand surges during severe weather events. These cases show that AI agent adoption is not homogeneous: each sector and region presents specific challenges in language, regulation and technological maturity.
The impact on employment is one of the hottest topics. Experts agree that the first effect will not be mass layoffs, but a slowdown in hiring. The most exposed roles are frontline support with repetitive, predictable tasks. However, as companies redesign their operations around AI-assisted workflows, broader restructuring may occur. Tulika Sheel, Senior Vice President at Kadence International, notes that human workers will focus on complex cases, escalations and relationship management, while AI handles routine inquiries.
For organizations, the real cost of Presence is not in API tokens, but in integration and governance. Connecting the agent to fragmented ERP, CRM and database systems requires significant development effort, as well as establishing access controls, audits and scaling policies. As Pareekh Jain, CEO of Pareekh Consulting, points out, the biggest expense in enterprise AI is often integration, not model consumption. Companies that already have a solid cloud infrastructure on AWS or Azure, and have implemented cybersecurity and BI solutions, will be better positioned to leverage agents like Presence.
In this context, having a technology partner that masters both artificial intelligence and system integration becomes critical. Q2BSTUDIO, as a software and technology development company, offers services that complement the adoption of AI agents. For example, creating custom software connects Presence with legacy systems, while cloud AWS/Azure solutions provide the scalable and secure infrastructure needed for deployment. Furthermore, cybersecurity is essential to protect data and automated actions, and BI/Power BI can monitor agent performance and generate audit reports. Process automation and AI implementation are areas where Q2BSTUDIO brings expertise to maximize return on investment.
The future of business automation is not just about whether AI can replace humans, but how organizations integrate these tools securely, scalably and ethically. Presence represents a step forward, but its success will depend on companies' ability to adapt processes, train staff and build strong governance. On this path, collaboration with experts in software development, cloud and cybersecurity will be a differentiating factor.
