ChatGPT becomes a superapp: AI agents and Italian SMEs

The statement that changes the rules: «Chat is dead»

In early June 2026, OpenAI internally circulated an unequivocal communication. The phrase circulating among teams is direct: «chat is dead» . This is not a marketing stunt. It is the operational premise for a deep restructuring of the company's best-known product.

According to reports by The Decoder , OpenAI is planning to transform ChatGPT into a superapp to all intents and purposes. The new product will bundle coding tools, autonomous AI agents and partner apps like Canva and Booking.com. Therefore, the ask-and-answer paradigm is being replaced by a continuous automation ecosystem.

This announcement doesn't happen in a vacuum. In fact, it's part of a broader trend where major tech players—from Google with Gemini to Microsoft with Copilot—are moving toward agentic architectures. Even so, OpenAI is the first to explicitly call time of death on the chat model as the go-to approach.

From conversation to action: what changes in the architecture

An AI agent doesn't respond: acts . This distinction is technical, but its consequences are very practical. A traditional chatbot waits for input, processes a reply, and stops. An agent, on the other hand, receives a goal and pursues it through a sequence of autonomous actions.

For instance, an agent can open a doc, pull data from it, match it up against an external database, whip up a report, and email it off—all without a human needing to step in halfway through. Plus, it can team up with third-party APIs, run code, browse web interfaces, and make split-second decisions along the way.

Rumor has it that ChatGPT's new architecture is built for precisely this capability. Integrated partner apps—like Canva for creating visuals and Booking.com for managing trips—turn into nodes in an automation network. As a result, users no longer have to manually juggle every step between different tools.

To delve into the technical foundations of AI agents, the MIT Technology Review offers an updated overview of the evolution of these systems in the enterprise context.

Immediate impact on SMEs: three concrete scenarios

For Italian B2B and retail SMEs, the shift to the agent superapp opens up operational scenarios that deserve attention. This is not futurology. Some of these capabilities are already available in embryonic form and will become mainstream by the end of 2026.

• Customer service automation: an agent can handle first-tier requests, consult the CRM, update tickets and reply via email or chat without supervision. Therefore, the human team focuses on complex cases.
• Coordinated content production: integration with Canva and editorial tools allows for semi-automatic generation of visual and textual campaigns. We at SHM Studio we are already evaluating how these flows integrate with our clients' SEO strategy.
• Operational management and reporting: agents connected to ERPs and spreadsheets can extract KPIs, generate dashboards and send regular briefings to managers. As a result, the time spent on data collection is drastically reduced.

In all three cases, the assumption is that business processes are structured well enough to be delegated. This is often the real bottleneck for Italian SMEs.

The work still in progress: risks and limits not to be underestimated

It would be incorrect to present this transition as friction-free. In fact, agentic architecture introduces new complexities that the chat model didn't have.

The first risk is action supervision . An agent acting independently can make mistakes with a ripple effect. For example, a wrong action on a billing system can cause damage that is hard to track. Therefore, agent governance — who can do what, with what limits — becomes a business priority, not just a technical one.

The second risk concerns the dependence on closed ecosystems . If ChatGPT becomes the central automation platform, SMEs risk significant lock-in. According to an analysis by Gartner , diversifying tech stacks remains a priority for companies wanting to maintain strategic flexibility.

Finally, there is the issue of output quality . Current agents are powerful but not infallible. Despite this, many companies tend to overestimate the reliability of these systems in the early stages of adoption. A controlled pilot phase is always recommended before scaling up.

What nobody is saying: the real shift is organizational

Public debate focuses on technology. However, the most profound change the agency superapp introduces is organizational . Companies that effectively adopt AI agents won't be the ones with the best tools, but the ones with the clearest processes.

An agent can only automate what is defined. If a process exists only in one person's head, it cannot be automated. Therefore, true preparation for the age of agents starts with mapping and documenting existing operational workflows.

Similarly, internal skills must evolve. It is not about training everyone to code agents. It is about developing the ability to design objectives clear and verifiable — what is called in literature prompt engineering advanced or, more precisely, task decomposition .

Italian SMEs that have already started paths of AI adoption with SHM Studio are in a better position. They have already tackled the fundamental questions: what data is available, which processes are repeatable, where human judgment is still needed.

What to do now: strategic guidance for SMEs

OpenAI's roadmap does not have a definitive public release date. However, signs indicate that the first advanced agency features will be available by the end of 2026. Therefore, the time to prepare is now, not when the product is already on the market.

Some concrete actions that SMEs can start right away:

• Audit of repetitive processes: identify the low-value tasks that take up the most time for operational teams. These are the top candidates for agentic automation.
• Technology stack evaluation: check which tools already in use (CRM, ERP, e-commerce platforms) have open APIs. Agents work better in connected ecosystems.
• Controlled experimentation: start a pilot project on a non-critical process. This allows gaining experience without high operational risks.
• Internal training: educate teams on the difference between rule-based automation and agentic automation. Realistic expectations reduce post-adoption disappointment.

For SMEs operating in B2B, integration with tools such as LinkedIn Ads and Google Ads will benefit from agents capable of optimizing campaigns in a more granular and continuous way.

Outlook: 2027 as a year of consolidation

The transition from ChatGPT-chatbot to ChatGPT-superapp won't happen overnight. Therefore, SMBs have a reasonable window of time to adapt. However, those who start today will have a significant cumulative advantage over those who wait.

Projections for 2027-2028 indicate that AI agents will become standard components of the corporate operational stack, much like CRMs did in the 2000s. According to Harvard Business Review , organizations that integrate AI into core processes are already showing productivity increases of over 20% compared to competitors that do not.

We at SHM Studio we guide Italian SMEs on this journey. From digital marketing strategy to the AI adoption , right up to the organic visibility and to the web development : each service is rethought as part of an increasingly agency-focused ecosystem.

For a direct comparison of your company's specific opportunities, you can contact our team . Or explore the SHM Studio blog for continuous insights on AI, automation, and digital strategy.