Agentic AI in business: from OpenAI research to practice

The context: OpenAI captures accelerating adoption

Last August, OpenAI published a detailed study on how businesses are really putting AI to work. The paper, available directly on the official OpenAI website , analyzes the use of tools like ChatGPT Enterprise and Codex in structured business contexts. The results are significant. It is no longer about isolated experimentation, but systematic integration into core processes.

The very title of the report is revealing: From assistance to execution . This formula sums up a major qualitative leap. AI tools no longer just act as assistants that reply to prompts. Instead, they run sequences of actions, hook into external systems, and wrap up complex tasks on their own. This is the realm of Agentic AIs .

In particular, the research identifies a group of companies defined as frontier firms . These organizations have moved past the pilot phase. As a result, they are already reaping measurable competitive benefits in terms of productivity, decision-making speed, and lower operating costs.

The numbers that matter: what the research really says

Some research findings deserve special attention. First of all, it turns out that the most advanced companies don't just use AI for individual tasks. Instead, they have integrated it into shared workflows across different teams. This implies structured governance, not spontaneous and fragmented use.

Plus, the rollout of Codex—OpenAI's code-writing tool—shows that automation is creeping into tech roles too. It is not just about marketing or customer support anymore. So, companies that keep AI locked in a single department risk missing out on the big-picture perks of cross-functional integration.

Another relevant data point concerns the learning speed. The frontier firms they iterate faster. They experiment, measure, correct, and scale in much shorter times than average. The gap is not just operational: it's economic.

Finally, research shows that the main hurdle isn't tech. Internal skills, change management processes, and company culture drive the pace of adoption. This is super relevant for the Italian market.

Strategic reading: what it means for Italian businesses

The Italian market has specific characteristics. SMEs are the backbone of the economy, but they often have limited IT resources. Similarly, the mid-market struggles to build internal AI teams with the necessary skills. However, this does not mean that the adoption of agentic AI is out of reach.

On the contrary, accessible paths do exist. Tools like ChatGPT Enterprise are designed to integrate with existing systems via APIs. Therefore, there is no need to rebuild your tech stack from scratch. It is enough to spot high-volume, low-complexity processes—the ones that happen over and over and follow clear-cut rules.

In digital marketing, for instance, agentic AI can handle campaign planning and optimization, generating and testing creative variants, performance monitoring, and automated reporting. We at SHM Studio we are already integrating agentic logic into some workflows for our clients, with measurable results on execution speed and output quality.

Furthermore, the issue of AI consulting is becoming a key topic in chats with marketing managers. It is not about replacing the human team, but about boosting their operational firepower. So, the real competitive edge doesn't come from AI itself, but from the ability to orchestrate AI and people smoothly.

Agentic AIs in digital marketing: concrete use cases

It is helpful to get down to specifics. Agentic AIs find immediate application in various areas of digital marketing. In particular, three areas show the highest potential for medium-sized Italian companies.

• Paid campaigns: an AI agent can monitor the performance of google ads campaigns in real time, identify anomalies and suggest — or execute — budget and targeting adjustments. This cuts reaction time from days to minutes.
• Content and SEO: agents can analyze content gaps, plan an editorial calendar, generate drafts optimized for SEO and monitor positioning. The workflow of SEO copywriting becomes faster and more scalable.
• B2B lead generation: In the field of Linkedin , agents can segment audiences, personalize messages, and qualify leads automatically. This is especially relevant for B2B companies with long sales cycles.

Similarly, in e-commerce and retail, agentic AIs are demonstrating interesting capabilities in personalizing the user experience and optimizing product listings. The ROI is measurable and not theoretical.

The widening gap: why timing is critical

One of the most concerning aspects of OpenAI's research involves the speed at which a structural gap is forming. The frontier firms they aren't just running faster. They are building advantages that will become increasingly hard to bridge over time.

This phenomenon is known in literature as compounding advantage . Each learning cycle generates better data, which feeds more accurate models, which produce higher quality output. Those who start earlier accumulate a non-linearly growing advantage.

Even so, many Italian companies are still playing the wait-and-see game. The reasons are totally understandable: rule uncertainty, lack of in-house skills, and fear of making the wrong investments. Still, waiting comes with a price tag. Every month that goes by without a clear AI plan is a month where faster competitors pull further ahead.

What nobody says: the problem isn’t the AI, it’s the process

There's one thing that's often missing from the public debate on corporate AI. No matter how advanced it is, tech doesn't work in an organizational vacuum. An AI agent is only effective if the processes it needs to automate are already documented, measurable, and repeatable.

So, before investing in agentic tools, you need to do some process mapping work. Which workflows repeat frequently? Which ones have clear rules and defined outputs? Which ones cause bottlenecks? This preliminary analysis is often underestimated, but it is crucial for a successful implementation.

We at SHM Studio we stand right beside clients during this phase. First you define the strategy and map the processes, then you pick the tool. Not the other way around. This approach cuts the risk of misdirected investments and speeds up time-to-value. Anyone interested in exploring these possibilities can contact us directly for an initial assessment.

Operational implications: where to start

For a marketing or digital manager wanting to start structuring a path toward agentic AI, there are a few concrete priorities to consider.

• Audit of repetitive processes: identify the high-volume tasks your team manually performs each week. These are the ideal candidates for your first automation.
• Tool evaluation: ChatGPT Enterprise, Copilot for Microsoft 365, and vertical solutions are evolving fast. It's a good idea to compare them based on your company's specific use cases rather than generic features.
• Internal training: AI adoption requires a change in mindset even before tools. Investing in team training is a necessary condition, not optional.
• Success metrics: define clear KPIs before starting. Time saved, output quality, error rate, team satisfaction. Without metrics, it is not possible to evaluate ROI.

Furthermore, it's important not to isolate the AI initiative in a separate project. Instead, it should be integrated into the digital marketing strategy overall. Only in this way does it generate systemic value rather than remaining an isolated experiment. To explore the possibilities related to web development and to the integration of AI tools in corporate websites and platforms, you can explore our dedicated services.

In short, OpenAI's research doesn't describe a distant future. It describes a present that some businesses are already experiencing. The time to build a structured AI strategy is now. Italian companies that act methodically over the coming months will have a real and measurable advantage over those who keep waiting. To stay updated on these topics, you can follow our Blog dedicated to digital marketing and technological innovation.