What is really happening in the world (and what it means for Italian tourism)
Introduction
Over the past three years, artificial intelligence has moved from being an emerging technology to becoming a true engine of transformation for businesses. If in 2023 the conversation was mostly about chatbots and conversational assistants, by 2026 the landscape has changed dramatically: today AI no longer just responds — it acts.
Autonomous systems capable of planning activities, analyzing complex data, and automating processes are redefining how companies operate. And this is true for tourism as well.
For those managing a destination, a tour operator, or a tourism platform, understanding where artificial intelligence is heading is no longer a technological curiosity — it is a strategic capability.
In this article we analyze:
- The current state of AI worldwide in 2026
- The most relevant technological innovations
- How Italian companies are reacting to this transformation
- What all of this means for professionals working in tourism.
From Chatbots to Autonomous Agents: the Real AI Breakthrough
The first phase of generative AI adoption was dominated by chatbots — tools capable of generating text, answering questions, or creating content.
In 2026 we have entered a new phase: the era of intelligent agents.
AI agents do not simply generate responses. They can:
- Analyze data
- Plan actions
- Coordinate activities across different systems
- Execute operational processes
In other words, they become digital collaborators.
AI is evolving toward systems capable of managing complete operational pipelines, such as:
- Analyzing emails and CRM data
- Monitoring commercial relationships
- Suggesting strategic decisions
- Automating content production
This technological leap is one of the reasons many companies are now rethinking their internal processes.
The Technologies Driving AI Forward
Behind this evolution is not a single innovation but a combination of new technological paradigms.
1. Reinforcement Learning with Verifiable Rewards (RLVR)
One of the most important advancements concerns how models are trained.
Traditionally, AI models were improved through RLHF (Reinforcement Learning from Human Feedback): humans evaluated model responses and guided the learning process.
In 2026 a new approach is emerging: Reinforcement Learning with Verifiable Rewards (RLVR).
In this system:
- The model attempts different solutions
- It receives a reward only if the answer is objectively verifiable
This approach is particularly effective for tasks such as:
- Mathematics
- Programming
- Logical problem solving
The result is stronger autonomous reasoning capabilities.
2. Inference Scaling: when AI “thinks” before answering
Another key innovation is known as inference scaling.
Instead of generating immediate answers, models can allocate more computational time to the reasoning phase before producing a response.
This allows AI systems to:
- Analyze a problem through multiple steps
- Verify their own hypotheses
- Correct potential mistakes
This phenomenon is often described as an “aha moment”: the system realizes it made an error and recalculates the logical path.
This deeper reasoning is significantly improving the accuracy of AI systems in complex tasks.
The “DeepSeek Moment” and Global AI Competition
Another key element shaping the AI landscape is geopolitical competition.
In 2025, several analysts began referring to the “DeepSeek Moment,” highlighting the rapid rise of AI models developed in China.
Today the competition largely reflects two different development strategies.
U.S. Models
American companies such as OpenAI, Google, and Anthropic focus on:
- Proprietary models
- Massive infrastructure investments
- Large-scale data center expansion.
Chinese open-weight models
Several Chinese labs — including DeepSeek, Qwen, and Kimi — are instead developing open-weight models, meaning their model weights are accessible.
These systems emphasize:
- Greater algorithmic efficiency
- Lower computational costs
- Broader global distribution.
According to many observers, this strategy could accelerate worldwide adoption significantly.
The Real AI Bottleneck: Energy and Infrastructure
If in the past the main limitation was algorithm quality, today the real constraint is different: energy infrastructure.
The growth of artificial intelligence requires enormous amounts of electricity.
According to several estimates mentioned in recent research:
- The United States alone may require around 90 GW of additional power capacity to support new AI data centers.
To give a sense of scale:
- This is roughly equivalent to the output of about 90 nuclear power plants.
For this reason new infrastructure strategies are emerging, including:
- Mega data centers of 5–10 GW
- Installations near major hydroelectric sources
- Energy projects in regions such as the Middle East or India.
Artificial intelligence is no longer just a software topic — it has become an industrial and geopolitical issue.
Personal AI: the Return of Local Intelligence
Alongside massive cloud models, an opposite trend is emerging: local AI.
Projects such as OpenClaw demonstrate that advanced AI assistants can run directly on consumer hardware, including laptops.
These systems allow companies to:
- Manage private knowledge bases
- Build personalized CRM systems
- Automate internal workflows
- Keep sensitive data locally instead of sending it to the cloud.
One of the most interesting aspects is evolving memory.
Local assistants can:
- Store conversations
- Learn from past interactions
- Adapt their behavior over time.
In the future, many companies may build custom AI ecosystems around their own data.
The Impact on Work: Programming in Natural Language
Artificial intelligence is also changing how software is developed.
According to several industry surveys:
- Many professional developers already use AI for more than 50% of the code they produce.
AI-assisted development tools now allow users to:
- Describe a problem in natural language
- Automatically generate the code
- Debug complex issues.
This does not eliminate developers — it transforms their role.
Increasingly, their work consists of:
- Defining the problem
- Supervising AI systems
- Orchestrating complex software architectures.
And in Italy? A Slower but Growing Transformation
Compared with the global landscape, AI adoption among Italian companies is progressing more slowly than in other technological ecosystems.
There are several reasons for this:
- The strong presence of small and medium-sized enterprises
- Digital infrastructures that are not always fully mature
- A shortage of specialized skills.
However, things are starting to change.
Many companies are beginning to use AI for:
- Content automation
- Data analysis
- Customer support
- Operational process optimization.
In tourism, AI is increasingly applied to areas such as:
- creating tourism product catalogs
- managing multilingual content
- analyzing customer requests
- suggesting personalized offers.
The real breakthrough, however, will happen when AI becomes integrated into operational processes, not just used as a standalone tool.
The Near Future: AI-Native Companies
Looking ahead to the next five years, the difference between companies will no longer be between those who use AI and those who do not.
The real distinction will be between:
- AI-native companies, which design their processes around artificial intelligence
- Companies that treat AI as a simple supporting tool.
The first group will gain significant competitive advantages:
- Faster operational speed
- Better use of data
- Greater service personalization.
Conclusion
The year 2026 marks the beginning of a new phase for artificial intelligence: no longer simply a technology, but a strategic infrastructure for businesses.
For tourism companies, the real challenge is no longer whether to adopt AI, but how to integrate it into operational processes.
Those who move first will be able to work more efficiently, make faster decisions, and deliver increasingly personalized experiences.
In the end, the real value of artificial intelligence is simple:
automating the predictable so there is more space for what truly matters in tourism — humanizing the exceptional.
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