Boston 1630: Cows laid trails, founders paved them. Result? A maze of winding roads even today. Companies do the same: they "digitize" inefficient processes instead of redesigning them. "Using ChatGPT to write faster emails in a process that takes 12 for a simple decision." Michael Hammer: "Stop paving cow paths. Obliterate them and start over." The right question is not "how to do this faster" but "why are we doing this?"

We are not building AGI-we are building an increasingly convincing illusion. In 2025, general intelligence will emerge not from a single system, but from a mosaic of coordinated specialized AIs: LLMs, image generators, AlphaFold. Quantum computing promises to exceed the computational plateau (-99% consumption according to IBM), while Microsoft and Google compete with radically different approaches. The provocation? If human consciousness is itself an emerging illusion, perhaps AGI "by proxy" is more like us than we think.

"Using an LLM to calculate an average is like using a bazooka to hit a fly." Critical analysis of real use cases: Instacart, Google, Uber, DoorDash. The truth? The most compelling cases maintain the human-in-the-loop approach-AI assists, not replaces. The best applications are those tailored to specific domains, not generic ones. The companies that thrive are not those that adopt LLMs more widely, but those that apply them more strategically.

Europe attracts only one-tenth of global investment in artificial intelligence but claims to dictate global rules. This is the "Brussels Effect"-imposing regulations on a planetary scale through market power without driving innovation. The AI Act goes into effect on a staggered timetable until 2027, but multinational tech companies respond with creative evasion strategies: invoking trade secrets to avoid revealing training data, producing technically compliant but incomprehensible summaries, using self-assessment to downgrade systems from "high risk" to "minimal risk," forum shopping by choosing member states with less stringent controls. The extraterritorial copyright paradox: EU demands that OpenAI comply with European laws even for training outside Europe-principle never before seen in international law. The "dual model" emerges: limited European versions vs. advanced global versions of the same AI products. Real risk: Europe becomes "digital fortress" isolated from global innovation, with European citizens accessing inferior technologies. The Court of Justice in the credit scoring case has already rejected the "trade secrets" defense, but interpretive uncertainty remains huge-what exactly does "sufficiently detailed summary" mean? No one knows. Final unresolved question: is the EU creating an ethical third way between U.S. capitalism and Chinese state control, or simply exporting bureaucracy to an industry where it does not compete? For now: world leader in AI regulation, marginal in its development. Vaste program.

87% of support teams have seen customer expectations rise, with 68% attributing this to AI. The first 90 days are essential to avoid analysis paralysis and start getting real results. The 3-phase plan covers from strategic alignment to pilot implementation and measurable expansion, avoiding common mistakes and tracking key metrics such as efficiency and revenue impact. With dedicated support and ongoing training, you will turn initial successes into a pro-IA company culture.

While 61% of people are already wary of AI that understands, in February 2025 Gibberlink gained 15 million views by showing something radically new: two AIs that stop speaking English and communicate through high-pitched sounds at 1875-4500 Hz, unintelligible to humans. This is not science fiction but FSK protocol that improves performance by 80 percent, subverting Article 13 of the EU AI Act and creating double-level opacities: inscrutable algorithms that coordinate in indecipherable languages. Science shows that we can learn machine protocols (such as Morse at 20-40 words/minute) but we run up against insuperable biological limits: 126 bits/s human vs. Mbps+ of machines. Three new professions are emerging-AI Protocol Analyst, AI Communication Auditor, AI-Human Interface Designer-while IBM, Google and Anthropic develop standards (ACP, A2A, MCP) to avoid the ultimate blackbox. Decisions made today on AI communication protocols will determine the trajectory of artificial intelligence for decades to come.

AGI (General Artificial Intelligence) remains theoretical: unlike current narrow AI (Siri, autonomous cars), it should transfer knowledge between domains like the human brain. Experts estimate decades to achieve it. Main challenges: cognitive complexity, ethics/security, immense computational resources. In Italy, potential applications in agribusiness, government services (MLPS chatbots already active), water monitoring (Rome), personalized media. Italian resources: CINI-AIIS, IIT, I3A Turin, PAI Lab Pisa. Italy participates in the global GPAI.

76 percent of companies keep AI captive in technical departments-and lose the bulk of its value. True transformation happens when every employee, from marketing to operations, can leverage AI without writing a line of code. Learn how natural language interfaces, role-specific applications and AI integrated into existing workflows have generated real results: -28% downtime in manufacturing, +67% time spent with customers in financial services, -41% administrative paperwork in healthcare.