{"id":6949,"date":"2026-07-06T07:23:35","date_gmt":"2026-07-06T07:23:35","guid":{"rendered":"https:\/\/innovaway.it\/?p=6949"},"modified":"2026-07-06T07:26:55","modified_gmt":"2026-07-06T07:26:55","slug":"oltre-lhype-dellai-pragmatismo-sicurezza-e-logica-neurosimbolica-per-il-business","status":"publish","type":"post","link":"https:\/\/innovaway.it\/en\/oltre-lhype-dellai-pragmatismo-sicurezza-e-logica-neurosimbolica-per-il-business\/digital-transformation\/","title":{"rendered":"Beyond the AI Hype: Pragmatism, Security, and Neuro-Symbolic Logic for Business"},"content":{"rendered":"

Sergio Ajani, Service & Solution Design Director at Innovaway, analyzes the limitations of probabilistic models and illustrates how the integration of neuro-symbolic logic is the key to ensuring security, compliance, and repeatability in corporate and Public Administration processes.<\/em><\/p>\n

Artificial Intelligence, particularly Large Language Models (LLMs), has monopolized the technology debate in recent years. However, once the initial enthusiasm fades, business decision-makers and IT leaders face a complex challenge: how to deploy these technologies within\u00a0mission-critical contexts.<\/em>\u00a0contexts where the margin of error must approach zero? Sergio Ajani, Service & Solution Design Director at Innovaway, offers a pragmatic, business-oriented perspective that steers clear of utopian promises to focus on the actual applicability of AI at the enterprise level.<\/p>\n

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The Limitation of Probabilistic Logic in Critical Processes<\/strong><\/p>\n

The core issue of adopting LLMs in business lies in their inherently probabilistic nature. These models are trained to generate the statistically most plausible answer, often developing a tendency to \"please\" the user. While this approach is acceptable for drafting an informal email, it becomes a systemic risk in engineering, medical, or financial fields.<\/p>\n

Companies cannot base their decision-making processes on systems that generate entropy or varying responses for the exact same input. For business, the absolute priority is process\u00a0repeatability<\/strong>\u00a0and the ability to unequivocally identify the cause-and-effect relationship. This risk is further amplified with the rise of\u00a0Agentic AI<\/em>, where autonomous agents delegate tasks to other agents; in this scenario, the chances of error and \"drift\" multiply exponentially.<\/p>\n

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The Compass Metaphor: The Need for External Control<\/strong><\/p>\n

How do you govern such a complex digital ecosystem? Ajani uses an effective aviation metaphor: even the most modern aircraft maintain redundant control systems based on physical or analog logic (such as the traditional magnetic compass) that operate entirely outside the primary digital avionics domain.<\/p>\n

Similarly, controlling the actions of AI agents cannot happen within that same probabilistic domain. What is needed is a \"third-party\" monitoring framework that verifies adherence to business processes, acting as a compass to keep the system on course and prevent systemic hallucinations or deviations from regulations.<\/p>\n

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The Innovaway Approach: Neuro-Symbolic AI<\/strong><\/p>\n

To meet the demands for transparency (Explainable AI) imposed by regulators and market needs, Innovaway is collaborating with academia to implement theNeuro-Symbolic Artificial Intelligence paradigm into its services.<\/strong>.<\/p>\n

This approach combines the strengths of two historically separate computing worlds:<\/p>\n