Cyber Resilience: Responsible AI in Cybersecurity with Mauricio Nanne and José Amado

Cybersecurity experts Mauricio Nanne and José Amado discuss AI adoption challenges, ethical frameworks, and strategies for resilient cyberdefense in Latin America

As AI-driven cybersecurity solutions outpace traditional defenses, organizations that fail to integrate proactive ethical frameworks and cross-sector collaboration will face unprecedented vulnerabilities.

In this context, Mauricio Nanne and José Amado, CEO and Outsourcing Cyber Security Manager from SISAP respectively, visionaries in Latin American cybersecurity, unpack critical strategies for resilient, ethical AI adoption. This interview explores balancing innovation with security, navigating regulatory landscapes, and fortifying organizations against evolving threats.

How can organizations keep pace with the rapid advancement of AI solutions applied to cybersecurity?

A: Organizations must adopt a proactive approach combining tech vigilance, continuous training, and strategic partnerships. Testing labs, security automation, and constant evaluation of AI solutions are key to staying current without compromising operational stability.

What are the main challenges in implementing AI-based cybersecurity projects, and how can they be secured by design?

A: Key challenges include data quality, algorithmic bias, model explainability, and resistance to attacks. Secure-by-design requires frameworks like "ethical AI" and auditable, transparent models trained on representative data.

How does the speed of AI adoption impact the competitiveness of solution providers and their clients?

A: Rapid adoption gives manufacturers innovation advantages, while clients gain improved threat detection, operational efficiency, and resilience against sophisticated attacks.

What practices ensure AI cybersecurity solutions avoid new vulnerabilities or ethical risks?

A: Establish clear AI policies, implement model security controls, conduct robustness testing, ensure human oversight in critical processes, and enforce transparency and accountability from the design phase.

How to balance fast AI innovation with responsible, verifiable cybersecurity tech?

A: Use a dual strategy: controlled innovation and continuous verification. Launch pilots in secure environments, validate metrics, scale gradually, and leverage AI governance frameworks.

What role do regulations and industry alliances play in ensuring AI cybersecurity benefits the entire ecosystem?

A: Standards and alliances foster fair conditions, interoperability, and safeguard fundamental rights. Public-private collaboration and ethical compliance frameworks balance competition with collective responsibility.

What approach is SISAP taking to integrate AI into cybersecurity solutions without compromising client trust?

A: SISAP uses specialized assessments to diagnose organizational AI readiness, identifying gaps and risks. We offer tools to detect unauthorized AI use, enabling secure, transparent adoption aligned with client policies.

How is SISAP preparing Latin American clients for AI-driven cybersecurity challenges?

A: We provide strategic recommendations for secure, responsible AI adoption, promoting governance and monitoring frameworks. Global experience is adapted to Latin America, accelerating compliance and threat readiness.