When Automation Meets Ethics, Budget, Data, and Risk: The Real Factors Behind AI Deployment | An ...
0Artificial intelligence is often described through hype or headlines, but few people work directly at the intersection of research and real-world implementation the way Andrea Isoni does. As a data scientist and machine learning engineer managing AI projects since 2017, Andrea brings a refreshingly direct view of what’s possible—and what’s practical—when it comes to using AI for business and societal impact.
In this episode recorded at Infosecurity Europe, Andrea outlines the many roles involved in operationalizing AI, from data engineers and analysts to project managers and machine learning specialists. He emphasizes that despite all the impressive language surrounding AI, much of the work still involves cleaning data, assessing model readiness, and making decisions based on cost, scalability, and risk tolerance. A “one-size-fits-all” model doesn’t exist; every implementation must be evaluated against the client’s specific context and budget, and decisions often come down to whether the project is meant to drive research and IP or automate existing workflows.
Andrea discusses two real-world case studies. One project with the Ministry of Justice in Saudi Arabia explored automating small claims car accident rulings based on previous court data—a proof-of-concept with 95% accuracy. Another, more grounded example involved helping telecom providers automate regulatory reporting, saving hours of manual compilation by analysts. These examples illustrate the spectrum of AI’s capabilities: from ambitious innovation to process improvement that simply makes work more efficient.
He also reflects on the future—and the risks—of democratized AI. As models become smaller and more portable, Andrea warns that the same proliferation that empowers businesses and researchers could also enable criminal actors to build customized AI systems, much like cartels already invest in developing undetectable submarines or secure telecoms. When illicit groups begin investing in AI R&D rather than just purchasing commercial tools, unpredictability rises sharply.
Andrea leaves us with a philosophical but clear-eyed view: AI can reduce inefficiencies and unlock new capabilities, but it must be implemented thoughtfully, with full awareness of its context, limits, and impact. It’s not about replacing human judgment—especially in nuanced, high-stakes environments—but augmenting it where automation is justified.
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Guest: Andrea Isoni, Chief AI Officer, Director at AI Technologies | https://www.linkedin.com/in/andreaisoni20/
Hosts:
Sean Martin, Co-Founder at ITSPmagazine | Website: https://www.seanmartin.com/
Marco Ciappelli, Co-Founder at ITSPmagazine | Website: https://www.marcociappelli.com/
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KEYWORDS
andrea isoni, sean martin, marco ciappelli, ai, machine learning, automation, data science, cybersecurity, risk, scalability, infosecurity europe, event coverage, on location, conference