2025-07-26 –, Track 1
Listen to how a former accountant turned dev learned the hard way what it takes to get AI off the ground—and how you can shortcut the pain
AI is eating the world—but not before a lot of promising projects get quietly killed behind closed doors.
In security-conscious organisations, AI initiatives often die early—not due to technical failure, but because they lack strategic alignment, measurable business impact, or risk transparency. From CISO pushback to data governance red flags, security is no longer an afterthought—it’s often the silent veto.
This talk dives into why AI projects get canned at the executive level, even when the models work, and what cybersecurity professionals, engineers, and data teams can do to build AI projects that don’t just survive—but lead to real, trusted adoption.
AI initiatives often derail not because the code is wrong, but because the project never earned the right executive buy-in. In security-sensitive organisations—where data privacy, regulatory compliance, and risk aversion are paramount—AI pilots frequently die in the boardroom. Left unchecked, these “shadow algorithms” rewrite realities behind the scenes: a model built without clear business metrics, or deployed without a responsible-use policy, becomes an ungoverned risk that CISOs and CFOs won’t tolerate.
As a former accountant turned software developer, I’ve watched several technically sound pilots get cancelled within weeks of deployment. The missing link? A structured approach that ties AI back to hard financial metrics, integrates security and compliance from day one, and delivers fast, visible wins. Drawing on the RAPPID system approach—which stands for Recognise, Forecast, Measure, Invest, Publish, Improve—this talk shows you how to build AI projects that survive scrutiny, deliver measurable value, and scale responsibly.
We’ll walk through a 30-60-90-day RAPPID-inspired roadmap, using specific, security-aware use cases. Each stage highlights concrete actions you can take to:
Recognise & Forecast Value, Invest & Integrate Securely, Publish Results & Improve for Scale
I’m a former accountant(and restaurant cleaner, waiter, manager etc ) turned, software developer, tech educator, product strategist, and driven by impact.
My background and interests in engineering an fuels my work: launching learning programs in ML, mobile dev, and data annotation to connect talent with real-world needs.
I live at the intersection of AI, design, and scalable solutions—especially in health, education, and fintech.
When I’m not building tech, I geek out on sci-fi, hackathons, hiking trails, art exhibitions and exploring new places , food and cities. And yes—I champion learning that’s practical, project-based, and actually fun.