Artificial intelligence is everywhere these days, but most companies are making the same mistake. They’re so focused on what they can build that they forget to ask what they should build. The rush to deploy AI solutions often leaves ethics and privacy as afterthoughts, creating problems that could have been avoided from the start. Jacques Nack, CEO of JNN Group, Inc. and Quantum, has spent over 20 years watching this pattern repeat itself across fintech, healthcare, and technology companies.
Start With Ethics, Not Excuses
Most companies get this backwards. They build first, then try to patch in ethical considerations when regulators come knocking. Nack has watched this play out countless times, and it never ends well. “Too often, companies treat ethics as an afterthought, something to fix after deployment. It’s a common mistake. This is not where you build and constantly iterate. No.” The smart move is building ethics into your AI from day one. That means setting clear rules about how AI can and cannot use data before you process a single file. You need boundaries, transparency, and a clear way to explain what your algorithms actually do. When Nack’s team works on healthcare analytics, they put fairness checks right into the AI pipeline before any data gets processed. It’s not just about checking boxes for GDPR and HIPAA compliance. It’s about building trust with users and stakeholders from the ground up.
Privacy Isn’t Optional Anymore
Here’s something every CEO needs to understand: just because AI needs data doesn’t mean it should get access to everything. You need governance frameworks that put consent first, collect only what you need, and use strong encryption and anonymization. Nack doesn’t treat this as a nice-to-have feature. “In our work, we treat privacy as an operational standard, not a checkbox,” he explains. This thinking shapes everything they do, whether it’s financial data or cloud-based solutions. Privacy protection gets built into every single stage, from collection to processing to storage. JNN Group runs an AI-powered audit and compliance platform that walks clients through complex regulatory requirements while keeping their sensitive information locked down. The questions start right away when new clients sign up. “When people are trying to log into Compliance Core from Singapore, the first question they ask is: Is your data center located near us in Singapore?” Nack points out. The same concerns come up with UK clients and everyone else. People want to know where their data lives and what control they have over information they share. If you can’t answer those questions clearly, you’re going to lose business.
Monitoring AI Behavior Continuously
AI models don’t stay the same forever. They learn, they change, and sometimes they go off the rails. That’s why ongoing audits, bias monitoring, and clear accountability matter more than most people realize. Nack sees companies getting burned by this all the time, especially when AI systems talk directly to customers. “Today, I see many companies using automated sales tools to talk to their clients. That means you have a chatbot representing your company, your CEO, your COO talking to someone else, and sometimes they drift off.” He’s seen some very public examples recently where chatbots started saying things that definitely shouldn’t represent a company’s leadership.
The fix isn’t complicated, but it requires discipline. You need a governance board that regularly reviews AI performance against your stated principles. At JNN Group, they’ve found that mixing engineers, legal experts, and business leaders into oversight prevents blind spots and keeps decisions balanced. They also build in manual checkpoints where humans can review AI outputs. “We implement manual checkpoints where a human can review the output of an AI process and approve, disapprove, or add comments, which add context and improve the fit of the AI response in the future,” Nack explains. It’s about maintaining oversight over outputs, understanding how information gets processed, and catching when your model starts to drift.
Here’s what Nack wants every business leader to understand: ethical AI governance isn’t about slowing down innovation. It’s not about adding more bureaucracy to your processes just because regulators are watching. “Navigating AI ethics in data governance isn’t about showing you have AI. It’s about adding meaningful constraints to your pipeline and process. We’re not looking to slow down your innovation. It’s about guiding it in the right directions,” he says. Companies that build ethical considerations into their design, protect privacy at every step, and commit to ongoing oversight can actually move faster. They avoid the regulatory headaches, the public relations disasters, and the customer trust issues that sink their competitors. The AI future belongs to companies that get this right from the beginning. The technology is powerful, but it needs to be guided by people who understand that responsible innovation creates better long-term results than quick wins that fall apart under scrutiny.
Connect with Jacques Nack on LinkedIn to explore how ethical AI can drive business growth.
