#human-oversight

#human-oversight

Artificial Intelligence has quickly become one of the most powerful accelerators marketing has ever had. There is no doubt that Gen AI tecnologies are expected to shape the future of marketing for companyies. Used well, it sharpens execution, unlocks efficiency and expands creative possibilities. Used poorly, it quietly erodes trust, weakens brands and forces painful strategic reversals. Recent years' examples make this contrast clear.

South Korea has launched a landmark set of laws to regulate AI before any other country or bloc (the EU's regulations are set to go into effect in stages through next year). Under Korea's AI Basic Act, companies must ensure there is human oversight for "high-impact" AI in fields like nuclear safety, drinking water, transport, healthcare, and financial uses like credit evaluation and loan screening.

Generative AI (genAI) has passed the point of novelty. It's helping software engineers write code, lawyers draft contracts, and physicians summarize medical notes. It has quickly and quietly woven its way into the tools people use every day. The speed of genAI adoption has been staggering, but so has the uncertainty it has ushered in. As adoption continues to accelerate, one significant question looms: When will genAI transition from "experimental" to a truly "enterprise-grade" technology that we can trust with our data?

No doubt you've noticed it-along with millions of others who now rely on AI for everything from planning product launches and rewriting emails to turning their beloved pets into cartoons. The adoption speed has been remarkable. In just a few years, AI has gone from a buzzword to a daily fixture in countless workplaces. And for many, it's already hard to remember what work looked like without it.

That doesn't mean a jobs cliff is imminent, said James Ransom, a research fellow at University College London, who studies the impact of AI on work. But it does mean the rules of entry into the job market are changing fast - and the smartest move isn't to chase prestigious titles, he said, but to understand the tasks inside those jobs, then show how you can supervise and scale AI to do them more effectively.

Omar argues that traditional security models are no longer sufficient.