By Paranth Thiruvengadam
Recent research, like a compelling MIT study, highlights why human intelligence must remain central to the AI equation. This study observed participants writing essays under various conditions, including using AI tools like ChatGPT. The surprising finding? Participants who relied heavily on AI showed significantly lower levels of brain activity compared to those who worked independently. The more assistance offered, the less active their brains were during the task.
AI is undeniably transforming the way we work, but the true revolution isn’t about machines replacing humans – it’s about how we collaborate with them. Across industries, the best-performing business operations leveraging AI are not simply implementing new tools but investing in skills, encouraging cross-functionality, and leaning into a culture of experimentation. Ultimately, AI innovation is, and will always be, a human story.
Working with AI
AI works best when we treat it as a collaborative teammate, one that helps us think, not think for us. When people use AI to explore ideas, ask better questions, and co-create solutions, it strengthens their own skills and creativity. When AI thinks for them, however, it undermines the very skills on which human value relies.
But, in our excitement to automate, we might hand over the most interesting work to machines and leave humans with only the supervisory or maintenance tasks. That’s a shortcut to complacency. When AI handles the heavy lifting, human creativity, dissent, and “what-if” thinking need to stay active. Systems should be designed so humans can derail AI’s path when intuition, ethics, or curiosity suggest a better route.
Another critical challenge is designing for what AI doesn’t know. That’s where human judgment bridges the gaps in ambiguity, nuance, ethics, and unpredictable contexts. So, we need to build feedback loops not just between humans and systems, but among humans about how the systems should evolve.
Identifying capabilities of AI agents
AI agents can now carry out more advanced work, from helping with new-employee onboarding to helping with mundane/obsolete tasks that add no value when humans invest time in them. Just like human workers, though, these platforms perform best under proper direction, proper management, and proper authority. Without proper leadership, even the most advanced platforms will fail to deliver meaningful value.
As AI capabilities advance, the need for robust orchestration and governance becomes paramount. This new generation of AI administration platforms will be crucial for helping organisations coordinate their AI agents, align their activities with strategic goals, and ensure accountability. Thoughtful control mechanisms will be vital in ensuring these increasingly capable AI agents operate safely, reliably, and deliver genuine value.
The overarching message is clear – innovation in AI is a group effort. Its success hinges on cross-functional collaboration where all teams come together to not only to determine what AI can accomplish but also how it will be utilised. When AI acts as a complement, rather than a substitute, human creativity and judgement converge with machine efficiency, unlocking immense potential without the pitfalls of over-reliance.
The AI revolution is not about replacing human beings but finding ways of co-creating spaces in which technology and humankind can leverage the strength of each other. Organisations investing in cross-functional work, spending on skills, and creating a culture of experimentation will come out on top.
This is not a battle between humans and tools. It’s a collaboration. The future of innovation depends on weaving together human values and machine scale. If we get this right, AI will amplify what’s best in us, and not what’s easiest. And that’s a future worth building.
The writer is site leader & head of engineering, Atlassian India
