Research institutions are slow by design. Committees, approvals, strategic plans that take two years to write and are outdated before the ink dries. This worked when the world moved at the same pace.
It doesn’t work anymore.
2025 was a turning point for AI. Not the theoretical, “this might change things someday” kind. The practical, “this is already changing how work gets done” kind. Agents that scrape data, tools that build custom workflows, assistants that handle tasks that used to require entire support teams.
And 2026 will be faster. Every indication points to capabilities arriving sooner than anyone predicted even twelve months ago.
Most research institutions are not ready. They’re still debating AI policies while their researchers are already using these tools daily. They’re forming working groups while competitors are deploying solutions. The gap between institutional speed and technological speed has never been wider.
This isn’t about chasing hype. It’s about survival. The institutions that figure out how to integrate AI thoughtfully, that invest in training, that update their processes, that treat this as a strategic priority rather than a side conversation, those are the ones that will attract the best talent and produce the best work.
The ones that wait for certainty will be waiting forever.
The last fifty years of technology were evolutionary. Useful, but incremental. AI is different. It’s closer to what the Industrial Revolution did to manufacturing or what postwar investment did to science. It’s a structural shift.
You can match it with creativity, adaptability, and institutional courage. Or you can write another strategic plan and hope for the best.
— João
It doesn’t work anymore.
2025 was a turning point for AI. Not the theoretical, “this might change things someday” kind. The practical, “this is already changing how work gets done” kind. Agents that scrape data, tools that build custom workflows, assistants that handle tasks that used to require entire support teams.
And 2026 will be faster. Every indication points to capabilities arriving sooner than anyone predicted even twelve months ago.
Most research institutions are not ready. They’re still debating AI policies while their researchers are already using these tools daily. They’re forming working groups while competitors are deploying solutions. The gap between institutional speed and technological speed has never been wider.
This isn’t about chasing hype. It’s about survival. The institutions that figure out how to integrate AI thoughtfully, that invest in training, that update their processes, that treat this as a strategic priority rather than a side conversation, those are the ones that will attract the best talent and produce the best work.
The ones that wait for certainty will be waiting forever.
The last fifty years of technology were evolutionary. Useful, but incremental. AI is different. It’s closer to what the Industrial Revolution did to manufacturing or what postwar investment did to science. It’s a structural shift.
You can match it with creativity, adaptability, and institutional courage. Or you can write another strategic plan and hope for the best.
— João