Impact of AI on research is the most talked about topic in most academic circles and research conferences these days. In one such discussion during the India Strategy Conference (ISC2025) at Indian School of Business this year, I raised a concern that if most research gets 'powered' by AI - which is increasingly the case - the quality of research outcomes will be increasingly dependent on the kind and version of AI one has employed. As AI becomes a resource, ability to carry out high quality research becomes a question of access and affordability.
I was countered with an argument that AI is an equalizer. In one sense it is, as it allows one to try his/her hands at high quality research without the depth of skillset that research demanded earlier. But beyond the basic level, inequality starts taking shape because the resource is limited and controlled. Claude Haiku 4.5/Sonnet 4.6/Opus 4.7? ChatGPT Free/Go/Plus? Gemini Free/Plus/Pro/Ultra? We all know that the free ones are extremely limited in capability and reliability. Paid ones have variants offering different levels of capability depending on how much you pay. The pricing is equal worldwide, but the purchasing power isn't. So users are forced to settle, and work with whatever is the best they can get their hands on.
Research outcomes have always been constrained by access to resources. But now, with 'intelligence' as a resource, the race can get too exhausting for many - some running on sand, some even on water - while a few cruising on firm surfaces, breezing through in skates that don't even make a sound. The bodies may be equal, the race still isn't.
Posted on LinkedIn on 27 May 2026.
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