AI. Capital.
What comes next.
An investor's perspective on the technology reshaping business. Keynotes, panels, and candid conversations that make complex ideas useful.
A sharper lens on
the future of AI.
AI in finance
What AI changes for investors: diligence, thematic frameworks, and the distinction between a compelling technology and a durable business.
The infrastructure stack
Compute, neoclouds, data, and inference economics. How the layers fit together, where bottlenecks emerge, and why they matter to capital allocation.
Careers at the intersection
Building a career across institutional investing and AI, drawing on experience in private capital and partnerships and prompt engineering work at Anthropic in a contracted capacity.
The next opportunity
begins with a conversation.
For advisory engagements, speaking invitations, and media enquiries, get in touch to discuss what you have in mind.
Isha Ajmera is an investor and AI adviser operating at the intersection of private equity, venture capital, and artificial intelligence.
Isha began her investing career at KKR. She has since closed 22+ transactions worth over $4B and actively deploys capital into AI-native software, infrastructure, and enterprise businesses.
Isha's AI expertise started through her work at Anthropic as a contract prompt engineer. She founded Ajmera Advisory to bring that hands-on knowledge to PE, VC, and hedge fund investors-- helping them find opportunities and develop thematic AI frameworks.
Her expertise spans 100+ expert network engagements across GLG, AlphaSights, Tegus, ThirdBridge, and Guidepoint. Clients include leading global firms including Goldman Sachs, Bain Capital Ventures, Citadel, Mckinsey & Co.
As one of the most active voices on AI in the investment world, Isha is recognized by Business Today as a Global Leader of Tomorrow, named a Top Coach in finance by Leland, has spoken on podcasts, and panels at Wharton, Stanford, and Harvard Business School.
Isha’s most popular keynote topics:
AI in finance: investing, diligence, and infrastructure
Building careers: in institutional investing & AI
The AI infrastructure stack -- inference economics, neocloud, data labeling, enterprise software displacement