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View profile for Albert Mao

Founder @ VectorShift(YC): No-Code AI Platform | Ex-McKinsey | Statistics @ Harvard

Enterprise AI solutions are 99% showmanship – cool internal demos without real ROI. That is the cold hard truth. <10% of enterprises have GenAI solutions in production. Most enterprises have: 1. Appointed a head of AI 2. Identified use cases across business units 3. Built proof of concepts So why are enterprises stuck before moving to production? - Uncertainty around AI investments: Companies are concerned about the implications of investing in AI solutions that may not deliver the expected results (or worse, result in negative reputational risks). - Too many choices: Firms are flooded with options and are not sure what to choose. Should I use an out of the box solution? Should I build the solution in-house? Should I outsource to a vendor? - Complex decision making structures: I have seen many enterprises form multiple committees that complicate decision-making processes, leading to delays and indecision. We built VectorShift to help enterprises move from proof of concept to production with confidence. Feel free to reach out - happy to share best practices: [email protected]

I would also say lack of familiarity with tools, inability to evaluate trade offs, generally to stuck in database / cloud optimization projects they’ve already committed to / budgeted for

Dhiren Jani

GenAI, Digital Strategy & Products

3mo

An enterprise is not a monolith, but has multiple parts functioning in harmony. If you can offer ROI of GenAI for a department or team, that's a big win that can move the entire organization. I found the appropriate GenAI solution architecture and roadmap in a week, but still don't see the ROI business case after months. If you can solve that, happy to talk.

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Praneeth Nadella, MBA

Workflow Automation Expert | Helping SMBs Optimize & Scale with No-Code Solutions

3mo

This is a great breakdown of why enterprises face challenges with AI adoption. Enterprises also struggle with change management — whether its aligning AI initiatives with business processes or retraining employees.

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Your points on navigating AI investments and decision-making complexities are spot on

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