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Ashish Nagar

Founder@Level AI I Amazon Alexa AI I Stanford GSB I BCG

Ashish Nagar is the founder and CEO of Level AI, a professional with a diverse background in product management, business development, and venture capital.

With a strong foundation in engineering from Indian Institute of Technology, Delhi, and further studies in engineering and business at Stanford University, Ashish brings a blend of technical and business acumen to his roles.

Prior to founding Level AI, Ashish served as a Product Manager in Amazon Alexa's Conversational AI team, contributing to the advancement of voice technology.

Ashish has also held leadership positions at Silicon Valley startups Kinestral Technologies and Relcy Inc., overseeing business and product teams, and driving growth from initial stages to significant funding milestones.

Before his ventures in Silicon Valley, Ashish worked as a management consultant with Boston Consulting Group, collaborating with Fortune 500 companies globally to facilitate strategic transformations in product management and operations.

His educational journey includes an MBA from Stanford University Graduate School of Business, complementing his technical background with practical business knowledge and exposure to a diverse network of professionals.

Ashish's professional experience spans across industries and geographies, having worked in African, US, and Indian markets, demonstrating his versatility and adaptability in varying business landscapes.

Passionate about hard sciences and mobile technology, Ashish's expertise lies in product development, market strategy, and driving innovation in emerging technologies.

His career trajectory showcases his progression from consulting to venture capital and ultimately founding Level AI, highlighting his entrepreneurial spirit and leadership capabilities.

Through his roles in renowned organizations such as Amazon, Kinestral Technologies, Relcy Inc., and Boston Consulting Group, Ashish has honed his skills in product management, market development, and business strategy.

Highlights

Jul 17 · linkedin

Had a chat with the CEO of a multi-billion CX company. He made an interesting distinction between "AI that shows good" and "AI that enterprises use."

Over the last decade, RPA and back-office AI have boomed because they are "AI that folks use" – they offer high ROI and scalability.

In Generative AI, the useful stuff includes AI for intelligence, workflow automation, and augmenting human productivity (co-pilots).

On the other hand, "AI that shows well" but hits a wall includes broad human workflow replacement with end-to-end automation and full-service AI agents.

For Enterprise CX leaders crafting their Generative AI strategy, immediate ROI and rapid scaling are crucial. AI that just looks good won’t cut it in the short term.

What AI use cases would you classify as "show good" vs. "folks use"?

Jul 11 · linkedin

Remember when Blockbuster was going after Netflix in the early days of digital content?

Non-native AI SaaS companies who are selling old non AI SaaS or Open AI powered SaaS are like Blockbuster. They just don’t know it yet.

In a world of rapidly changing AI align with Netflix/Hulu not Blockbuster in customer experience software.

#ai #customerexperience

Ashish Nagar
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Location

San Francisco Bay Area