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5 Key AI Trends Reshaping Business: Insights from Ramp CEO Eric Glyman

The Digital Future Initiative kicked off its BIZTech Lectures series with a discussion exploring AI’s impact on business operations, financial efficiency, and technological adaptation.

Published
March 12, 2025
Publication
AI and Transformative Tech
Focus On
Artificial Intelligence (AI), AI & Transformative Tech
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Ramp CEO Eric Glyman

Ramp CEO Eric Glyman, left, with Professor Daniel Guetta

Category
Thought Leadership
Topic(s)
Artificial Intelligence, BizTech Speaker Series, Business and Society, AI and Transformative Tech, Finance

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Columbia Business School’s Digital Future Initiative (DFI) recently hosted a conversation with Eric Glyman, CEO and co-founder of Ramp, a leading financial operations platform serving over 30,000 companies from family farms to Shopify. They're also one of the fastest growing startups of all time, and headquartered here in New York.

The discussion, led by Associate Professor of Professional Practice Daniel Guetta, was the first in the DFI series of BIZTech Lectures and covered a range of topics, including AI’s transformative role in business operations, financial efficiency, and how companies can adapt to new technological paradigms. 


For business professionals looking to stay ahead of the curve, here are five key takeaways from the event.

1. AI is Moving from Experimentation to Essential Infrastructure

Ramp’s unique vantage point—processing over $55 billion in corporate spending—provides valuable insights into AI adoption across industries. Glyman noted a dramatic shift in AI usage, from experimental trial-and-error to widespread, integral adoption. Only 50% of companies that adopted an AI tool in 2022 had it 12 months later. In the past year that went up to 70%, signaling a clear transition toward AI as a core business function rather than a novelty.

For business leaders, this trend underscores the importance of implementing AI thoughtfully—not just as a one-off experiment but as a long-term strategy for efficiency and growth.

2. AI Is Reshaping Sales and Customer Acquisition

One of the most compelling use cases of AI at Ramp is in sales development. Traditionally, sales development representatives (SDRs) manually researched leads, crafted outreach emails, and followed up with potential clients. Today, Ramp has automated most of these tasks using AI. Machine learning models identify high-potential leads, craft personalized outreach, and even run A/B tests to refine messaging.

As a result, Ramp’s SDRs focus on human interactions—engaging with prospects who have already expressed interest—leading to five to six times higher productivity compared to traditional sales teams. For businesses, this represents a major opportunity: AI-driven sales automation can significantly enhance efficiency while allowing human teams to focus on relationship-building and strategic negotiations.

3. Zero-Touch AI and Process Automation Are the Future

Glyman emphasized that some of the most impactful AI applications are those that operate behind the scenes without requiring user input—what he calls “zero-touch AI.” Examples at Ramp include automatically categorizing expenses, reconciling transactions, and processing reimbursements.

For instance, when an employee makes a purchase, Ramp’s AI can instantly match the transaction with a receipt, cross-reference calendar data to verify business meetings, and assign the correct accounting category—without requiring the user to intervene. This automation removes friction from financial operations, reducing manual labor and errors.

Business leaders should consider how similar AI-driven automation can streamline internal processes, from HR and payroll to customer service and compliance monitoring.

4. AI is Driving Down Costs—and Companies Must Adapt

One of the most surprising insights from the discussion was the rapid decrease in AI operational costs. Glyman pointed out that the cost of running AI models has dropped significantly, and as the technology continues to improve, costs will approach zero. This shift creates new competitive dynamics, as companies that leverage AI effectively can operate with significantly lower overhead than their competitors.

Additionally, AI is making software development more accessible. Historically, switching between enterprise software platforms required expensive and complex migrations. Now, AI-powered automation is simplifying these transitions, eroding traditional moats for legacy enterprise software providers. Businesses that fail to adapt risk being outpaced by more agile competitors that leverage AI to reduce costs and increase efficiency.

5. The Future of Work: From Managing Work to Doing Work

Glyman closed with a thought-provoking observation about the broader implications of AI: it enables workers to focus on meaningful contributions rather than administrative busywork. Many modern jobs involve substantial overhead—emailing, data entry, and compliance tasks that consume valuable time. AI’s ability to automate these functions means that employees can spend more time innovating, strategizing, and solving complex problems rather than managing logistics.

For executives, this signals a crucial shift in workforce management. Investing in AI tools that automate low-value tasks allows teams to concentrate on high-impact work, leading to greater job satisfaction, efficiency, and overall productivity.

Glyman's insights provided a compelling look at how AI and automation are reshaping business operations. Companies that integrate AI strategically—whether in sales, finance, or general operations—will gain a competitive edge in efficiency and adaptability, he says. 

Business leaders must move beyond viewing AI as a futuristic experiment and start treating it as a core part of their operational strategy. As AI continues to evolve, the most successful companies will be those that embrace it not as a replacement for human intelligence but as a powerful tool to amplify productivity and drive meaningful innovation.

 

This article was generated with the assistance of AI and subsequently reviewed and refined by a human editor to ensure accuracy, clarity, and coherence.

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