How AI is rebuilding sales [Newsletter #83]

Hello, AI enthusiasts from around the world.

Welcome to this week’s newsletter for the AI and the Future of Work podcast.

What is the most important part of closing a sales deal?

It is hard to measure because it is deeply human: Conversations.

For years, salespeople struggled to focus on them. Meetings meant scribbling notes. Follow-ups meant logging data. Hours went to tracking activity instead of listening.

Those tools captured what happened. They rarely explained why a deal moved forward or fell apart.

This week’s conversation explores how AI can change that balance. By taking over repetitive tasks, it gives salespeople space to focus on what matters most. Real human connection.

Let’s dive into this week’s highlights.🚀

🎙️ New podcast episode with Amit Bendov, CEO of Gong

It started with yellow notepads and one question. Why?

Amit Bendov was coming off one of the worst quarters of his career as a CEO. His dashboards showed every metric. Pipeline. Deals. Activity. The numbers were bad. The problem was simpler and deeper at the same time.

None of the dashboards explained why it was happening.

The existing CRMs told leaders what their staff was doing. They were excellent at tracking activity, but not at explaining success. A critical gap remained: how do you decode the why behind winning deals?

Salespeople felt that gap every day. During meetings, they scribbled notes instead of listening. Afterward came the logs, updates, and entries. All of it was time-consuming and distracting.

That was the discovery: salespeople spent too much time away from customer conversations.

Closing that gap was a communication problem, not a data problem. AI could help by becoming situationally aware, capturing context so salespeople could focus on what mattered most: connecting with humans.

That insight led to Gong and the idea of autonomous revenue intelligence. PeopleReign CEO Dan Turchin sat down with Amit for a candid conversation, where Amit explains that Gong was never built to replace CRM systems.

Instead, it helps sales teams reduce second-guessing by providing real-time, analytical feedback on deals as they unfold.

This week’s conversation covers this and much more:

• Gong’s Revenue AI analyzes sales conversations to help sellers prepare, follow up, and improve performance in real time, setting it apart from traditional CRM systems.

• Sales carries a high emotional load. AI can reduce that burden, improving both outcomes and job satisfaction for sellers.

• What it takes to build trust in AI tools that analyze customer conversations, including data stewardship, transparency, and delivering clear value to the people using them.

• Gong’s AI-first product vision existed years before the technology was ready, showing the importance of designing for autonomy rather than simple automation.

• The reality behind “overnight success”, including early product-market fit tests, risky paid pilots, and navigating growth slowdowns without abandoning the original vision.
  
  🎧 This week's episode of AI and the Future of Work, featuring Amid Bendov, CEO of Gong

Listen to the full episode to learn more about how traditional CRMs and revenue AI differ, and why replacement is not the end goal.

📖 AI Fun Fact Article

AI is changing how jobs disappear and emerge, but not at the same speed everywhere. Writing for the World Economic Forum, Atul Kumar explains why this uneven impact matters.

Industries that depend heavily on structured data tend to feel disruption first. When data is easy to collect and analyze, AI adoption accelerates and certain roles disappear faster. Software engineering, customer support, and financial analysis often fall into this category.

Other sectors move more slowly. Healthcare, construction, and education face constraints around data availability and context. These limits delay automation but do not eliminate change.

This gap shapes where opportunity forms. Kumar argues that the most resilient roles combine technical understanding with human judgment and business context. McKinsey estimates that data-rich industries could reach AI adoption rates of 60 to 70 percent. Gartner projects that sectors with limited data may struggle to exceed 25 percent.

For job seekers, relevance depends less on narrow expertise and more on adaptability. Every industry needs people who can translate AI capabilities into real-world systems and decisions.

Dan Turchin, CEO of PeopleReign, points to the early internet as a useful parallel. It created far more jobs than it replaced. AI will be the same way.

Human drivers are a powerful example. Despite the accelerating pace of self-driving cars, the industry of human passenger transportation will generate more than 100 million new jobs, that's net new jobs, in the next decade, even as it replaces some jobs for Uber, taxi, and bus drivers.

As new regulations emerge, we need people to define, monitor, and enforce those laws. We need urban planners, construction workers, electricians, and designers to re-architect systems that design how we live and commute.Society needs new technicians to program and manage these new fleets of vehicles and analyze and act on the data we'll generate.

Every industry will be impacted by AI, and in every industry, ambitious humans on the right side of innovation will benefit from higher-paying, safer, future-proof jobs.

📽️ Worth a Watch

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Until Next Time: Stay Curious 🤔

👋 That's a Wrap for This Week!

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