The Intersection of Associate Product Managers and the Impact of AI on the Industry


Hatched by Glasp

Sep 13, 2023

4 min read


The Intersection of Associate Product Managers and the Impact of AI on the Industry


In today's competitive market, organizations are constantly looking for ways to capture and nurture talent early on. One such role that has gained prominence is that of an associate product manager. This junior position allows companies to bring in promising individuals and train them to become successful product managers. Additionally, some organizations utilize associate product managers to alleviate the workload of existing product managers without overburdening the team or budget. In this article, we will explore the role and responsibilities of associate product managers while also delving into the transformative power of AI and its implications for the industry.

The Rise of Associate Product Managers:

As organizations mature, they recognize the importance of investing in talent acquisition and development. Product managers, in particular, are highly sought after but can be challenging to find. To address this issue, companies have adopted the associate product manager role. By hiring junior talent and providing them with comprehensive training, organizations groom these individuals to become competent product managers. Some companies even follow a tenure-based promotion system, where associate product managers are promoted to higher positions after a certain number of years.

The Impact of AI on the Industry:

As AI continues to advance, it is reshaping various industries and revolutionizing the way tasks are performed. One notable effect is the reduction of creation costs. Just as the internet eliminated distribution costs, AI is driving down the expenses associated with content creation. This reduction in costs is not evenly distributed but rather subject to rapid consolidation and power law outcomes among infrastructure players and end-point applications.

The Role of Compute Power and Open Source:

The availability of widely accessible math and similar training datasets has leveled the playing field for AI development. With sufficient skills and resources, almost anyone can build a copycat AI model. However, the true differentiators lie in factors such as developer community, ease of use (including UI/UX), and the network effect around the ecosystem. Open source also exerts downward pricing pressure on model providers selling access to their models via APIs, compelling them to compromise on pricing when competing with free alternatives.

Long-Term Model Differentiation and Data-Generating Use Cases:

While fine-tuned models may win individual battles, the war is won by foundational models that excel at generating valuable data. This long-term model differentiation stems from the ability to harness data-generating use cases effectively. Companies that prioritize data collection and analysis have a competitive advantage in the AI landscape.

The Role of Sales and Marketing in AI Adoption:

In the race for AI domination, the purchasing decisions of businesses are often influenced by go-to-market (GTM) strategies rather than a direct comparison of vendors. The success of an AI startup in securing its market endpoint is determined by factors such as sales, marketing, and overall brand perception, rather than the pure performance of its AI models. AI becomes a marketing tool, and companies that excel in distribution and product capabilities have a significant advantage over startups attempting to develop comprehensive AI products from scratch.

Distribution as the Ultimate Decider:

In the age of easily accessible content creation, distribution becomes the key differentiating factor. Creators who leverage AI tools to produce better content at a faster pace can amass a critical mass of fans. However, the digital media landscape already exhibits a pattern where a small percentage of creators monopolize the revenue. AI exacerbates this dynamic, further emphasizing the importance of distribution channels.

The Rise of Invisible AI:

Invisible AI refers to companies that utilize AI without explicitly mentioning it. These organizations leverage AI to achieve what was previously considered impossible, resulting in delightful experiences for users. By seamlessly integrating AI into their products and services, these companies gain a competitive edge in the market.

Actionable Advice:

  • 1. Invest in talent development: Organizations should prioritize talent acquisition and development programs to groom future product managers. By hiring associate product managers and providing them with comprehensive training, companies can ensure a competent pool of product management professionals.
  • 2. Embrace the power of data: Long-term model differentiation in the AI landscape relies on the ability to generate and analyze valuable data. Companies should focus on collecting and leveraging data-generating use cases to gain a competitive advantage.
  • 3. Prioritize distribution channels: In a world where content creation is easily accessible, distribution becomes the ultimate decider. Creators and businesses should leverage AI tools to enhance content creation and focus on building strong distribution channels to reach their target audience effectively.


The role of associate product managers offers organizations a valuable opportunity to capture and develop talent. Simultaneously, the rise of AI is transforming industries and revolutionizing the way tasks are performed. By understanding the implications of AI and incorporating actionable advice, companies can navigate the evolving landscape and stay ahead in this dynamic and competitive market.

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