Product management is a crucial role in any organization that aims to develop and deliver successful products. It involves understanding customer needs, translating them into actionable requirements, and ensuring that the final solution is not only effective but also profitable for the business.

Sep 16, 2023

3 min read

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In today's fast-paced and dynamic market, the role of a product manager has become even more critical. With the exponential rise in knowledge and the increasingly distributed nature of work, finding existing knowledge has become a time-consuming and often broken process. This is where artificial intelligence (AI) comes into play.

AI has the potential to revolutionize the way we work and access information. As organizations become more distributed and knowledge becomes fragmented, an intuitive work assistant like Glean becomes a critical tool in driving employee productivity. Glean can help employees find the information they need quickly and efficiently, saving them valuable time and allowing them to focus on more important tasks.

However, the adoption of AI in enterprises is not without its challenges. One of the key obstacles preventing the shipping of AI applications to production is the lack of appropriate governance controls. It is crucial for organizations to ensure that their AI applications understand what the end user is allowed to see and not see. They also need to consider where the inference is done and who owns the source data that led to a given model output.

Data processing and annotation remain the most tedious and expensive part of the AI process. It is also the most important for quality outcomes. While pre-trained large language models like GPT-4 have gained popularity, enterprises should not overlook the value of their proprietary data. By leveraging their own data across multiple modalities, organizations can create production AI that leads to differentiated services, insights, and increased operational efficiencies.

Traditionally, tasks like classifying e-commerce listings with multiple paragraphs of text would take humans days to complete. However, with advancements in AI technology, such tasks can now be performed within hours. This not only saves time but also improves accuracy and efficiency.

So, what should organizations and product managers keep in mind when it comes to AI and product management? Here are three actionable pieces of advice:

Embrace AI as a tool for productivity: AI, when properly integrated into the product management process, can significantly enhance productivity. By leveraging AI-powered tools like Glean, product managers can streamline the process of finding relevant information and insights, allowing them to make more informed decisions and deliver better products.
Prioritize data quality and governance: While AI holds immense potential, it is crucial to ensure that the data used to train AI models is of high quality and properly governed. Organizations should establish robust data governance practices to maintain data integrity, privacy, and compliance. This will not only improve the accuracy and reliability of AI applications but also mitigate potential risks.
Continuously adapt and learn: The field of AI is evolving rapidly, and product managers need to stay updated with the latest advancements and trends. By continuously learning and adapting, product managers can identify new opportunities for leveraging AI in their product development process and stay ahead of the competition.

In conclusion, AI has the potential to transform the way we work and access information. By embracing AI as a tool for productivity, prioritizing data quality and governance, and continuously adapting and learning, organizations and product managers can harness the power of AI to deliver innovative and successful products. As the future of work becomes more distributed and knowledge continues to grow exponentially, AI will play an increasingly vital role in driving productivity and success.