Product Management in the Age of AI and Machine Learning

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By Sagar Patidar, CEO, Primathon

Today we see a world that is evolving and adapting to the challenges posed by new and changing technologies. We are all preparing for the “golden age” of AI and machine learning.
Artificial intelligence, deep learning, and machine learning are all used in product management to enhance, improve, create, and shape products.

In the technology industry, product development used to be a long and difficult process. You went through a cascade process, first doing research, then writing a huge product requirements document over several months, then throwing it over the wall to engineering to build, to get something completely different on the other end several months later, before starting all over again.

Until recently, product management was still part of the marketing or engineering departments, falling under these hierarchies and naturally aligning more with one or the other, resulting in conflicting priorities and focus.

Considering that product management is a relatively new field, it is still progressing. The birth of software technology had a significant impact on its development, and then came agile approaches. Today, as artificial intelligence devours software, it is silently reshaping the product management function. It’s increasingly a stand-alone job, with a seat at the executive table and reporting directly to the CEO. This is important because it aligns the product team with the company’s vision and goals, makes them internal and external champions of the vision, and empowers them to make tough prioritization decisions.

Effective product management is becoming a sustainable competitive advantage and continues to evolve in the age of AI and machine learning. It continues to integrate aspects of user experience, separating user flows and experiences from aesthetic design. It promotes flexible working methods that adapt to the needs of the team, the product and the market.

Within organizations, it is increasingly recognized and acquired. It is evolving into a discipline in which you can be an engineer, designer, founder or product manager. All that matters is that you are at the heart of the product and working to improve it for the benefit of consumers. It emphasizes the importance of product management as a profession.

The new age
The world is moving towards a product-driven service model. From global tech giants to similar startups, the most successful companies have developed products that address customer issues in different ways. This trend has accelerated as companies increasingly adopt the subscription-based SaaS (Software-as-a-Service) model as a cost-effective way to pay for what they use.

Against this backdrop, organizations must continue to grow in the product space in order to remain competitive in the technology industry. However, not only does the product development process require frequent customer feedback, but it also requires a strong marketing plan to generate demand. Therefore, product management is the most important part of a product’s success.

According to a recent survey of global business leaders, 70% have started AI activities. With the rise of AI in business, it’s easy to see how it can be applied to B2C and B2B products and services: Google Search, Photos and Translate, Alexa, Amazon Recommendations and Stitch Fix, to name a few. name a few. All of these have one thing in common: machine learning (and data). Discovering the right data and understanding how to use it to develop an innovative product that delights customers and keeps them coming back for more is key to successful AI product management.

Opportunities for AI Product Managers (PMs) are available due to the current shortage of AI PMs and the rapid rise in AI-related development and technology. In addition to the usual product team and stakeholders, PM IAs collaborate with data scientists and engineers. AI project managers must be able to properly deliver AI-based specifications to data science teams. In the face of AI, however, it’s critical for AI PMs to remember to keep the customer in mind.

While the potential of AI is intriguing, the first goal of an AI PM is always to solve a customer’s problem.

AI and machine learning are here to stay, and they will continue to change the way we interact with each other and with the rest of the world. AI project managers need to take a new approach to AI projects, starting with analyzing data to find and validate business leads. So that AI project managers know how to ask the right questions to customers,

They must also continue to collect data in order to refine current AI programs. AI ideas come to life through effective collaboration across cross-functional teams. AI PMs should use AI and machine learning to better understand their customers. Perhaps most importantly, AI project managers must take failure into account.

Uncertainty is unquestionably higher when it comes to AI projects. As artificial intelligence (AI) and machine learning (ML) continue to transform the world around us, they are also having a significant impact on software product management as we know it and reshaping it.

If you have an interesting article / experience / case study to share, please contact us at [email protected]

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