AI Product Management

Artificial intelligence is probably the most hyped technology of the last few years. The marketing community jumped all over AI, and it has become such a buzzword that many people think it’s not actually real. But they couldn’t be more wrong. This technology is real, useful, and used by companies like Alibaba, Google, Facebook, and Microsoft to better their products and services. 

AI is related to computer science, artificial life, machine learning, cognitive science, and more. In simple terms, it’s a collection of methods and algorithms that enables devices or software applications to learn without being explicitly programmed. It reads data, learns from it, and generates a corresponding set of instructions that help it perform a particular task. Before you run straight for the hills, though, understand that this is a very broad definition that doesn’t help anyone understand what exactly AI is and isn’t capable of. 

AI is often associated with automating human processes by mimicking human thinking, such as recognizing images (e.g. face detection), learning (e.g. video object detection), and speech (e.g. automatic speech recognition). It’s already used in products like Siri on your iPhone or Cortana on your PC. Social networks like Facebook use AI to recognize faces in your friends’ photos or recommend videos based on your current activity and preferences. Finance companies are using AI to allow you to analyze market data (stocks) more efficiently than a human being can – after all, it’s all about efficiency and cost-effectiveness here. 

While many applications of AI are quite clearly demonstrated, it’s not quite as easy to pin down what things are still impossible for AI to solve yet. The theory and limitations of AI are discussed every year at the International Joint Conference on AI (IJCAI) held annually in California and this year’s conference took place in Barcelona from the 19th to the 25th of July 2016. This article provides an overview of what IJCAI-16 brought to light: 

What is AI Product Management? 

Product management and AI don’t seem to align at first glance, but AI is actually a potential asset for product managers, especially as it’s adopted by everyone – consumers, companies, and organizations. AI can help you track competition, monitor conversion rates, find new opportunities and clients, make product design decisions, test them, and more. The main challenge with current artificial intelligence technologies as they stand now is that they’re ‘black boxes’ – you put in some data, get some output, and have no idea how exactly they got there. This makes it difficult to apply any kind of feedback loop and to iterate a given algorithm based on facts – you just don’t know what’s going on inside. But according to Andrew Ng, the goal of AI ultimately is to be transparent and explainable – and we are getting there. 

How can Product Managers manage AI?

Ultimately, the entire process of creating and maintaining a product relies on communication, coordination, and different types of interaction between people. This is true even if you’re working in a startup with only a small team. In big corporations, you have to deal with a massive number of teams: product, engineering, R&D, designers, customer support, marketing channels, etc. Putting all of these teams together without direct organizational connections is a real challenge. A single mistake can set your whole marketing campaign back by months. People end up getting super-busy with miscommunication, trains get derailed. AI will help us control the flow of information within organizations we haven’t been able to control in the past. The best thing about AI is that it searches for new solutions all the time, it has almost unlimited memory capacity, and it doesn’t get tired or depressing (at least not yet). AI is more like a human and more specific than any other tool used in product management today. In practice, AI can help you pivot faster. If your current business plan isn’t giving you the results you expected, you can create a competing or complementary product without having to go through extensive discussions within your company or with outside partners. 

Conclusion

AI is a young science, but it’s constantly evolving and getting better. It certainly has a bright future in many different fields, and product management is one of them. It’s a perfect fit because it takes all your data and consolidates it into a single place that you can use in any number of ways. And there are many companies already using AI to their advantage in product management. 

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