Council Post: How Product Managers can leverage Artificial Intelligence
Artificial intelligence is a basic concept in computer science and engineering, in which a machine is given the ability to perform tasks that normally require human intelligence. These tasks include learning, reasoning, and natural language processing. Artificial intelligence has been successfully applied to many practical problems, such as recognising speech, solving chess, automatically driving cars, and translating languages. Many people believe that AI will be able to match or exceed human intelligence in the near future. The first AI was created by John McCarthy in 1956 at Dartmouth College. His system was able to play checkers extremely well. He called this “strong AI” because it could learn from experience without being explicitly told how to play. The first strong AI program was called ‘ELIZA’ (Electronic Linguistic Interactive Computer). It used simple rules and dialog boxes to simulate conversations between a therapist and a patient. In 1959, Marvin Minsky wrote an algorithm for playing tic-tac-toe with two players who were trying to win against each other. Later, an algorithm for playing chess was developed by Stuart Russell and Peter Norvig in 1999. Artificial intelligence is a broad term that describes the science and technology of making intelligent machines. In brief, it’s the study of how to make machines think like humans. Artificial intelligence consists of two parts: computer science and machine learning. We need machine learning to build AI systems and computer science to design them. Artificial intelligence has become a hot topic in the news lately, with companies like Amazon and IBM investing heavily in the technology. There are many aspects of AI that are still waiting to be discovered by the general public, but it is already clear that we will see more and more applications of AI in our daily lives. Artificial Intelligence in Product Management A great product manager can help your team build the best products. The problem is that you need a great product manager who knows how to use AI-powered machine learning and artificial intelligence tools in order to do it. If you’re not sure how your company should be using AI, it’s time to start thinking about it. The artificial intelligence product management is a kind of business that uses AI technology to provide services, such as: Companies in the travel, medical care and insurance industries use AI to provide services. For example, an insurer can use AI to analyse claims data and determine which customers are likely to file more claims in the future. In addition, it can also determine what type of policies a customer may be interested in purchasing. Companies in the gaming industry use AI technology as a means for creating new games and enhancing existing ones. For example, one company has developed an AI that helps develop future games by analysing data from previous games and identifying where improvements can be made. Companies in the manufacturing industry use AI to automate production processes. For example, one manufacturer uses AI technology to identify which parts need replacing on an assembly line and then automatically generates replacement parts based on specifications. Great Product managers in the coming AI age should be able to code it in their head and then write the code. This is where artificial intelligence can help. The business is growing, but the product development cycle is too long. The products are not being developed as fast as they need to be. The engineers do not have the time or resources to properly implement AI. The company wants to make money, but can’t afford to hire more engineers or develop more products. Using a programmatic approach – product managers can leverage AI tools to auto-generate simple pieces of code (like SQL). This can then free up precious engineering time and resources to focus on testing, stitching together codes, and optimisation. The author believes that in the coming future, everyone should have an exposure to basic coding – to build a logical flow to solve problems. This is a key skill that is a necessity. Infact, one of the ways startups and fintechs are able to pivot and adapt quickly is that they are not solely in the IT department with engineering skills. In these environments – everyone speaks and understands AI with the product managers able to generate and test pseudo codes. The time to market thus shrinks from weeks to even hours. This article is written by a member of the AIM Leaders Council. AIM Leaders Council is an invitation-only forum of senior executives in the Data Science and Analytics industry. To check if you are eligible for a membership, please fill out the form here.
Artificial intelligence has been successfully applied to many practical problems, such as recognising speech, solving chess, automatically driving cars, and translating languages. Many people believe that AI will be able to match or exceed human intelligence in the near future.
Artificial intelligence has been successfully applied to many practical problems, such as recognising speech, solving chess, automatically driving cars, and translating languages. Many people believe that AI will be able to match or exceed human intelligence in the near future.
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["data science", "Go", "machine learning", "artificial intelligence", "AI", "RAG", "Aim", "analytics", "SQL", "R"]
["AI", "artificial intelligence", "machine learning", "data science", "analytics", "Aim", "RAG", "R", "SQL", "Go"]
Amit specialises in business analysis and helps to identify the needs of business and bring in solutions to problems. Managing risks through identifying and assessing the threat to business is also one of them. He has a critical understanding of technology and platforms for deploying digital assets.

Amit is currently the Senior Vice President at SBI Cards whose passion ranges from building businesses around data and digital and being a catalyst to bringing financial services to the under-served. His interest diversifies to Artificial intelligence, Machine learning, Analytics, modelling and business research.