Artificial Intelligence (AI) is a technology that attempts to automate human intelligence based on the way a human brain processes any information whereas, Machine Learning (ML) is a subset of Artificial Intelligence that focuses on giving computers the ability to learn without explicitly being programmed. These two technologies go hand in hand and are continuing to be the platform for the growth of many companies. So, what are Artificial Intelligence problems? Let’s have a look.
1. If the answer to the problem needs symbolic representation in computers, then we can consider it as an artificial intelligence problem. For example, understanding of English sentences by a computer when they are represented in the symbolic form.
2. If there is a combinatorial explosion in outputting the result of a traditional problem, then we can consider such a problem as an artificial intelligence problem. For example, (8- Queens problem) Given a chessboard of size 8 x 8, we have to place 8 queens on the chessboard such that no queens contradict each other. There are 96 possible solutions.
3. It is hard to characterize data in artificial intelligence problems. Adjectives like beautiful, white, etc., cannot be quantified. So, fuzzy set theory is used to solve such quantification.
4. The knowledge base of an artificial intelligence problem is voluminous. This size increase happens by the change of knowledge from time to time by adopting new knowledge.
5. The data or knowledge base is changing fast. The size of the knowledge base increases day by day. This is achieved by the learning process.
6. In doing some jobs, humans get fatigued, whereas computers can perform such jobs without any tiredness. For example, an ATM of a bank performs jobs as a clerk cum cashier for the entire day.
In this article we look at:
A recent survey of global business leaders has indicated that 70% of them have started taking AI initiatives. AI Project Management is a relatively new field, and AI Product Managers ensure that those AI initiatives are successful and meet the needs of customers.
As the name implies, AI product management entails many of the same responsibilities of normal product management, except the products that they manage are AI products. AI product management focuses on using artificial intelligence, deep learning, or Machine Learning to enhance, improve, or create products. Also, the Role of an AI Product Manager includes (but not limited to):
· Additional input: AI Product Managers have to work with data engineers and data scientists, in addition to the traditional product team and stakeholders. AI Product Managers need to be able to deliver AI-powered specifications to data science teams effectively.
· Problem mapping: Yes, this is likewise a critical segment of conventional product management. It’s fundamental, notwithstanding, for AI PMs to make sure to remain client driven despite AI. While the capability of AI is captivating, an AI PM’s objective is still particularly about taking care of a client’s concern. AI isn’t a fix-all; AI PMs should keep the client center upfront.
· Data proficiency: Knowing the correct questions to ask about client data is a completely new PM range of abilities. Having involved insight or working information of data and models as an AI PM is viewed as fundamental expertise by AI specialists.
· Communication: Like problem mapping, this isn’t an ability unique to an AI PM. To be effective, all product managers should be superb communicators. Viable correspondence keeps on being a vital segment of AI-centered product management. Some AI specialists portray AI PMs as interpreters since they should connect the language of data science with the language of product development.
· Acceptance measures: An AI PM’s new measurement to focus on is AI precision (versus open bugs, for instance).
· Explainability: Trust plays a vital part in consumer loyalty and maintenance and, generally speaking, business achievement. Reasonable AI gives clients an understanding of AI dynamics. AI PMs are answerable for reasonableness and guaranteeing trust in a product.
· Ethics: For AI PMs, the moral utilization of AI should be a progressing thought and profound concern. AI and ML are useful assets; it’s up to an AI PM to recall (and here and there remind others) that with extraordinary force comes incredible duty.
· Evangelism: PMs should proselytize something beyond the product. They should likewise comprehend and advance the benefits of AI adoption to help their organizations stay serious in a bold, new AI world.
Now, you may be asking yourself, how to become an AI Product Manager? Here are some of the basic requirements that you need to have in order to get a job as an AI Product Manager.
AI is booming in the market. AI is being used in a lot of industries and organisations like banks, agriculture, healthcare, finance etc. You might have seen features on social media that allow you to tag faces automatically or even your phone password might be face unlock. These features also rely on the use of AI.
Software companies hire people with a strong AI background because AI requires robust knowledge of many software products. It is like a conventional toolbox that involves more than just business and technical strategies.
Here are six factors that you will need to become an AI Product Manager:
1. Knowledge and experience with Machine Learning and different AI concepts such as neural networks, computer vision, natural language processing, speech-to-text conversion clustering techniques, etc.
2. Learning and understanding mathematical concepts such as statistics, probability, distribution theories, and so on.
3. An intermediate-level understanding of AB testing, hypothesis testing, and model evaluation techniques.
4. Some degree of expertise in development processes for data science and Machine Learning.
5. Awareness and ongoing curiosity in regards to the industry, AI, and analytics trends.
6. Experience going through full product cycles. Those cycles include introduction, growth, maturity, and decline.
· Ensuring the success of new AI products by focusing on scalability, potential biases, and compliance.
· Evaluating the business impact of Machine Learning models.
· Developing business cases for AI in new and existing products.
· Formulating product requirements and identifying new opportunities with the help of customer feedback, market analysis, and usability studies.
· Collaborating with data scientists, data engineers, business stakeholders, etc.
· Building a multi-year strategy and roadmap for AI solutions.
Those were some of the basic requirements for you to be an AI Product Manager. But this job requires more than that. Also, the work environment involving the Product Manager is worth talking about. Most of the time, it starts by getting a couple of engineers and working with them to help ship something good to the customers, but a skill that you really want to layer onto your career would be “customer design-based thinking.”
Also, a major reality about a product role is that; you never get perfect. This means that you have to keep on working and seek that practical perfection. Another great thing about product roles is you’ll have a lot of responsibility and not a lot of authority.
To this question, there is no simple answer because it depends on a lot of factors such as which country you’re in, which part of the country you’re in, which company you’re in, etc. Let’s have a look at what the AI Product Managers at Silicon Valley get as it is one of the most expensive places in the world, which has some of the highest salaries in the tech industry. Now, the numbers are not going to be perfect, but it should give you a rough idea.
So, in general, an AI Product Manager makes 15-20% more than a generalist product manager. A little bit of this is because of the hype, a little bit because of the expertise, and a little bit because of the fact that a lot of revenue for certain consumer companies is driven by AI, which places you at the center of production. Also, the exact payment of an AI Product Manager depends on their level as well. Say you are a Senior Program Manager with 5 years of experience, you’ll be paid between $60k and $200k per year. This has a lot of exceptions depending upon a lot of factors.
The number one step to becoming an AI Product Manager is to choose the industry vertical where you want to be an AI Product Manager, as AI product management is a very broad concept. You’d want to narrow down the scope of which industry you’re targeting; do you want to be an AI Product Manager in financial tech or marketing tech or retail?
Step number two is within your chosen vertical you need to become the customer. This applies to product management in general. You should have that product sense, a natural intuition about what customers want. The way to do it is to talk and interact with your customers and analyze them.
Step number three is to design for the customers. As you become more like the customer, you’ll begin to see gaps, you’ll see opportunities, and you’ll be building a portfolio and some hands-on experiences being an AI Product Manager.
Step number four is getting familiar with AI tools and ML tools. Showing your wireframes to the recruiters is not going to impress them. You have to show them something high fidelity. A key point for an AI PM is to build for the customer, which means that you’ll have to familiarize yourself with algorithms, decision trees, neural networks.
Familiarizing with clustering algorithms, basics of natural language processing, understanding how the dictionary works will help you have the edge over anyone else.Finally, if you want to become an AI Product Manager just be an AI Product Manager. Just start doing what an AI Product Manager does, and then what those recruiters will see that you already are an AI Product Manager, that will be your ticket into landing your first paid full-time real opportunity as an AI Product Manager.
If you’re a data scientist, data analyst, product manager, UX designer, a marketer, AI is impacting the lives of everyone. In the end, honestly, many of us have interacted with some sort of chatbot or anything that just fails to perceive the intent as a user, and a lot of that might be driven by a product person that was trying to push something that was just unrealistic to accomplish in the first place.
Hence, it is important for a company to invest more of their time and funds to get an AI Product Manager that can help push the growth of the company in the right direction, and for a person who wants to be an AI Product Manager, it’s important to keep learning and keep growing. Let’s see what artificial intelligence brings us in the next ten years and how it will impact the different jobs associated with it.
If you wish to learn more about Product Management, our 6-month online PG Certificate Program in Product Management with IIM Indore is the reflect option for you! Check it out today.