How AI Can Help Improve Product Management
CIO Review
It has become more difficult for common people to understand powerful technologies like Artificial Intelligence (AI) and machine learning (ML) due to its hype. Here are a few tips that can help product managers to understand how AI can help in regular life.
As a product manager, it is necessary to understand the problem space so that it becomes easy for them to accurately define the requirements and allow the team to solve the issue. Most of the products on which the product managers have to work need decision-making based on data, although the process of making decisions might vary from time to time. For example, the decisions can be made by humans or machines, and the data can be dynamic or statistic. The priority on decision-making abstracts away the details of particular methodologies noise of industries. Such a wide range of definitions helps the product managers become more attentive towards the problem space and reduce distractions that might force them to think about solutions at an early stage of the procedure.
Here are three primary concepts that can help as the groundwork of everything that the product managers do.
. Tactic- Doing things accurately so that it becomes easy to execute the strategy
. Vision- The end goal which the product managers try to accomplish
. Strategy- Doing the correct thing to realize their vision
The product managers must operate every three levels at any given time, depending on the product lifecycle. They must align the teams to the vision they are trying to accomplish while confirming that every individual understands the strategy and how their daily operational system fits with the entire plan. It is also necessary to remember that AI is a technique that can be utilized for solving specific issues rather than a strategy or vision. Implementing AI without any end objective will not bring any value to the end-users.
Top 3 Ways AI Is Improving Energy Sector in 2020:
With the advancements in technology, the renewable energy sector has made significant progress in the past decade. Technologies like the AI and Machine Learning can analyze the past, optimize the present, and predict the future. The energy industry needs smart systems that can help increase the combination of renewable into the existing grid and make renewable energy an even player in the energy supply.
AI helps with the integration of microgrids and manages the distributed energy. When community-level renewable energy generation units are summed to the primary grid, it becomes tough to balance the energy flow. The AI-powered control system plays a significant role in solving the quality and congestion issues.
Expansion in Market
AI helps in renewable energy suppliers to expand the marketplace by including new service models and encouraging higher participation. AI-powered systems help to analyze the data related to energy collection and offer insights on energy consumption. The data would help the suppliers to optimize the existing services and launch a new set of service models. It also helps retail suppliers to target new customer markets.
Smart and Centralized Control Centers
The energy grid can be combined with tools and sensors to collect a massive amount of data. Smart and centralized control centers, combined with AI, give the data new insights to the grid operators for better control operations. It also offers flexibility to the energy suppliers to cleverly adjust the supply with the demand. The improved load control systems can be installed with tools like industrial furnaces or large AC units that automatically switch off when the power supply is low. Along with this, the intelligent storage units can be adjusted based on the flow of supply.
Additionally, smart machines and advanced sensors can make weather and load predictions that can overall improve the integration and efficiency of renewable energy.
