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Hackernoon logoAI-driven Features with the Highest Potential for Enterprise Development by@arinakarataeva

AI-driven Features with the Highest Potential for Enterprise Development

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@arinakarataevaArina Karataeva

Marketing Manager at Exposit

Enterprise players across all industries are eager for optimization and improvement of their business processes: administration, customer service, marketing, sales, recruiting, and others. Today AI-driven software can cover the most common Enterprise needs like data security, data processing, resource optimization, and brand awareness. Forrester has reported that AI is also able to improve customer service and quality of existing products, increase revenue streams, and customer lifetime value.

Together with Exposit Machine Learning experts, we have selected AI-driven features with the highest potential in Enterprise business processes improvement. 

AI-driven features with the highest potential in Enterprise business processes improvement:

  • Big Data processing 
  • Advanced analytics
  • Workflow automation
  • Monitoring data
  • Optimal matchmaking
  • Big Data processing 

Machine Learning algorithms can easily deal with data processing including images, videos, and audio. Depending on your needs, a pre-trained ML model can classify, recognize, group or describe objects or patterns based on the parameters you have set before. For example, AI can analyze product photos uploaded to an online store considering size, shape, color, and so on. This data helps algorithms to identify the right category for a product and automatically send it there. 

Analytics

AI can provide you with advanced analytics thanks to its unique ability for data processing. It can store and process huge amounts of data visualizing the results in the most convenient form. You can choose from tables, charts, diagrams or create your own form of data visualization. If your application has a dashboard with the most important insights, AI can automatically send daily reports to it and update them in real-time. 

Machine Learning algorithms can cover the majority of financial and marketing analytical tasks including predictive, descriptive, prescriptive, and diagnostic analytics. Detailed AI-generated reports can give you valuable insights that you haven’t considered before and use this data to improve your business strategy. 

Workflow automation

AI allows businesses to automate daily working processes including documentation workflow, data filling, and template creation. It helps to optimize time and money and boost the productivity of HR, PM, administration, and other departments. You can implement a virtual assistant similar to Amazon’s Alexa and train it to perform daily working tasks like calendaring, scheduling, business correspondence, or other required activity.  

Delegating tedious work to AI also helps you to achieve the maximum accuracy in records management because it reduces human errors. It can work 24/7 retaining the same productivity and effectiveness.  The most important thing you should care about is the previously gathered data used for training ML algorithms. You should provide algorithms with the relevant data and focus training on the specific purpose for the best-case result. Remember that the more data provides the better-trained model and better results.  

Monitoring 

You can use listening and monitoring tools for different purposes depending on business needs. For example, Artificial Intelligence can perform monitoring of pricing policy in your industry. Algorithms can process prices offered by your competitors and identify retailers that initiate increasing or decreasing market prices. It will help you to stay aware of the price change and build advanced sales strategies based on the latest data.  

Another monitoring option is tracking your brand across the Internet resources including social media, blogs, e-shops and so on. It can help you to stay informed about the feedback of your products and services as well as of possible customer complaints. Real-time notifications will help to speed up responding to messages across your social media channels and never miss an important mention. 

Matchmaking

AI-powered matchmaking brings personalization opportunities to your business improving marketing, shopping, design and even recruiting. Well-trained Machine Learning algorithms have great potential in pattern recognition and Big Data analytics. AI can process more than one hundred criteria considering historical data to suggest the most suitable decision for you. 

For example, you have to find a relevant specialist for your project ASAP. You can provide AI with the necessary criteria of the ideal candidate including skills, character and other specific preferences. As a result, ML model will create a profile of a perfect candidate as well as find the most relevant one of the proposed. 

AI adoption for Enterprises

AI adoption itself often becomes challenging for businesses. Usually, it happens due to the lack of information and the legacy of IT infrastructure. You need to consider several things before you start working on developing an ML Enterprise solution:

  • Determine business goals and needs that you want AI to cover.
  • Determine whether you have enough data for processing for training algorithms.
  • Find a reliable ML software development partner.

A clear understanding of these 3 factors is a foundation for building an effective ML solution development process. Usually, the Machine Learning implementation process includes 6 main steps: 

  • Business understanding
    A stage where you determine what business tasks you need to solve using Machine Learning algorithms.
  • Data understanding
    A stage for a closer look at the data available for training Machine Learning model.
  • Data preparation
    A stage for converting and cleaning data for modeling.
  • Modeling and training
    A stage to apply various models and select the most suitable parameters.
  • Evaluation
    A verification stage to analyze whether a model can cover your business needs.
  • Deployment
    Implementation of Machine Learning model in business processes.

Cut through the hype and use AI opportunities suitable for your business

There are plenty of opportunities on how to use AI in your business processes: trained machine learning algorithms, computer vision, natural language processing, robotics, and more.

Take your time to consider what AI-powered approach will work best for your business to boost productivity and increase sales. 

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