How to incorporate ML & AI services in budget?

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How to incorporate ML & AI services in budget?

Modern technologies like artificial intelligence and machine learning are laying a massive positive impact on businesses today. It seems that incorporating these cutting-edge technologies to business has become vital for success. Can small and medium-sized enterprises implement AI and ML? The answer is ‘Yes,’ they can apply these technologies with a careful budget and detailed plan. Here is a list of valuable tips for small and medium-sized companies to incorporate AI/ML on a budget.


  1. Identify the problem you want to solve with AI/ML:

The first thing you need to know is to know the problem you want to solve with  ML & AI services. One should start with a small investment to deal with the problem. Determine the financial value of these technologies for your company.


  1. Start with non-core functions:

Not only the core functions of the business like the expertise, big budgets, and focus but also the non-core functions like the quality of work of an employee should be kept in mind while determining the objects of implementing AI/ML. These non-core functions can bring significant improvement to your company. 


  1. Identify how you will measure success:

It would be beneficial if you implement these technologies in the areas that provide the most ROI to your enterprise. Ask yourself these questions to determine your reasons and assess your success.

  •       What are you hoping to get by these technologies?
  •       How are you going to measure your success?

Answers to these questions will help you track your progress. You will also know the areas of improvement. These goals will give clarity to the areas that require AI/ML in your business.


  1. Get support from your team:

ML & AI services cannot do wonders overnight. It’s a difficult task to integrate these services with daily operations. You can start by handing a prominent problem with the help of these technologies, and observe your win record to make your employees motivated. Afterward, you can implement it to increase the ROI and for other projects.


  1. Look at proven use cases:

ML & AI services can be a waste of time and money without considering the value of the outcomes. You must go through the proven use cases inside the industry, where the value has already been shown.


  1. Develop a risk management strategy:

AI can identify the most significant risk sources and prioritize gaps for remediation. As we know that cybersecurity is no longer a human-scale problem. In short, a business can maximize risk reduction with minimal resources and effort with the help of AI services.


  1. Ensure you have well-defined data:

Before bringing AI/ML into your company, ensure you have extremely well-defined data and rules to be used as the basis to build out an AI or ML system.


  1. Take a plug-and-play, modular approach:

An end-to-end partner offers modular solutions. It helps you minimize initial investment, implementation risk, and ramp time by integrating this technology into one or two key business areas. Use services that are designed to work with your existing systems for a smooth transition.


  1. Start with a low-risk ml pilot study:

You can start by getting started with a low-risk machine learning pilot study to save money. You can use ML for data classification and organization. It is low risk and simple to implement. Yet, it can still save lots of time from analysts.


  1. Leverage open-source tools:

AI/ML has a lot of open-source tools. It takes less than a day to create chatbots and to train an engine to classify images and comments. You can start small by using open source tools and run small experiments.


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