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Everything You Need To Know About Starting An AI Program In Your Technology Business

Artificial Intelligence, or in short, AI, has been the talk of the town for quite some time now. These days, tech giants like Microsoft, Salesforce, and Google are coming up with ways to integrate AI and use it as a layer across the entire technology stack. From an AI website hosting service that tracks office supplies digitally to AI-powered virtual assistants and chatbots, businesses are looking for ways to leverage the power of AI.

However, one must realize that the scope of AI is diverse, and to make the most of a technology business, it is important to take a step-by-step approach. This article will cover all that you need to know about starting an AI program for your technology business.

Step 1: Familiarise Yourself With AI

The scope of artificial intelligence is diverse, and you need to know its functionalities before you get down to its implementation. There is an ocean of AI-related information available online. It is a good idea for a business owner to learn predictive analytics, machine learning, and other basic AI concepts through remote workshops and virtual lectures. This will help them figure out what works for them and what does not and plan how to create an AI program tailored for their organization.

Step 2:  Identify the Business Problems that AI can Solve

Once you have strengthened your core concepts, the next step is evaluating your current business model and identifying flaws. Then sit back and evaluate how AI capabilities can solve these problems. Research on use cases to find out how image recognition, natural language processing, or other AI techniques can provide demonstrable value to you and solve unique problems to your business or industry.

Step 3: Arrange Solution Value in Order of Priority

Before you set out on the practical implementation of AI solutions, evaluate its financial feasibility. Ideally, you can create a 2X2 matrix with the solution’s potential and its feasibility as the two parameters. That way, you will prioritize near-term visibility and know what you are getting into before making the jump to AI.

Step 4: Set Up a Pilot Project

Understand that no matter how well you do your homework, you cannot expect to take complete charge of your AI project right from day one. While it is important to know the basics, having a clear goal and inputs from an AI consultant will help in a successful pilot project.

Have a small goal, a tight deadline, and a small team as your business steps into its maiden AI project. For best results, your team should be a heterogeneous group of people who know your business and those who are well-versed in AI technologies. The success of your pilot project is important as that will give you the confidence to make longer strides in Artificial Intelligence.

Step 5: Systematically Arrange Your Data

If your business has been in place for some time, the chances are that your corporate data is unsystematically placed across multiple legacy systems. Before you set out on a full-scale machine learning solution for your business, it is important to have your papers in order. Create a dedicated multi-business-unit taskforce that identifies data inconsistencies from multiple sources and assimilates them into a collective unit.

Step 6: Take an Incremental Approach

The ideal approach for AI implementation in business is to start small and work on feedback as you incrementally increase the scope of operation. For example, you can start AI implementation by the machine learning system’s direction to solve a certain problem on a small data set. When you are satisfied with the result, gradually increase the data set’s size to get the results you expect.

Step 7: Do Not Ignore Storage

As you gradually scale up your AI systems, you need to be prepared to deal with large data volumes. As AI continues to evolve, you can expect better algorithms that give more accurate results. However, the results’ accuracy can improve only when the system has access to a larger data pool.

As a business looking to make the most of AI, you need to consider the AI system’s storage aspect. Spend some time reading up on what is cloud storage, ways of cost-effective storage systems, etc. Having a fast, optimized storage system right from the initial days of your AI implementation will help you develop a workflow model that can easily scale up to meet your business needs.

Step 8: Build a Balanced System

As one of the last stages of AI implementation, balancing is perhaps the most crucial one. Here, you need to ensure that the AI system you are envisioning is synchronized with the features and limitations of the software you intend to use.  When used with the latest advanced AI algorithm, low-end hardware or software will give a dysfunctional result.

Based on your budget, requirements, and upskilling goals, make sure that you develop a system that strikes a balance and helps you achieve the desired goals. Ideally, you should use anti-malware tools, VPN connection, and high-level data encryption in your bid to create a balanced system. Ensuring that your system has the required graphic processing unit, networking, and storage bandwidth are other important steps in this regard.

Step 9: Incorporate AI as A Part of the New Normal

If you are an already established business, you should be prepared for some of your employees retaliating against AI’s introduction in your business. Understand that this hesitation comes from a fear that technology may replace their jobs. As a business owner, you need to walk the extra mile and explain how your AI solutions will only augment their daily tasks and not replace them altogether.

As far as possible, be transparent in explaining to your employees how your AI solutions work and how your business stands to benefit from its implementation. Realize that your employees are the biggest asset of your business, and having them be comfortable with your AI program is important for the organization’s success.

With this step-by-step approach, you now have a clear roadmap for implementing AI in your technology business. Doing so will involve a great deal of research and commitment from your entire team. However, if you follow these steps in a disciplined manner, you will be able to steer your business’s success story in a positive direction.



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