5 Tips To Create An Effective AI Implementation Strategy

AI Implementation: How To Make The Most Of It

From automating administrative tasks and personalizing learning experiences to performing complex performance analyses, there is almost no limit to what Artificial Intelligence can achieve. At the same time, if your organization doesn’t have a solid implementation plan in place, chances are the results you get will be lesser than expected. In fact, many businesses witness a very small ROI on their AI projects simply because they haven’t realized that algorithms still need human direction. To ensure the success of your AI implementation strategy, we share 5 tips to help you lay the right foundations from day one.

Implementing AI In Your Organization In 5 Easy Steps

1. Perform Thorough Research

AI can have multiple uses in an organization, such as employee development, scheduling, reporting, forecasting, and resource management, to name a few. However, the type of AI that’s going to accompany each operation and ensure its success can differ. For example, you can use supervised or unsupervised machine learning to achieve data mining. This type of ML functions by “feeding” the algorithm a set of sample information so that it can find matches in your database. On the other hand, forecasting functions require reinforcement learning algorithms which are better at interacting with their environment, learning from their mistakes, and making predictions. AI is evolving fast, and it’s essential that you research enough to know which option is better for what you want to achieve and how much training, direction, and redirection it’s going to require.

2. Define Your Problem Areas And Set Goals

Once you have a firm grasp of AI’s capabilities and limitations, you can kick off your implementation strategy by setting goals. The first step is, of course, identifying problems you can solve by utilizing Artificial Intelligence. Evaluate your organization’s processes, workflows, and data, and pinpoint areas with clear-cut data and existing technology that can easily transition to AI. You can even conduct a training needs analysis if you discover that some of the problems reside in your L&D program to dive deeper. Starting with simpler, more achievable goals helps you dip your toes into the already complex technology of AI. Specifically, being able to measure the results of your AI project in a short amount of time allows you to easily gauge ROI and make adjustments without putting a big dent in your budget. Once you get the hang of it, you can move on to goals with a longer implementation schedule.

3. Assemble A Team Of AI Rockstars

Your AI project will have no future without an experienced and talented team to train, run, and control it. Keep in mind that an AI team must be versatile and include many different professionals, from data modelers and engineers to business analysts and graphic designers. Make sure that they are properly trained and have what it takes to not only get your system up and running but also maintain it and deal with unexpected problems. Finding such a team is a challenge on its own, as there is an AI talent scarcity. There are various choices you can explore here, such as outsourcing or in-house training. You can also participate in boot camps and conferences, where you can find and attract potential candidates.

4. Evaluate Your Tools

Artificial Intelligence is very demanding when it comes to system requirements. Therefore, a crucial step in your AI implementation strategy is appraising your existing tools to figure out if they are up to the challenge. Implementing AI programs relies on three essential factors. First, you need a tool that can successfully develop, run, and maintain AI software. Secondly, you must have an abundance of data and the tools to prepare them for training the algorithm. Finally, you need adequate storage resources, preferably in the cloud, so that all your data and machine learning models are organized and readily available. Missing any of these factors can seriously affect your AI readiness. Therefore, before you move forward, make sure to upgrade your IT equipment.

5. Start Small

We mentioned earlier that your chances of a successful transition into AI become significantly higher when you start from easily achievable goals. Let’s look a little deeper into that. Research has shown that almost half of AI projects never go past the prototype stage and into production. This could be because the initial idea was too ambitious and the tools for its mass production are too complicated or have not yet been created. Although the speed with which technology evolves allows us to dream bigger, it’s important to function within our means, at least during our first steps. Start your AI project with a thorough implementation plan which will give you measurable results fairly quickly. This way, you can safely learn from your mistakes and plan your next steps accordingly.

Transform Your Organization

Effectively utilizing Artificial Intelligence can help you realize your goals and achieve your KPIs faster than you ever thought possible. The future calls for technology-based entrepreneurship, and AI is one of the best ways to accomplish it. Follow the tips we shared in this article and create an AI implementation strategy that will certainly make the most out of your investment and bring your organization into a new era.