6 Tips for Building a Successful AI

Artificial Intelligence (AI) has become the buzzword of the 21st century. It is a hot topic at IT conferences and IT magazines are often brimming with the latest AI news. If you are a business owner you have undoubtedly wondered if or how AI can benefit your business. But where do you start? You should have a better idea after reading our tips for building a successful AI project below.

1. Learn more about AI

If what you know about AI and Machine Learning is limited to what you read in the Sunday newspapers, you should first brush up on your AI knowledge before making anything even resembling a decision. At least familiarize yourself with basic AI concepts by taking advantage of the massive amount of online resources, courses, and remote workshops available.

2. Be realistic

Do not get caught up in the hype surrounding AI. Instead of trying to replace your CEO with an AI bot, rather consider using AI to streamline the firm’s decisionmaking processes by ensuring they are based on reliable data.

A recent study of 152 AI projects showed that overly ambitious moon shots are more likely to fail than ones going for ‘low-hanging fruit’ that aim to improve business processes.

3. Identify exactly what you want to achieve by using AI or Machine Learning

This is where you start getting specific. Think about ways in which you can add AI functionality to improve existing company services and products. Areas in which AI are currently being used with significant success include: analyzing large amounts of data to determine underlying trends, chatbots, virtual assistants, farming and agriculture, shopping, retail, fashion, autonomous flying, surveillance and security, sports analytics, production and manufacturing, inventory management and livestock, self-driving vehicles, medical imaging analysis, healthcare, logistics, and warehousing.

4. Get your priorities straight

With AI it’s easy to get lost in your own dreams. Never forget the bottom line: something that costs the business money should deliver tangible rewards. When having to choose between a similar priced AI powered receptionist that looks like Miss Universe and a rather dull AI driven data analytics tool that can save the firm large amounts of money by streamlining its inventory control systems, follow the numbers. And no, we don’t mean 36-24-36.

5. Know what you can do in-house and what needs to be outsourced

Once you have a better idea of what you hope to achieve with an AI project, you need to take stock of the resources you already have in-house in terms of staff, expertise, data, hardware, software, and more. This will help you to determine what resources should be sourced externally. Chances are good that you will need the help of an AI consultant to help you with this.

6. Start small

Instead of jumping into an AI project head over heels. If you are setting up a data analysis project, start by applying AI to a relatively small data sample. Call it a trial run or a pilot project if you like. Select a particular problem you want the AI to solve. Feed it the necessary data, and then ask it to answer a very specific question. You will learn more from than by bombarding the AI with a massive amount of data right from the start.

Analise the results and adjust the algorithms where necessary. Using the help of an AI consultant at this stage is probably better than trying to save a few dollars.

Have a question?

Drop us a line and we will get back to you