5 Steps of Artificial Intelligence to Attain Success to Your Business

It is clear that artificial intelligence (AI) is a growing force in the tech industry. Artificial intelligence is taking center stage at conferences and showing its potential in a variety of industries, including retail and manufacturing. New products are included with virtual assistants, while chat bots answer customer questions about everything from your online office supplier website to your web hosting provider's support page. Meanwhile, companies like Google, Microsoft, and Salesforce are integrating AI as an intelligence layer across their entire technology suite. Yes, artificial intelligence is definitely having its moments.

This is not the artificial intelligence that popular culture has expected of us; It's not even conscious bots, Skynet's assistant, or Tony Stark's Jarvis. This AI plateau is happening below the surface, making our current technology smarter and unleashing the power of all the data-collecting organizations. What it means: Huge advances in machine learning (ML), computer vision, deep learning, and natural language processing (NLP) make it easier than ever to bake an AI algorithm layer into your software or cloud platform.

For businesses, practical AI applications can emerge in every way depending on your organizational needs and business intelligence (BI) insights derived from the data you collect. When it comes to asset tracking and management, organizations can use AI to improve logistics and efficiency, from extracting social data to increasing engagement with customer relationship management (CRM).

1. AI get to know me

Take the time to learn what modern AI can do. Techcode Accelerator provides its startups with a wide range of artificial intelligence resources through its partnerships with organizations such as Stanford University and corporations. You should also make use of the information and resources available online to learn about the basic concepts of AI.

2. Select the problems you want to solve using AI

Once you are aware of the basics, the next step for any business is to start exploring different ideas. Think about how you can add AI capabilities to your existing products and services. Most importantly, your company should consider specific use cases in which AI can solve business problems or provide demonstrable value.

3. Give priority to the solid value

Next, you need to assess the potential commercial and financial value of the various potential AI applications that you have identified. It's easy to get lost in discussions of AI "pies in the sky," but Tang stresses the importance of linking your initiative directly to the value of the business.

"This should help you set priorities based on near-term vision and knowledge of the company's financial value. At this point, you usually need ownership and recognition from senior managers and executives. It happens."

4. Bring in experts and prepare a pilot project

Once your business is organizationally and technically ready, it's time to start building and integrating. The most important factors here are to start small, keeping in mind the goals of the project, and most importantly, being aware of what you know and don't know about AI. This is where bringing in external experts or AI consultants can be invaluable.

5. Forming a data integration team

Before implementing ML in your work, you need to clean up your data to prepare it to avoid a "garbage in, out" scenario. “Internal company data is typically spread across multiple data warehouses for different legacy systems, and may also be in the hands of different workgroups with different priorities.” And it's a very important step toward creating a cross-functional [business unit] workforce, integrating various data sets together, and removing inconsistencies so that data is accurate and rich, with all the right dimensions required for machine learning. "