Sitting on Diamond Data? 4 Steps to Getting Started with AI for Business

Most companies are data-driven, but not all data is made the same. There are different levels of value to be gained from available data—and getting the most out of it can be difficult. While artificial intelligence (AI) has helped us analyze and understand data better, it has yet to be effectively utilized at scale. AI adoption has been slow as it’s still not easily accessible for most businesses.. 

However, software developments and end-to-end platforms are making it easier to bring the value of AI to more companies by making it a viable opportunity for more businesses. The implementation results are already being felt: 63% of businessesOpens a new window reported an increase in revenue, and 44% of companies reported a reduction in costs from using AI. When these figures combine, it’s easy to see that AI software can be a worthy investment. 

AI tailored for the business world means we can move past the traditional image and text models regarding data. Instead, we can start using its capabilities to predict finances and churn rates, for example, and use AI to help humans make better-informed decisions. Each business is unique, so end-to-end platforms make it possible to design data dashboards specifically for each company’s needs. 

If you’ve wondered how AI could benefit your business, here’s how to get started. 

Understanding the problem 

Many companies don’t understand their problems, and this is especially true when it comes to the way they conduct data analysis.

Having data is one thing; understanding it is another. If you have a lot of data and metrics but are unsure what to do or how best to use them, working with an AI platform can help maximize your available resources. It’s the difference between getting diamonds from your data and something more primitive: Applying AI to metrics means better quality insights. 

For example, an office and studio rental agency might employ data insights to see what type of businesses are renting and how their spaces are being used. An AI-powered data dashboard could correlate information, inform what kind of rentals are grouped, and help optimize services by knowing their customers. These data-driven insights make it easier to boost what is working and cut what isn’t. 

Knowing your data 

When AI is tailored for business, possibilities open up as people across departments can utilize it. One of the biggest challenges to AI adoption is that small businesses, in particular, cannot afford to hire their own data analysts or any other data-specific role. Instead of an analyst, platform APIs (application program interfaces) work with existing CMS (content management systems) in end-to-end solutions to drive value from what you already have. 

AI’s ability to store and correlate large quantities and varieties of information makes it able to analyze customer patterns and behavior shrewdly. This is especially important in eCommerce, for example. Sites like Amazon or Etsy can use AI to determine if a customer is more likely to value shipping time over price. Knowing if the customer would be happy to wait a week for a cheaper product helps the algorithm decide which product to show the customer first. AI is there to help present customers are most t likely to close the deal. 

Applying AI for better insights

For businesses looking to optimize their production, AI can guide precise prediction lines, innovate faster, and deliver an actual product—rather than end up with something no one asked for. This is excellent news for startups looking for product-market fit quickly as real-time data provides more effective help with speedier testing and feedback cycles.

The ability to analyze data at scale means AI helps find optimum choices. As such, more and more companies are being created out of an AI algorithm to fix real-world problems. Trucking companies with fleets are a good example of AI maximizing fleet logistics and optimization. In the transportation industry, for instance, AI uses real-time data on maintenance cycles and the lowest petrol prices available, which can inform route choices. 

AI can also improve user experience (UX) and innovate industry offerings. For example, AI can combine amalgamated real estate website data with personal preference information such as hobbies or potential school requirements to offer users more personalized choices and help close the deal. AI can also analyze real estate photos to see renovation works or match listings with other user criteria that might not be included in the post metadata. As a result, the user experience is seamless, and they can view more options from a broader range of sources. 

How you apply AI will depend on your industry and the products and services you’re offering. Using digital tools, like an end-to-end AI platform, means companies can better understand the data they already have and how to create actionable insights and an improved customer experience from it. 

See More: Doubling Down on AI: Three Powerful Strategies

Overcoming adoption challenges 

Currently, however, there’s no protocol for how best to use AI. Various companies are creating disparate solutions, but using many providers can make life hard for businesses as it’s challenging to connect these dots. Likewise, only 54% of customersOpens a new window say they trust companies to use AI in a beneficial way for consumers. Software developments and end-to-end platforms are making adopting and applying AI more accessible and giving companies more control over their data. 

Knowing the value of AI will also come when businesses measure the impact of implementation. Companies should first measure a process or metric (e.g., eCommerce conversion rate) without AI to create a baseline and then test and build from there. It’s best to work with one small improvement at a time to see if it’s working or not. Simple feedback surveys from staff and customers on their experience will ensure AI meets user needs and expectations. 

AI adoption has proven its worth. Now, there needs to be more focus on helping scale solutions for smaller companies. Greater adoption will come with education on the available tools and how to use them. Companies should know that end-to-end platforms, which utilize existing data and have user-friendly interfaces, are already there for those ready to try. 

Do you need to incorporate AI into your business? Have you diagnosed it yet? Let us know on FacebookOpens a new window , TwitterOpens a new window , and LinkedInOpens a new window . 

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