Artificial intelligence has been considered a godsend to several industries today. Not only does it improve business productivity, but it also allows human resources to focus on creative endeavors instead of being stuck with monotonous work. If you have been looking to improve the operational efficiency of your business, chances are that you would have stumbled across an AI solution that could potentially revolutionize your business operations. However, since AI is still relatively new, implementing AI solutions can be extremely intimidating and challenging. In this article, we will take a look at how to implement Artificial Intelligence in your business. We will also discuss the various methods through which you can measure the impact of AI solutions.
Businesses are leveraging artificial intelligence through various approaches. In fact, global spending on cognitive and AI systems is expected to reach $57.6 billion this year. One of the most common business applications of AI is business intelligence, which involves the use of algorithms to identify trends and create insights from a company’s database. Using AI for business intelligence is expected to be one of the fastest-growing areas in the field over the next ten years. The benefits associated with the use of business intelligence include infrastructure cost reductions and enhancing operational efficiency.
Another popular method through which organizations are leveraging business intelligence is through the implementation of business dashboards. Many software companies are developing analytical dashboards that are capable of collecting data from other sources to help managers to make informed decisions. AI can also help optimize business management and enhance business security.
The applications of AI don’t stop here. Businesses have started using this emerging technology in several other areas as well. For example, AI solutions can also be used in business for-
One of the primary incentives for AI adoption by businesses is the advantage that they stand to gain over their rivals. However, there are many other drivers that come into play for AI adoption. Some of the main driving forces include:
Artificial intelligence solutions can go a long way in boosting customer engagement and retention, developing trust, and elevating levels of confidence exhibited by consumers towards a brand. Some of the major benefits that businesses observe after the integration of AI into their business operations include:
As a business owner, your primary concern during the adoption of new technology will be the risk that it poses for your business. AI adoption offers several benefits, but like most emerging technologies, there are some risks associated with it as well. Some of the limits and risks of AI use in business can prove to be:
Fortunately, there are a few practices that you can follow to mitigate these risks during AI transformation. While adopting an AI solution, makes sure to keep these points in mind:
Is there a particular process that you find inefficient or lacking? Are you facing a problem with customer service or employee productivity? It is important to clearly define the business problem that you are trying to solve by adopting an AI solution. This will help when you need to pitch the idea to the company’s stakeholders. Evaluating your business operations and understanding your needs and requirements is the most fundamental step in AI transformation.
During this step, it is also important to have an idea about the type of data you will be dealing with and whether this data can be used or not. For instance, consider a company that wants to improve its customer service with an AI solution. The first thing to consider is, will such a task be possible or not, based on the available data. This is quite different from traditional software implementations, where the main question is how the implementation will be carried out, not whether it is possible. This is because each business has its own unique set of data. The success or failure of AI implementation depends completely on this data.
After you have defined the project requirements, you will have to look into whether the project is feasible or not. This step will require a certain amount of AI knowledge and experience. This is why getting the help of an experienced AI development company will be a good idea. In this stage, research must be conducted using the data sets provided by the organization to develop several models that are able to verify the information that can be extracted from the supplied data. The solution that is developed in this step is not the final solution. It is merely a report that outlines the results of the study and the possible next steps for the project. It also offers a structure to the analyzed data.
After the feasibility study, you will be able to hone in on the aim behind your AI project. This is where you will look at what kind of data sets will be needed by the AI solution. Most companies don‘t have much clarity regarding their data, which may result in the poor performance of the AI algorithms. Gather your data from relevant sources and store it in a secure manner. Eventually, this data will need to be explored and transformed.
After the secure storage of the data, it is important to verify its coherence and validity. In some cases, there may be a few key characteristics that can be missing from the required data. Any issues or errors with the data must be eradicated in this step so that the accuracy of the final AI computations isn’t compromised. Also, data stratification should be verified against the data from the feasibility study.
After the audit results have been received, you will need to prepare the raw data for processing. This stage involves data categorization, selection of important features, scaling, dealing with missing information, and other operations that aim at the creation of complete, flawless data sets for the analysis. This is crucial to building accurate predictive models and ensuring high-quality output information.
The goal of the PoC is to describe the AI model, including its architecture and tuning, and prove the efficiency of the selected method. As an outcome, the PoC produces a report that provides guidelines for model implementation.
There is a major discrepancy between research into AI and the tangible results that businesses experience in the real world. This is why measuring the impact of an AI solution and defining the potential return on investment of the AI project is important. Generally, businesses measure this impact by developing a pro forma. Most service providers will offer pro forma development as a service included with ML and AI development. Essentially, a pro forma refers to a method of calculating financial results using certain projections or presumptions. Some of the primary practices that businesses use to measure ROI include:
Implementing artificial intelligence into business operations can be a very complex challenge. More often than not, you will need a reliable development partner to walk you through the process. If you are looking to implement an AI solution in your business, we can help you out. Reach out to us for a no-obligation consultation today.