6 steps to adopting AI for your business

Now, more than ever, businesses need to utilize artificial intelligence (AI) software solutions if they are going to succeed. AI-powered business solutions can assist with an array of functions, ultimately helping reduce the time it takes to get your product on the market and into the hands of your customers. AI business solutions are no longer specific to certain industries or sectors of the economy—their potential uses span the entire business world.

Now, more than ever, businesses need to utilize artificial intelligence (AI) software solutions if they are going to succeed. AI-powered business solutions can assist with an array of functions, ultimately helping reduce the time it takes to get your product on the market and into the hands of your customers. AI business solutions are no longer specific to certain industries or sectors of the economy—their potential uses span the entire business world.

What does that mean for your business? Simply put, you must develop a robust understanding of how you can use AI, along with the steps it takes to integrate AI into your operations. At Codal, we help businesses launch AI solutions that fit their unique technical challenges and goals. Keep reading to learn about common AI use cases, key steps to adopting AI solutions, and how Codal helps businesses leverage this powerful new technology for greater productivity, efficiency, and scalability.

AI use cases

AI’s rapid expansion means that the only limits to its potential uses are the limits of human imagination. Consider the following:

• AI is expected to grow at a rate of 37.3% per year, every year, until 2030.

• AI may create up to 97 million jobs.

• Surveys show that 60% of businesses believe AI will increase productivity and improve customer relationships, while 97% believe programs like ChatGPT will help businesses.

As a result of this explosion in AI adoption, many businesses have begun to explore numerous types of use cases for AI. These include task automation, natural language processing (NLP), predictive analytics, chatbots, and machine learning.

Task automation

AI is more than capable of handling numerous automated tasks, allowing you to redirect staff time to more productive or creative jobs. Potential tasks ripe for include data entry and analysis, certain types of manufacturing, transportation, and code creation.

Natural language processing

Natural language processing (NLP) is a discipline of computer science that ensures computers can read, understand, and communicate text like humans. With appropriate NLP tools, the sky is the limit for AI programs, as they can interact with customers, solve problems, and ensure that team members can pursue more productive areas of business.

Predictive analytics

Predictive analytics enables you to use data to project into the future. Combined with AI, the power of predictive analytics grows exponentially. With the help of AI , you can incorporate additional data sources, increase the accuracy of your predictions, and extrapolate well into the future.

Chatbots

Chatbots have been around for years. These automated chat tools have long been deployed on websites so businesses can better triage and solve customer problems. Thanks to advances in NLP, chatbots are becoming more effective and may no longer need human intervention to get the answers that customers need.

Machine learning

Machine learning refers to the ability of computers to use data and algorithms to learn and adapt to human needs. Machine learning capabilities can be particularly important for AI. For example, when deployed appropriately, machine learning can , deploy dynamic pricing , and help identify items or services a customer may need before they realize they need it.

Steps to adopting AI

All businesses have different AI-related needs and follow their own pattern when adopting AI solutions. However, generally speaking, you will need to engage in a systematic, step-by-step process to better understand your business and maximize the potential business cases for AI. One example of such a step-by-step process is as follows:

Understand AI

Perhaps the greatest challenge with AI is understanding how it can help your business and what it is in all of its forms. By now, you have almost certainly heard of , the generative AI tool that can create a vast array of content. However, AI comes in many different forms that can assist with customer service, business analytics, quality control, and much more. You’ll need to figure out how these variations can assist your business.

Identify business problems and use cases

Every business has unique challenges that need improvement. Once you have identified the types of AI available, you can determine specific use cases for AI . For example, is your business struggling to launch an eCommerce website? Create an engaging UI text persona to manage customer service. Improve workflow solutions? AI can help you identify a process to streamline responsiveness and increase efficiency.

Regardless of your challenge, there is an AI-related answer—so long as you have access to the right tools and expertise.

Perform a qualitative and quantitative analysis of your data

AI can only work based on the data that you can use. This means that you have to analyze the data you have to appropriately flesh out how to adapt AI to suit your business needs.

To that end, you will need to perform a qualitative or quantitative analysis of your data.

Qualitative analysis refers to developing an understanding of the data that numbers can’t explain. This can include data’s robustness, accuracy, and applicability, and how it can help you perform certain business functions. The type of qualitative analysis you perform ultimately depends on the nature of your data, the types of AI you may want to utilize, and the specific business problems you are trying to solve.

For example, have you used your data to identify patterns and want AI to take you to the next level? Content or pattern analysis may be the best way to go. Looking to see how data may fall into certain categories and how those categories apply to your business? Thematic analysis may be necessary.

Quantitative analysis refers to numbers. To narrow that down, you can use quantitative analysis to create models based on measurements and experiments. This type of analysis can help you identify problems, create solutions, and better understand what data you have. Quantitative analysis can also help you find gaps in your data. For example, let’s say you are in the agricultural sector and are looking to understand weather patterns. Quantitative analysis can help you find what data you are missing, what data you may need, and how that data may help you better refine your business services.

Performing either type of analysis before implementing an AI solution can help you better understand the nature of your data. By conducting your analysis, you can see where the gaps in your data exist and, more specifically, tailor an AI-driven solution to your needs.

Implement specific solutions and build out a proof of concept

If you have followed these instructions, you now understand what AI can do for you, how it can help your business, and what data you need. From there, you can begin to implement specific AI-based solutions. These solutions may involve using existing AI platforms or creating your platform to fill your business needs.

You will need to create a proof of concept. A proof of concept is the demonstration of how an AI platform you designed or purchased can help with a specific solution. For example, let’s say you operated a business in the behavioral healthcare space and were looking to identify a program that analyzed the risk of a patient decompensating or experiencing a major behavioral health crisis based on their specific quotes to therapists. In that case, a proof of concept could be developed that would be fed notes from actual therapy sessions and tasked with a risk level for each patient. The program could be tested based on the comments that other patients had given to their therapists, with risk results compared to actual outcomes.

In the above example, the proof of concept shows how AI can be implemented and what problems it will solve. Ideally, a proof of concept will also help you identify specific challenges to the proposed solution. For example, the above program may work well but fail to adjust for cultural or linguistic differences. In that instance, you would need to alter and refine your proof of concept and implement an improved idea that will work for all patients.

Measure, measure, measure

Improvement without measurement and data analytics isn’t possible. Your business must understand the measurements you’re looking to improve.

Ultimately, AI can have a series of different impacts on your business, such as increasing revenue, saving money, or improving efficiency. You will need to develop appropriate tools to track this data and ensure that AI has the desired effect on your business.

Invest in learning and training

AI is more than building code and data; it is also about people. Your business must invest in the necessary programming and training to enable your entire team to take advantage of this new technology. You will also need to build a culture that views AI as an opportunity—not a threat. With the right training, you can reorient your entire business model around this way of thinking.

What can Codal do for you?

If you need AI solutions for your business, you’ve come to the right place. At Codal, we help deploy AI-powered business solutions to ensure companies can utilize AI for a limitless range of services.

Our approach is based on four defining principles:

• Business-led: Our goal isn’t to sell you a specific product, service, or solution. Instead, it’s to help you find what works best for your business needs and goals. Our first job is to understand what you want to do and follow the above processes to determine how AI can help your business. From there, we partner with you to identify the right AI solutions to meet those needs.

• Data-driven: The best operating AI algorithms are based on the right data, and we want to ensure you have all of the data you need to succeed. We work with you to examine, refine, and perfect your data. Don’t have the data you need? No problem: we can provide technical advice to help you acquire whatever data sets you need.

• Tech-agnostic: We don’t have a preferred AI technology. Instead, we work with your team to find the best tech for your business. This may mean any number of AI platforms, including, but not limited to, AWS Bedrock, ChatGPT, and Azure ML. Furthermore, as a company leading the way in this field, we know the AI space is rapidly changing. We keep up with the latest AI trends so you don’t have to, and if there’s a new solution you need, we’ll find it together.

• Collaborative: We believe that AI is most successful when it’s used to collaborate with humans—not replace them. We work with your team to integrate AI into your business processes, increasing the efficiency, effectiveness, and profitability of your operations. AI can do jobs that humans can’t, freeing your team up for more profitable and productive tasks.

The right approach to adopting AI for your business

Your business may benefit from incorporating any number of AI tools. We specialize in implementing a series of deeply impactful and customizable tools, helping our clients:

• Automate time-consuming and redundant tasks such as data entry, freeing up employees to focus on more complex issues.

• Implement chatbots to enhance customer service and the overall customer experience.

• Identify fraud to prevent financial losses.

• Personalize marketing campaigns to increase customer engagement.

• Improve product recommendations to boost sales on eCommerce sites.

• Forecast demand to reduce inventory costs.

Codal is more than just a consultant: We lead the way, and we do so while following your leads. We aim to incorporate solutions that fit your needs, not just change your operations to be more responsive to available technology.