Chances are that you probably interact with AI multiple times a day as part of your daily life without giving it a second thought. The applications for artificial intelligence are incredibly wide and every business can now benefit from the technology.
If you aren’t exactly sure what artificial intelligence is and what it means for the future of your business, this article briefly looks at AI, how you can use it to transform your business, and what an AI integration project looks like.
If you want to grow your business and make it run more efficiently, AI can help you do both.
Here’s how:
Artificial Intelligence in Business
Artificial intelligence is a broad term that describes various types of computer software that mimic humanlike activities such as learning, planning, and problem-solving. By using actionable insights generated from customer data, AI leverages the radically changing business environment to open up a new realm of possibilities that have the potential to drive business growth. Behind all the buzz, AI boils down to leveraging machine learning techniques for prediction, pattern matching, and automation. How could you use that in your business?
Here are some examples:
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Automate and streamline: As a core component of ML engineering, automation involves making processes faster and more efficient. This may include automating specific or entire parts of the operations process involving repetitive and time-consuming tasks to increase productivity.
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Predict and prevent faults: Prediction involves using an algorithm to derive a new data set based on historical data sets to help organizations accurately guess outcomes, flag fraudulent activities, and provide insights that deliver tangible business value.
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Pattern match profitable markets: Just like our brains recognize patterns by matching any information we encounter with data stored in our memory, machine learning employs pattern recognition technology to compare incoming data with information in a database to identify common characteristics. The technique is used to quickly and accurately identify partially hidden patterns in objects to classify or cluster objects based on past representations.
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Minimize cycle times: Fluctuations in cycle times in production lines linked to complex processes and the inability to predict the effect of such delays are almost always tied to manual efforts. Adopting AI enables companies to investigate anomalies in real time by using pattern recognition in time series data to automate the analysis.
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Generate compelling content: AI can guarantee the relevance and the overall quality of content as it analyzes data from past articles and uses it in creating future content. This eventually helps to increase traffic and reader engagement levels.
Adopting AI in business can help companies automate business processes and understand and engage customers while reducing operational expenses. As modern-day business processes are characterized by complex tasks that can be stressful and inefficient when carried out manually, companies are riding on the availability of data to obtain valuable insights on specific areas where adopting AI will help them thrive and maintain relevance within the fierce competition. The benefits of using artificial intelligence include the potential to enhance efficiency and productivity and boost customer experience and revenue, besides driving business growth and transformation.
Some examples of specific AI functions that can be leveraged in business include:
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Customer Care: AI chatbots using programmed algorithms are becoming increasingly popular in managing the usually hard-to-handle customer care departments. Chatbots trained to mimic customer care representatives’ conversational styles using natural language programming (NLP) are used to direct calls, take and track orders, and answer frequently asked or complex questions requiring detailed responses.
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Media Recommendations: AI is at the heart of the engines suggesting the “coming up” song, TV show, book or movie on all major online platforms. By analyzing which media is successful with a large set of users with different traits, AI is able to suggest with a high degree of certainty the kind of media any particular user will enjoy.
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Financial Services: You may not have visited your bank branch in the last few years because they have leveraged AI to facilitate customers by simplifying transactions that traditionally take enormous amounts of time. AI-enabled algorithms enable customers to deposit cash, transfer money, or open accounts leveraging the technology for security, identity management, and privacy controls. Additionally, AI uses machine learning algorithms to provide tools for companies to detect and deal with fraud threats by identifying suspicious transactions, stopping them, and alerting appropriate parties.
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Security and Monitoring: AI can be trained to enhance the functions of the traditional surveillance camera via security algorithms, supervised exercises, and identification protocols to identify potential threats and alert human security officers to investigate further, be it at your bank or at your home’s front door
Integrating AI into your Business
Suppose you’re searching for ways to give your business a competitive advantage by adopting artificial intelligence. With its wide and ever-increasing range of applications, AI continues to affect business activities in all industries, from healthcare, sports, banking, finance, manufacturing, etc. In that case, you need to identify tools and insights to help you maximize the established and emerging developments of artificial intelligence, machine learning, and big data.
You can incorporate AI into businesses in multiple ways, but one of the most effective processes is as follows:
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Review
To stay competitive in a world where customers demand better products and processes, you must consistently integrate AI and machine learning (ML) into your business. The first step in an AI Integration is to thoroughly review your business processes and select the specific ones you can automate with machine learning. Start by evaluating workflows and identifying high-impact Machine Learning use cases so you can quickly and consistently integrate AI and machine learning (ML) into your business.
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Select
Once conducting a thorough review, you should determine your goals’ ideal ML and automation platform combination and select specific business processes you can automate. Also known as business mapping, defining strategies to discover AI opportunities takes a lot of work as you must evaluate your workflow and determine which repetitive or human-intensive tasks can be AI-automated.
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Optimize
The next stage of the process involves feeding data into the computer algorithm and teaching your software to create predictions and evaluate accuracy. Evaluating results and fine-tuning your KPIs based on your data and ML models ensures they align with your objectives and goals so your AI efforts can organize and streamline your workflow and meet objectives critical for business performance. After testing and reinforcing learning models to maximize their future potential and you’re satisfied that your AI model mimics its intended environment, it’s time to move from simulation and get into the real world.
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Integrate
Assuming all the other stages are complete, you must ensure your team understands how your AI solution operates and integrate it into your workflow. While the target at the optimizing stage is to develop an accurate, robust model that can make intelligent decisions based on data, the integration stage is about how the hardware will be applied and the language used. You must then test for accuracy via simulation to verify the model’s reliability under its anticipated use cases to avoid costly redesigns that could drain both time and money once the model is deployed.
Conclusion
It’s an open secret that the AI transformation is here to stay. Every enterprise that wants to remain competitive must eventually embrace it and create a relevant artificial intelligence ecosystem. While there’s some chance that your company is an exception, there’s every indication that companies that will not adopt AI in one form or another will eventually be left behind.
This article was originally published on the author’s