How AI, machine learning can create value for your business

The rise of artificial intelligence (AI), machine learning (ML) and automation has already started to change the way businesses operate. But how exactly do these tools work, and how can businesses like yours leverage them to create additional value and efficiency? 

Read on to learn more about AI, ML and automation, how businesses are using them to enhance processes and how your business can implement this technology in an effective, responsible way. 

Simply put, artificial intelligence (AI) is a type of software that’s designed to simulate human thinking. It uses algorithms to analyze data and make decisions based on that data. Machine learning, on the other hand, is a subset of AI that focuses on giving computers the ability to learn from data without being programmed to do so. Machine learning also uses algorithms to identify patterns in data, which are then used to make predictions and decisions. 

Automation—the use of technology to perform repetitive tasks—can be used in combination with AI and machine learning. Automation technologies often follow pre-programmed rules to automate tasks, minimizing the need for human input or intervention.

Around the world, businesses are using automation technology to serve a vast number of purposes, from fraud detection to image recognition to predictive analytics. Understanding these common use cases can not only help your business discover new opportunities within your own processes, but also help you keep up in your current marketplace. 

Though the uses for AI and machine learning vary by industry, business size and goal, many use cases fall under three categories: 

Enhancing customer service

As you know, customer satisfaction is crucial to the success of every business. AI and machine learning can help streamline your customer service channels, including automated phone trees, chatbots and more. Many businesses also use data-driven AI to better understand their customers and deliver more personalized experiences across different touchpoints.

Increasing efficiency

One of the most common uses for automation technology is to increase efficiency. Because automation reduces the need for human intervention, integrating AI/ML into simple or repetitive processes has allowed businesses to allocate their staff to higher-value tasks. In industries like manufacturing, automation can help eliminate waste, optimize resources and reduce production times. Some businesses are also beginning to use AI to generate first drafts or outlines of content, which allows more time for ideation, collaboration and creative thinking. 

Improving cost savings

For many businesses, cost savings is the primary motivation behind integrating AI and machine learning. This can be achieved by increasing efficiency, as mentioned above, or even increasing their output of a product or service. Another way that businesses are reducing cost is through advancements in fraud detection. With the help of machine learning, companies are able to detect fraudulent activity faster and more accurately, significantly reducing financial losses. 

Other ways AI and machine learning can help create value for your business 

Automation is quickly becoming a tool that’s used across industries and the world. But beyond just increasing efficiency, how can using AI and machine learning translate to increased value for your business? 

In addition to saving time and money, the use of automation technology can also be a valuable way to build customer relationships. AI and machine learning can help your business interact more closely with customers and learn about their preferences. With this insight, you can further customize the user experience, which may lead to increased sales opportunities and help you towards building customer loyalty.

Another way AI and machine learning can create value is through predictive analytics. This tool can help your business anticipate future trends, so you can make informed decisions about business strategies and position yourself competitively in your marketplace moving forward. 

Opportunities and challenges of AI

As companies within the TMT sector increasingly integrate AI into their businesses, opportunities continue to grow. But there are also challenges, risks and complexities that companies in this industry are facing as well. 

Content generation, for example, is one area where AI is already causing significant disruption. These tools can assist in generating personalized content for marketing, advertising or entertainment. But there is also the potential for biased or misleading content. This is because large language models, while incredibly powerful, can inadvertently generate content based on incorrect or prejudiced information. Biased content can also find its way into other applications, like chatbots, as well.

Ensuring that the content developed with AI tools is free of harmful biases is essential, and businesses in the TMT sector appear to address these concerns proactively as they further expand automation tools. Companies like Google and IBM, for example, do so by supporting responsible, ethical approaches to AI development and usage. 

Balancing the need for efficiency and innovation with the potential social consequences of AI implementation is a crucial aspect of responsible AI adoption, regardless of the industry it’s deployed in. But by embracing these technologies responsibly and strategically, businesses in the TMT sector and beyond can create positive impact and value throughout their business.

As automation technology continues to advance, it’s important to follow best practices when implementing AI and machine learning:

1. Start small

A general rule of thumb is to always start small and expand gradually. This will allow your business to thoroughly test the technology and make adjustments before incorporating any automation into a larger process. 

2. Keep everyone in the know

It’s critical that your business involves all relevant departments and employees when planning new AI or machine learning usages. This will ensure that everyone understands the role of these technologies, so they can take advantage of and fully utilize the benefits they offer. 

3. Evaluate and make adjustments

Once implemented, it’s important to regularly evaluate and adjust the automation process to ensure it continues to meet the needs of your business. And because AI and machine learning are constantly evolving, your business should regularly examine the latest updates available, advancements in best practices and any updated usage guidance.  

4. Prioritize risk-management and responsibility

In general, businesses should strive to build and deploy AI and machine learning responsibly. It’s encouraged for all businesses to approach the use of emerging technology in a way that prioritizes risk management and puts people first. 

There are many benefits that businesses can gain from AI, machine learning and automation. By utilizing some of the best practices for implementation, your business can more effectively leverage these tools within your current ways of working. And by keeping in mind the limitations and ever-growing advancements of this technology, you can help position your business competitively today and in the future.