Practical applications of Machine Learning and Artificial Intelligence are becoming more and more popular, as they can really make data analytics tools produce business outcomes that work better (and faster) than humans.

As software developers “close to the pavement” on technology trends, we’ve seen a huge jump in the usage of ML and AI in more practical business applications. However, most people don’t really know exactly how AI would change their businesses. I’d like to share some practical ways ML and AI can be implemented in this article.

Five Years Ago: Machine Learning and AI On the Horizon

Let’s take a look at how business leaders viewed ML and AI under five years ago. Many of them knew the technologies were coming, but not many had implemented full-fledged solutions.

In 2017, less than 39% of all companies had an AI strategy in place. The largest companies—those with at least 100,000 employees—were the most likely to have an AI strategy, but only half have one according to the MIT Sloan Review. Meanwhile, 54% of executives said AI solutions implemented in their businesses had already begun to increase productivity. 84% of respondents say AI will enable them to obtain or sustain a competitive advantage (2017, Forbes).

2021: Machine Learning and AI Saturate Digital Business

Today, we’ve come a long way and AI services surround all of our business processes, even ones that we don’t see. For example, Cloud solution providers adopted Machine Learning and AI for their services in droves, and they now power the internet in countless ways. Just take brief a look at Amazon’s ML and AI offerings for developers and businesses:

AWS is just one provider of ML/AI solutions and there are hundreds of other smaller solutions on the market. Basic implementations of ML and AI are so ingrained in development now, that it’s possible to build and deploy a solution in as little as one day. The current AI ecosystem is diverse, but the bulk of AI usage in business is focused on customers: learning their behavior, engaging them, and retaining their loyalty. In addition, building brand awareness, powering marketing campaigns, supporting customers and recommending purchases

The New Wave of AI and ML Applications

Back in 2017, business decision makers in the Fortune 500 pointed out the general direction where the greatest impact of AI could be expected. Unsurprisingly, those predictions are exactly what we're dealing with now:

As you can see, virtual assistants were the highest on predictions, and today we can find them integrated into many customer-facing aspects of business. Think of your favorite ecommerce shop, and it’s doubtful that you haven’t experienced some of their AI-powered features like chatbot support, product recommendations, creating reminders, finding best-price-possible, push notifications, etc.

So, How Can Machine Learning Improve Your Business?

If your business needs to support customers, chatbots can simplify communication and increase engagement across any channel possible. Many brands use Natural Language Processing (NLP) for text analysis, voice recognition, translations, or classifying incoming messages to handle data faster and more accurately.

If you need to support sales growth, machine learning tools can help analyse your existing data and prepare the best strategies for moving forward. Contrary to appearances, you do not need a huge amount of data to start and it doesn't take a lot of time to get the first approach.

If you are producing or manufacturing goods, AI can help you save on material usage, optimise packaging, or discover opportunities (and flaws) in your supply chain or manufacturing processes. Most shipping companies today use basic AI and ML tools to help their supply chain, and these tools are available out-of-the-box for the smallest of local brands, to large scale global suppliers.

If you’re looking to optimize marketing, AI delivers exciting new possibilities for content delivery. Preparing product descriptions based on some keywords is a piece of cake now (without a human thinking of them). For developers, AI tools can add a dynamic approach to otherwise ‘static’ elements. Take for instance the images below, which are imbued with motion through AI tools.

Ecommerce brands can produce price predictions and best-pricing without any human suggestions, adjusting automatically every day to maximize revenue growth. ML and AI are also important tools to detect fraudulent activity, and halt it before it becomes a problem.

In the health and medical industry, there is a lot to improve. Machine Learning supports medics in making many decisions, suggests better treatments and controls them, predicts and warns before dangerous outbreaks related to heart disease or diabetes happen. It can help doctors and dieticians prepare better menus and recipes for people on different diets and make them easy to implement.

Perhaps the most creative and groundbreaking implementations of ML and AI have been across video and image processing. Impressive achievements have been made in this area, ranging from the emergence of highly convincing deep fakes, to simply adding motion and life to otherwise lifeless eCommerce product pages.

Machine Learning and AI are allowing digital businesses to simply get more fantastic things done, without the risks of investing tons of capital, or worrying about poor outcomes.

However, the best of AI and ML is still yet to come. Machine learning technology could transform pipelines for businesses, seriously cutting down on all the time and expenses needed to drive sales, marketing and operations processes. All the time spent generating leads, improving customer engagement, etc. could be automated to give strategies within seconds, changing how we view the way we run a business entirely.