Artificial intelligence (AI) and machine learning (ML) are advancing at an incredible pace. If you haven’t been following their progress, you’ll be surprised to learn about AI’s widespread adoption in every facet of life. And, while self-driving cars and patrolling robot dogs are grabbing the most headlines, a massive AI revolution is happening right now in the business world.

According to the World Economic Forum, 85 million jobs will disappear, and 97 million new ones will emerge thanks to AI by 2025. That’s an overall addition of 12 million jobs. We’ve entered an era where machines are no longer mere tools in the hands of humans but companions that work side by side and provide enormous value to any industry.

If your company is yet to employ AI, you’re missing out big time on efficiency and productivity gains, but above all, on better customer service. While you stall, others go full throttle, and it becomes increasingly harder to catch them up. Now is the perfect time to look at AI through the lenses of business capabilities and use it to your advantage.

In this article, we’ll look at how AI and ML are changing conventional business. But before we get there, we’ll walk you through a brief history of AI and present a few eye-opening stats about artificial intelligence and machine learning that make it the most sought-after skill today.

AI and machine learning history

Every journey begins with a single step, and for the AI, that step dates back to the Enlightenment period. In 1763, Thomas Bayes developed a framework for reasoning about the probability of events. Thanks to his work, Bayesian inference would become a valuable tool in applied machine learning.

It wasn’t until 1921 that the term “robot” would enter the vernacular. Czech writer Karel Čapek coined it in his play R.U.R. (Rossum’s Universal Robots). Robot originates from an old Church Slavonic word, “robota”, for “servitude,” “forced labor” or “drudgery.”

In 1943 Walter Pits and Warren McCulloch published the scientific paper “A logical calculus of the ideas immanent in nervous activity,” introducing the first-ever mathematical model for neuronal networks. The arrival of artificial neurons would mark a breakthrough in AI evolution.

More than a decade after the neurons went artificial, Arthur Samuel, a pioneer in computer gaming and artificial intelligence created a program for playing championship-level computer checkers. In 1959 Samuel coined the term “machine learning,” which now embodies an entire field within AI.

It would take almost 40 years, but in 1997 the IBM chess computer, Deep Blue, defeated world champion Garry Kasparov in chess – an undeniable proof that machines were catching up to human intelligence.

Fast forward to 2008, and the first speech recognition app appeared on the Apple iPhone. Developed by Google, it had above 80% accuracy at the time. One year later, Fei-Fei Li released ImageNet, a free database of 14 million images labeled by tens of thousands of Amazon Mechanical Turk workers. ImageNet, helped AI researchers train neural networks more efficiently.

In the last decade, AI has been progressing exponentially and has already co-produced a pop album and made $432,500 at an art auction. But what about businesses and critical industries? How have they welcomed the AI rise? Stay tuned as we reveal the latest AI stats and trends.

AI and Machine learning stats

AI is still in its infancy, and its impact may not be so resounding to the public. However, numbers paint a different picture. A glance over the latest studies confirms that AI and machine learning have truly arrived on the global stage and are ready to improve businesses in various sectors. Below we’ve listed several conclusive stats and trends:

Market size and prevalence

• The AI market will grow to a $190 billion industry by 2025 (Statista)
• The AI industry could be worth more than $15 trillion by 2030. (PwC)
• Global machine learning market was worth $8 billion in 2019 and is likely to reach $117 billion by the end of 2027. (GlobeNewswire)
• 75% of commercial enterprise apps will employ AI by 2021 (IDC)
• By 2021, 80% of new technologies will have AI foundations. (Gartner)
• There will be 8 billion voice assistants by 2023. (Statista)

Business adoption and application

• 9 out of 10 top businesses have an ongoing investment in AI (NewVantage)
• The number of enterprises using AI in business skyrocketed by 270% between 2015 and 2019. (Gartner)
• 83% of businesses say AI is a strategic priority for their businesses today (Forbes)
• 87% of companies who use AI intend to use it in sales forecasting and email marketing (Statista)

Top applications of machine learning

• Risk Management
• Performance Analysis & Reporting
• Trading investment idea generation
• Automation

Impact on businesses

• Startups using AI received more than $7.4 billion in funding during Q2 (2019) with the number expected to grow every year. (CB Insights)
• Netflix’s recommendation engine is worth $1 billion per year. (Business Insider)
• Chatbots will save over $8 billion annually by 2022. (Juniper Research)

AI and machine learning are solving problems more efficiently and delivering tangible business benefits. Crucially, they make consumers’ lives easier. According to Pega, 73% of global consumers say they are open to AI if it eases their lives.

If you’re looking to improve your business with the help of AI and machine learning, let’s see how they can positively affect different areas of your company.

Machine learning applications for business

From the healthcare industry to the manufacturing, banking, and construction sectors, every modern organization uses machine learning for the best performance and customer satisfaction. By delegating function-specific tasks to machines, companies improve security, optimize marketing campaigns, boost sales, and serve their customers better. Here are some common uses of machine learning:

Fraud Detection

Where money is involved, people will go to great lengths to take it from you. The ingenuity of fraudsters may have no limits, but machines can now outsmart them and prevent fraudulent activities. Machine learning can decipher patterns and spot anomalies within predictable systems. A recent study revealed that 69% of enterprises believe they will not be able to respond to cyberattacks without the use of AI.

Real-time chatbots

Chatbots are becoming smarter by the day. While the first generation of chatbots followed scripted rules and provided limited support, chatbots 2.0 are a completely different breed. Thanks to machine learning and natural language processing (NLP), chatbots are now more productive and interactive. The likes of Alexa, Siri, and Google Assistant resemble human beings and can perform a wide range of tasks. Over 80% of marketers already use chatbot software in their customer experience.

Recommender system

A recommender system or recommendation engine filters data such as search behavior and product preferences using machine learning algorithms to offer customers relevant products in real-time. Recommender systems help companies deliver customized experiences to customers by finding patterns in a blink of an eye. The result? Increased customer satisfaction, which ultimately leads to more profit.

Customer churn modeling

Customer retention is one of the key factors for business growth. Unfortunately, customer attrition, also known as customer churn, is a challenge every company faces. Customer churn is the rate at which customers stop doing business with you. The churn rate affects your profit and progress.

So how do you keep a healthy churn rate? An efficient way is to let AI identify patterns that diminish customer loyalty. By analyzing historical sales trends and demographic data, the ML algorithm will reveal the reason behind a customer’s decision to leave, so you can elaborate a strategy to retain them. Customer churn modeling is one of the reasons why 64% of marketers consider AI valuable for their sales and marketing strategy.

Document process automation

Business success depends on attention to the basics. Behind product management and marketing campaigns are monotonous, repetitive tasks that employees have to perform. But now, thanks to natural language processing, machine learning can automate the processing of legal contracts, invoices, and tax documents. Besides saving you precious time, ML increases accuracy and efficiency when working with sensitive data.

Recruiting and hiring

There’s a reason why 96% of senior HR recruiters believe AI can improve talent acquisition and retention. HR professionals often have to review hundreds of resumes and cover letters. With machine learning, their task has become so much easier. ML learning can standardize the entire recruiting and hiring process by organizing resumes and managing candidate profiles. Many startups are using ML to spot the brightest minds and remove unconscious bias from the system.

Operational efficiency

The beauty of AI and machine learning is that you can employ them for highly specialized tasks or use the technology to efficiently manage an array of processes from software development and testing to manufacturing and financial transactions.

According to Capgemini, more than half of the European manufactures (51%) are already employing AI, with Japan (30%) and the USA (28%) following in second and third. AI can boost productivity by providing accurate demand forecasting, predictive maintenance solutions, and automated material procurement.

AI Development at Digitize Everything

Innovation is at the core of what we do, and AI development plays a major role in how we help companies disrupt their industries through new products and services. Our tech stack includes open source programming languages and libraries such as Python, Django, TensorFlow, Keras, Scikit-Learn, and Pandas. We also work with the following enterprise machine learning platforms:

• Google Cloud Machine Learning
• Google Big Data Analytics
• Amazon Machine Learning
• Microsoft Azure Machine Learning
• IBM Watson Machine Learning

Our projects range from damage detection in residential home remodeling and flaw detection in medical equipment to recommender systems and tools for companies to train their AI models. We also worked on improving AI detection accuracy over time. Check our portfolio to see how our clients harness the power of AI.

Final Words

Artificial intelligence and machine learning are changing the fabric of our day-to-day lives. It is the common denominator among all cutting-edge technology you will find today. For digitally-minded companies, AI offers a competitive advantage in a new paradigm where customer experience and satisfaction are nuanced and individualistic. The next “big things” and innovations will all be AI-driven. That’s why the sooner companies transition to AI-based services, the better they’ll adapt to future challenges.