The global artificial intelligence market was valued at $39.9 billion in 2019. Experts from Grand View Research predict that it's going to grow at a Compound Annual Growth Rate of a smashing 42.2% between 2020 and 2027.
The continuous effort devoted to research and innovation in this area from tech giants and innovative startups alike drives the adoption of advanced AI technologies across different industries such as retail, healthcare, automotive, manufacturing, and finance.
Technology has always been an essential component for these sectors, but AI brings it to the center of these organizations by automating processes, assisting in decision-making, interacting with customers, and delivering critical data insights.
AI is now being infused into many different products, from self-driving vehicles to virtual assistants. Giants such as Amazon, Google, Facebook, Apple, and Microsoft are all investing a lot of resources into the research and development of AI-based technologies.
But what role can AI play business? How can it help organizations to develop a strong competitive advantage? Read on to find out the value of artificial intelligence to business organizations, no matter in which sector they operate.
Table of contents:
- What is artificial intelligence in business?
- Benefits of artificial intelligence for business
- Which business processes does AI support?
What is artificial intelligence in business?
In its essence, artificial intelligence is a computer program that can perform tasks that would normally require human intelligence to accomplish. Another definition of AI is a system that can learn from data on its own using techniques such as machine learning or deep learning.
AI systems usually demonstrate behaviors associated with human intelligence, such as:
- problem-solving,
- planning,
- learning,
- reasoning,
- knowledge representation,
- manipulation
… and sometimes even social intelligence and creativity!
AI solutions are now being used by businesses to make more accurate and relevant product recommendations, interact with customers in real-time (like AI-powered chatbots), solve customer problems, recognize who is pictured on photographs, or even detect credit card fraud.
Benefits of artificial intelligence for business
1. Personalization
Providing customers with fully personalized interactions increases their engagement, attracts new consumers to business offers, boosts customer loyalty and retention, and ultimately improves sales. That's why so many organizations are now busy developing AI-based solutions able to identify patterns in customer habits and purchasing behavior.
By using millions of transactions stored in the cloud, AI algorithms can analyze them and provide highly accurate offers to individual customers based on their preferences and behavior. Recommendations engines or personalized marketing campaigns is just the tip of the iceberg here.
2. Automated customer interactions
Most customer interactions, such as online chats, social media conversations, emails, and phone calls require human involvement. But more and more companies are going to automate these communications to reduce their response time and deliver better service.
AI combined with machine learning allows companies to create smart chatbots that can interact with customers, respond to their questions, solve problems, and even initiate communication for sales purposes. Already in the 2019 Gartner CIO Survey, the respondents pointed to chatbots as the main AI-based application used in their enterprises (source: Gartner).
3. Real-time customer communication
Another benefit of AI lies in communication with high volumes of customers throughout the day.
For example, the transportation industry deals with millions of passengers every day. Artificial intelligence can help these companies to interact in real time with their target. For example, it can send notices of delay, personalized travel information, or provide travelers with real-time updates about where their vehicle is going and what the estimated time of arrival is.
4. Operational automation
AI can operate other technologies to increase the automation of business tasks, helping staff to be more productive, faster, and happier. AI algorithms can control a robot factory, send emails, fill in databases, or maintain a perfect temperature using an intelligent heating solution.
In Japan, some hotels have human-looking robots at the reception who can book services and deal with customer inquiries.
5. Predictive analytics
Another value of AI is its ability to predict outcomes. For example, an algorithm can spot patterns in customer data to show whether a product currently on sale is likely to sell or not and in what volumes. The same algorithm can predict when the demand will stop. This information can be very useful for companies when planning to purchase stock and volumes.
But predictive analytics can be used in many other areas other than retail. For instance, banks use it to predict currency and stock price fluctuations. Healthcare providers use it to predict an outbreak of infections by analyzing social media posts. After all, it was an AI algorithm that first notified us about the Covid-19 pandemic.
Which business processes does AI support?
Broadly speaking, AI supports three crucial business needs:
- automating business processes,
- generating insights from data,
- engaging with employees or customers.
Let's take a closer look at each of these functions to show you the potential of AI for business.
1. Process automation
A common type of AI used by businesses today is systems that automate both digital and physical tasks. Most of the time, they address back-office administrative and financial activities. Businesses automate them by using robotic process automation (RPA) technologies.
RPA tools are more advanced than the earlier business process automation tools because they can act like a human that inputs and combines information from multiple IT systems.
RPA can carry out tasks such as:
- transferring data from email and call center systems to systems of record,
- replacing lost credit cards,
- reaching into multiple systems to update records,
- processing legal and contractual documents to extract provisions using natural language processing (NLP),
- reconciling failures to charge for services across different billing systems by extracting information from multiple document types.
It might sound complicated, but RPA is the least expensive and easiest to implement type of artificial intelligence. It usually brings a quick and high return on investment. And it's particularly well adapted to work across multiple backend systems.
For example, NASA launched RPA in accounts payable and receivable, Human Resources, and IT spending due to cost pressures. Now they're all managed by a shared services center. The four projects turned out to be very successful. For example, in the HR application, 86% of transactions are completed without any human intervention. RPAs are now being rolled out across the entire organization to help NASA tackle tasks faster.
As technology improves, robotic process automation might cause job losses in the future — most of the time, the jobs that were anyway delegated to offshore process outsourcing companies. If you can outsource a task, the chances are high that you can also automate it.
2. Data analytics insights
This most common type of AI uses algorithms to detect patterns in massive volumes of data and then interpret them, often in combination with other insights. These applications usually rely on a subset of artificial intelligence called machine learning.
Machine learning algorithms are now being used to:
- identify credit card fraud in real time,
- predict which product a customer is likely to buy,
- automate personalized targeting of digital ads,
- analyze warranty data to identify quality problems in vehicles,
- provide insurers with more detailed and accurate actuarial modeling.
Such solutions provide businesses with a wide range of cognitive insights that differ from those available from traditional analytics in several ways:
- First of all, there's usually much more data and details involved in such analyses.
- Models are typically trained on a part of the dataset, and they get better with time. They learn how to use new data to make more accurate predictions or put things into such categories.
- Deep learning mimics the activity of the human brain to recognize patterns and can perform amazingly in recognizing human faces on images or in voice recognition applications like virtual assistants.
AI systems are usually implemented to improve performance on jobs that only machines can do — for example, programmatic ad buying that involves high-speed data processing automation that is just way beyond human ability. Machine learning provides organizations with previously undiscovered insights that can help build a competitive advantage in the marketplace, develop enhanced products, and deliver better service to customers.
For example, a law practice could use AI to extract data from contracts. This would enable lawyers to address a much higher proportion of documents, achieving even 100% of coverage.
3. Customer engagement
The third key area where companies are using artificial intelligence today is projects that engage employees or customers by using natural language processing (NLP). Bots, intelligent agents, and machine learning chatbots belong to this category.
Many brands now use intelligent agents offering 24/7 customer service and addressing a wide range of issues, from sales advice to technical support.
Internal bots are used for answering employee questions. Product and service recommendations systems are gaining steam in retail, or healthcare providers use them for creating customized care plans taking account of the individual patient's health status and previous treatment.
Organizations usually take advantage of AI-based engagement technologies more to interact with employees rather than customers. However, as more and more companies become comfortable with turning customer interactions over to machines, this may change radically. The idea is to free agents from simple and frequently asked questions so they can dedicate more time to complex issues.
4. Intelligent recruitment and smart Human Resources planning
AI is making forays in human resource management. Recruiters no longer have to deal with large piles of resumes – they have systems in place that look for specific terms and sort resumes delivering the most relevant ones to human workers.
Another application of AI in this area is related to employee retention. Sourcing, attracting, and hiring new workers is costly and time-consuming. That’s why organizations turn to AI to help them assess employees, identify whether employees need training, and indicate when to motivate and reward the most deserving team members.
5. Fraud detection
The power of machine learning algorithms lies in their ability to spot discrepancies and anomalies in everyday processes. That’s why banks and financial institutions use AI to identify suspicious money transactions and payments.
But this is just the beginning. AI also comes in handy in customs clearing processes, insurance, cybersecurity, and tax evasion. Large-scale organizations that leverage AI in these areas are looking at massive cost savings.
AI in business – conclusion
We hope this article helps you see the value of artificial intelligence for businesses. The truth is that AI can take so many forms and bring benefits to so many business departments that it's hard to capture it all in one article. If we didn't cover your industry, department, or use case, it's not because Ai isn't going to impact it – trust us, sooner or later, it will.
If you'd like to learn more about how AI could help your business grow, get in touch with us. Our experts have many years of experience in implementing AI solutions across various verticals such as healthcare, retail, finance, and automotive. Leverage the power of AI with our help and put your business on the path to success.
