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These days Artificial Intelligence is no longer just a buzzword. It has become an absolute must for organizations wanting to optimize their day-to-day operations.
So if you consider using Artificial Intelligence in business management, this article is for you. Here we will define what Artificial Intelligence is, explore its evolution and the main types.
Additionally, we will define the major business benefits of AI and challenges associated with its implementation. Finally, we will take a look at the most popular AI use cases.
The term Artificial Intelligence refers to the set of innovative technologies enabling machines to perform advanced human-like functions such as learning, decision-making, and planning.
What makes these systems so powerful is their ability to improve their performance and deliver more accurate responses over time by adapting to new input information.
Speaking about Artificial Intelligence, we cannot but mention the two most popular AI technologies that are Machine Learning and Deep Learning.
Machine Learning is commonly known as a subset of AI that focuses on enabling machines to learn over time and improve the accuracy of its predictions. Its algorithms are capable of processing large data volumes, identifying hidden patterns, and using them to make predictions or take actions.
At the same time, IBM defines Deep Learning as a subset of Machine Learning, to be specific a neural network that has three layers and tries to simulate the behavior of the human brain. The technology of Deep Learning lies behind products and services that we use in our everyday life and emerging technologies such as self-driven cars.
To better understand what the future holds for Artificial Intelligence and assess its potential impact on our lives, let’s take a closer look at three main stages of AI evolution.
As the name suggests, the initial stage of Artificial Intelligence refers to machines capable of performing a very narrow set of certain tasks. Since these AI tools do not have thinking ability, their performance is limited to pre-defined functions only.
Popular examples of Artificial Narrow Intelligence are virtual assistants Siri and Alexa, image recognition software, and self-driving cars.
At this stage, AI obtains thinking ability, which enables it to make autonomous decisions, gain new knowledge, and apply it across multiple domains. That’s why Artificial General Intelligence (AGI) is also known as Strong AI.
Unfortunately, we cannot provide examples of Artificial General Intelligence since such AI solutions are yet to be developed.
Remarkable is the fact that many famous scientists, including Steven Hawking, have major concerns regarding Artificial Intelligence, seeing it as a threat to human existence. In his interview with BBC in December 2014, he stated that AI “would take off on its own, and re-design itself at an ever-increasing rate. Humans, who are limited by slow biological evolution, couldn’t compete and would be superseded.”
Only time will tell whether the great scientist was right or wrong, but even now, AI capabilities seem very impressive.
Finally, the term Artificial Super Intelligence (ASI) is used to define the last stage of AI evolution, when the capabilities of machines exceed human abilities.
Modern machines have not reached this stage yet, but looking at how fast AI progresses, we can say for sure that the Artificial Super Intelligence stage is closer than we think.
For now, we can see this hypothetical situation in movies and books where machines are taking over the world.
To sum up, the transition from one AI evolution stage to another is by no means linear and pre-defined. There are so many factors that influence the further development of artificial intelligence – from research and technological breakthroughs to ethical concerns. And while Artificial Narrow Intelligence is widely applicable in different applications and online platforms, the development of AGI and ASI is still an ongoing work that comes with certain risks and challenges.
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We have already mentioned Machine Learning and deep learning as the most common types of artificial intelligence. However, there are other AI subsets that are worth mentioning.
Check the table below provided by Huawei that summarizes capabilities of four main types of Artificial Intelligence.
Now let’s discuss each type in more detail.
These AI systems do not have memory and their responses to identical situations remain the same without any variations provided that you do not alter the input. That’s how spam filters and recommendation engines on online marketplaces like Amazon work.
To some extent, Reactive AI overpasses human capabilities since the human mind cannot process the whole user’s history on Amazon and offer customized recommendations.
Reactive AI is known for its reliability, that’s why it has proved useful for such mechanisms as self-driven cars but it still cannot predict future results if you don’t provide enough output information.
Limited Memory AI got its name due to its ability to absorb learning information and deliver better outcomes based on its experience. In this regard, such algorithms resemble the way neurons in our brain work together. Limited Memory AI is the most widespread type of Artificial Intelligence.
What makes these AI systems different from Reactive AI is their capability of using the historical data together with pre-programmed info, which allows machines to make some predictions and solve more complex classification tasks.
While Reactive AI and Limited Memory AI currently exist and are commonly used in our daily lives, Theory of Mind AI is a project for the future.
Here we are talking about machines that will be able to recognize and remember emotions. Moreover, they will be capable of adjusting their behavior based on emotions shown by other people.
Needless to say, developing the Theory of Mind AI comes with specific challenges. The thing is that the changes in behavior caused by shifting emotions that seem so natural and fluid in human communication are very difficult to recreate when it comes to building intelligent robots possessing emotions.
Self-aware AI can be seen as the most advanced form of Artificial Intelligence. Here machines will obtain human-level consciousness and a sense of self. It means they will be completely aware of their state of being, needs and desires.
Despite the active development of AI technologies, the idea of Self-Aware AI is still a distant reality. There are so many things we need to discover about the human mind, memory, and learning capabilities before applying this knowledge to advance AI technology further.
The wide adoption of AI among Big names such as Microsoft or Amazon shows that implementation of Artificial Intelligence in business can bring organizations multiple benefits. So let’s explore how artificial intelligence transforms the business.
AI solutions process and analyze large volumes of information much faster and more accurately than humans. As a result, you quickly gain valuable insights and identify certain patterns, which allows you to make data-driven decisions.
Additionally, applications of AI in your business operations enable you to uncover emerging trends, detect anomalies, and predict future outcomes. Armed with this information, you can prepare your business for rapidly changing market conditions and stay ahead of the game.
Businesses often use AI programs to automate and optimize complex processes and workflows, minimize human errors, and thus, improve overall operational efficiency.
AI automation makes your employees more productive since they require less time to complete a mundane task. Assigning these tasks to machines, your employees can focus on resolving more urgent issues that require their direct involvement.
One of the significant business benefits of Artificial Intelligence is the ability to offer your consumers personalized experience tailored to their specific needs and wants.
Implementation of AI algorithms simplifies the analysis of big volumes of customer information. You will quickly gain valuable insights into their purchasing behavior, predict customers’ preferences, and deliver personalized recommendations based on their past orders.
This way, you will be able to increase customer satisfaction and loyalty.
The last but not least application of AI in business is cybersecurity. Artificial Intelligence has proved its efficiency in detecting different types of cyberthreats and providing specific measures to prevent them. What is more important is that these threats are identified and handled much faster compared to human specialists.
Apart from that, AI utilizes such helpful tools as fingerprint scanners, facial recognition, and CAPTCHA to provide an additional security layer to secure authentication after failed login attempts.
Check the image below to define how the integration of Artificial Intelligence can help you ensure the safety of your company data and prevent cyber crimes:
There are several applications of Artificial Intelligence that can help your organization save money. First, you can use AI-powered chatbots to provide customer service 24/7 and handle customer queries. This approach reduces the need to hire human service representatives and allows you to reduce staff expansion costs.
Additionally, optimized inventory management, minimized equipment downtime, and improved supply chain efficiency also help avoid unnecessary expenses.
Finally, by automating and optimizing hiring and recruitment tasks, you will make your HR processes more efficient and less expensive.
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Though AI investment is highly beneficial for your organization since it can help your brand beat competitors with unparalleled customer experience, you should be aware of some challenges and concerns you may face when developing an AI system and integrating it into your business. Let’s discuss them more thoroughly:
AI technology is evolving faster than comprehensive frameworks that regulate its usage. As a result, your organization has to address complex and tricky legal and compliance concerns, be it intellectual property rights, data privacy, or cybersecurity.
Furthermore, let’s not forget about the mandatory compliance with General Data Protection Regulations (GDPR) or any other industry-specific laws or regulations that may cause additional issues.
To minimize risks of regulatory concerns, you should stay on top of the latest laws and regulations specific to your domain. It would not hurt to hire a qualified legal expert who will help you settle issues with regulatory compliance and data protection.
Finally, establish clear and straightforward guidelines regarding data usage, write them down, and make the documentation related to AI compliance accessible to all stakeholders.
AI tools are heavily reliant on big volumes of high-quality data to train and make accurate predictions. However, you may find it hard to obtain this information due to data inconsistency, incompleteness, or privacy and security concerns.
As a result, the performance and reliability of the results delivered by Artificial Intelligence may be seriously compromised.
To avoid data-related issues, specify and prioritize data requirements before you integrate AI into your business.
Another good practice implies investment in data collection and cleaning techniques that ensure the highest quality of the data.
Finally, the establishment of data governance practices will facilitate data integrity.
Implementation of AI and Machine Learning technologies across your organization or their interaction with existing software products may turn out challenging and complicated. You should carefully consider computational resources and infrastructure requirements to prevent some pitfalls that may occur during the integration process.
Besides, to make the most of Artificial Intelligence in business, you have to ensure that the AI tools you want to use are fully compatible with your legacy software systems and workflows.
Development and implementation of machine learning and deep learning models require specific skills and knowledge. Since these AI technologies are still in their infancy, we can witness a shortage of technical experts who can successfully design, train, and maintain such solutions.
As a result, you may find it extremely hard to find and hire qualified technical specialists or upskills your existing employees.
You have two available options here. First, you can invest in training and upgrading your current staff members.
Alternatively, you may spend time searching and hiring skillful data scientists, machine learning engineers, and other AI experts.
You should be prepared that it will take a good bit of money to design and integrate AI into your business.
Effective usage of AI in business requires hiring technical experts with specific skills and knowledge. Since these are rare specialists, their services may be quite expensive.
Apart from that, you should consider investing in training programs for your workforce and upgrading your software to meet the requirements of AI and Machine Learning tools.
You can minimize some expenses by searching for budget-friendly training programs. You always have an opportunity to find out whether this specific program suits your business before purchasing it.
To overcome the challenges we discussed above and use Artificial Intelligence in business efficiently, you should consider different aspects of the AI integration process. We recommend starting with data management, domain expertise, ethical concerns, and active collaboration between all involved parties.
Additionally, you need to implement the right governance frameworks and efficient AI and ML practices.
This way, you can mitigate any risks of AI implementation and maximize the benefits of Artificial Intelligence for business.
Owing to undeniable business benefits of AI, such as enhanced efficiency and productivity or improved decision-making, it is widely used in many areas. Below you can see the most common use cases of AI implementation:
Sales is the area where the implementation of Artificial Intelligence can have the greatest positive impact on your company’s bottom line.
Here are some statistics to prove this fact. Thus, Harvard Business Review states that companies that integrate AI into their operations can expect a 50% increase in leads and a cost reduction of 40%-60%. So yes, it is high time to invest in AI initiatives if you have not done this yet.
Now let’s look at some specific examples of using AI for sales.
First, AI assistants have become handy tools for demand forecasting. With their help, you can get historical sales results, which you can further use to create accurate sales projections.
Second, deep learning algorithms allow you to prioritize leads based on conversion probability.
Finally, the usage of Artificial Intelligence in sales enables you to uncover hidden upselling and cross-selling opportunities.
Artificial intelligence is a powerful marketing tool that brings your business multiple benefits. Thus, it provides valuable data that will enable you to predict the next step your consumers will take and, thus, improve customer journey correspondingly.
Now let’s discuss where exactly you can use Artificial Intelligence in marketing to deliver seamless customer experience and increase the value of your offerings:
Other examples of using Artificial Intelligence in marketing you may see on the following image:
To sum up, AI and machine learning algorithms will help you maximize the efficiency of marketing activities. You will better understand your customers’ needs and learn to satisfy them with your products and services.
Customers are the heart of any business. Hence, you need to prioritize the customer experience to prosper and gain a competitive advantage over other companies in your domain. It implies offering high-quality support services, where agents will resolve consumers’ issues quickly and promptly respond to their queries.
By using Artificial Intelligence in customer support, you can make support agents more efficient and productive. Chatbots and other AI tools automate customer support workflows and reduce response and handling time. They satisfy consumers with instant automatic responses 24/7 and save a lot of time for your support team.
Besides, you can use augmented messaging tools to deal with more sensitive and complicated cases.
Artificial Intelligence can make human resources managers’ lives easier by simplifying and automating talent acquisition, talent management, and corporate learning processes.
To be more specific, machine learning algorithms help find the perfect match between job requirements and skills and qualifications candidates have,
When it comes to career development, applications of AI allow you to offer employees individualized career plans and provide them with personalized recommendations. This way, Artificial Intelligence in human resources gives them unique opportunities to advance their career and gain new skills.
Accounting is another domain where applications of Artificial Intelligence bring businesses multiple benefits in terms of improved operational efficiency and accuracy.
Thus, AI and Machine Learning automate repetitive tasks accountants have to complete on a daily basis. Generally, they imply gathering, organizing, analyzing, and processing numerical information. These tedious processes are prone to human mistakes. By using Artificial Intelligence in accounting, you can minimize these errors and save your employees from overload.
Another business benefit of AI for accounting is the automation of mundane bookkeeping, payroll, and tax preparation processes.
Similarly to customer support, contact centers can make or break your business, meaning you can either gain loyal consumers or lose them to your competitors. To avoid the latter, your task is to ensure the seamless performance of contact centers holding large volumes of customer data. That’s when Artificial Intelligence comes to help.
Thus, you can use voice bots to reach hundreds of customers to promote your products or services. Additionally, chatbots can answer the simplest queries and pass information to your sales representative if a customer is interested in your offerings.
There are several ways in which the implementation of Artificial Intelligence can positively affect the manufacturing industry.
First, it automates warehouse management. As a result, manufacturers can easily monitor their inventory and improve logistics based on a continual stream of collected data.
Second, AI and Machine Learning are widely used for predictive maintenance. Deep learning algorithms make it possible to predict future failures in equipment performance and, thus, allow you to schedule preventive maintenance and repairs in advance and reduce unplanned downtime.
Finally, implementation of AI in business allows you to predict future demand for a particular product. Accurate forecasting helps you minimize risks and maximize the efficiency of supply chain management.
Check the picture below to define how Artificial Intelligence is used in the manufacturing industry:
Today we can see many applications of AI in many other industries, be it finance, healthcare, or manufacturing. Deep Learning and Machine Learning have enough potential to revolutionize the way people do business by improving their employees’ productivity and increasing overall customer satisfaction. Still, there are some concerns and considerations that should be carefully considered before you decide to use Artificial Intelligence in business.
Recently many brands have been investing heavily in Artificial Intelligence to maximize operational performance and gain a competitive edge. From enhanced efficiency and exceptional customer experience to reduced costs and advanced cybersecurity – there are many ways how AI is transforming businesses.
So if you do not want to lag behind your competitors, the time has come to make the most of Artificial Intelligence and Machine Learning.
If you want to harness the power of Artificial Intelligence and need a reliable software partner to help you with the digital transformation of your business, feel free to contact us. Our technical experts build, maintain, and scale up AI-powered solutions that augment human capabilities and bring the highest business value.
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