The duet of artificial intelligence and business is no longer the future; it’s the present. In 2023, the global market for AI was estimated at $196.63 billion. Medicine and healthcare, data management, processing and cloud, and fintech invest the most. The leading technologies include robotic process automation (39%), computer vision (34%), natural language processing (33%), and virtual agents (33%).
And how did it all begin? Let’s take a short excursion into the history of AI applications in business.
In the first half of the 20th century, science fiction introduced the world to the concept of robots with artificial intelligence. Already in 1950, Alan Turing, in his article “Computing and Intelligence,” discussed the possibility of building intelligent machines and testing their capabilities. However, there were serious obstacles to the development of AI, including a lack of computing power and the high cost of computers.
The first breakthroughs in deep learning and expert systems occurred between the 1960s and 1980s. Systems such as Dendral and MYCIN have been used to solve problems in chemistry and medicine, helping experts make decisions.
In the 1990s and 2000s, specialists made great strides in artificial intelligence transformation. In 1997, Garry Kasparov lost IBM Deep Blue in a chess game, which indicated the possibilities of software decision-making. That same year, Dragon Systems implemented speech recognition software for Windows. Other achievements included the creation of Kismet, a robot that detected and simulated emotions.
What now? The growth of data and massive computing capabilities has led to the spread of AI in various business sectors, from finance and medicine to retail and entertainment. It would be wrong to think that this technology is only for large corporations — 40% of small and medium-sized enterprises see quick results six months after the introduction of AI, and after a year, this indicator increases to 57%. At the same time, 88% of companies use AI in two or more areas.
In this article, we’ll discuss the technology’s benefits and uses of artificial intelligence in business. You will also learn experts’ opinions on whether AI will replace a person and how to implement AI optimally.
Leveraging AI for Business Success: Key Benefits Unveiled
It is obvious that AI offers many advantages — otherwise, it would not have become such a huge phenomenon. But what are the benefits of artificial intelligence in businesses you can expect?
AI Automation and Operational Efficiency
Regardless of role or industry, every workflow has several processes that should be automated. Entering data, compiling reports, or checking documents becomes much easier with AI in business.
At the same time, the impact of AI does not mean job loss, as your employees spend time on more meaningful and value-added tasks. This positively influences the work process, speeding up certain operations. As a bonus, specialists reduce the risks of burnout or dismissal and feel more motivated to work for your company.
Cost Reduction
In addition to improved productivity, automating routine tasks dramatically reduces operating costs. Another advantage is that optimization minimizes human error. Therefore, the work will not have to be redone, spending even more time on tasks. Also, you should consider the fines that might be avoided by tracking anomalies through AI usage.
Data Analysis and Forecasting
No human can process and analyze data with the same speed and accuracy as AI. At the same time, data sources include CRM and ERP systems, industry reports, analytical portals, social networks, competitor websites, etc.
This way, you identify trends, relationships, and anomalies, as well as recognize typical behavior. As a result, you better understand the market and the consumer, quickly detect risks and suspicious activity, or predict future events based on historical data. Who does not want to forecast profit, staff turnover, or the probability of repaying a loan?
Improved Decision-Making
In the era of AI, the phrase “who owns information owns the world” takes on a new meaning. Indeed, with data about the real-time situation and future forecasts, you make informed decisions about goods or services, areas of activity, or geographic expansion.
For example, in the hospitality industry, airlines and hotels use predictive analytics to dynamically determine prices, increasing demand while maximizing profits.
Revenue Increase
AI not only reduces costs but also maximizes revenue. For example, retail firms analyze purchases to offer relevant products, increasing sales and total receipts. By forecasting demand, they optimize inventory so that popular items are always available.
Another example with marketing departments: consumer analysis allows specialists to precisely create and target campaigns for maximum conversion.
Customer Satisfaction
Customer care is a priority for every company, and AI makes it easier to achieve. Show clients personalized content and products, congratulate them with discounts and promo codes, and even predict needs.
In addition, you should automate some processes, simplifying the customer journey. For example, you could provide quick consultations by answering popular questions through a chatbot.
In Which Business Areas Is AI Actively Used?
Together, AI and business optimize routine processes and improve data analysis. As for generative artificial intelligence, according to McKinsey, it is most often employed for marketing and sales, product and service development, and service operations.
According to Stanford University research, the most common uses of AI in business in 2022 were new product creation (20%), customer segmentation (19%), customer service (19%), and product improvement (19%).
Let’s examine these and other artificial intelligence business applications.
Customer service
Today, chatbots and virtual assistants are extremely common. This is unsurprising because they allow companies to meet most of the client’s needs — check the order status, inform about the goods, choose the necessary service, etc.
The biggest advantage of chatbots over real people is that they work 24/7. Therefore, the client gets instant help with their request. Of course, in more complex cases, it should be forwarded to a human manager.
As for support workers, chatbots not only relieve them but also help during communication with users, displaying all the necessary information and creating personalized solutions in real time.
Content Generation
Generative AI usage has simplified the lives of content creators. Writers actively use ChatGPT, Google Bard, and Jasper, while designers turn to DALL-E, Midjourney, and Stable Diffusion.
These tools help you scale up because creating content requires fewer resources and time. The impact of AI is also valuable in brainstorming, enabling creators to look at tasks from different angles and get inspiration from bold ideas.
However, you should remember that this is only an assistant, and the content generated by artificial intelligence for businesses is not ready for publication. It still needs to be fact-checked and edited to match the brand’s style. In addition, the intellectual property problem still remains open.
Marketing
For marketing departments, AI offers many opportunities that help not only to optimize routine tasks, but also to gain a deeper understanding of the market and the consumer.
Marketers spend a lot of time on marketing research. Instead, AI algorithms analyze large volumes of data, highlighting trends, patterns, and relationships. This greatly speeds up the process and reveals insights a human might miss.
After customer research, the system segments users into categories based on demographics, preferences, or website/app behavior. Then, based on the profiles, the marketing team personalizes content, offers, and promotions.
What about forecasting? Trends based on historical data allow you to predict future ones and, therefore, better prepare for changes in demand and preferences. You will also anticipate customer needs and cross-sell to maximize profits.
Sales
Demand forecasting is a business application of artificial intelligence useful for the sales department too. By analyzing customer data and past interactions, AI prioritizes prospects and the steps needed to engage them. If you keep records and evaluate prospects, smart algorithms will update them after each user action.
Any salesperson will confirm that most of their working time is not spent on actual sales but on manual tasks like data entry or mailing. The good news is that this can also be automated. For example, generative AI tools help personalize typical letters.
Human resources
ChatGPT and its analogs help create not only social network posts or articles but also recruiting materials — job descriptions, e-mails for candidates, interview questions, etc. Of course, this is only a draft that should be edited, but it is still faster than writing from scratch.
You might be surprised, but chatbots also attract candidates. On your career page, you may host an assistant to help users find the job they need and apply by answering questions.
Another use case gaining popularity is the automatic selection of candidates through applicant tracking systems (ATS). You specify the search parameters — and the system scans all resumes, rejecting those that don’t suit your needs. Thus, recruiters focus on more qualified specialists.
For existing employees, AI allows you to assess their competencies and productivity to create individual development plans and predict future workforce needs.
IT operations
Business artificial intelligence has become so integrated into IT operations that the term AIOps (Artificial intelligence for IT operations) has already appeared. Amazon defines it as using AI to support IT infrastructure by automating data backup, performance monitoring, workload planning, and other tasks.
AIOps helps the technical team quickly react to slow down failures and minimize their impact on operations. It also reduces operational costs, better allocates resources, and allows moving from reactive to predictive management.
Cybersecurity
Cybercriminals are improving their methods, but cybersecurity specialists are not standing still. They are developing new tools to detect threats — with AI assistance.
Algorithms analyze large volumes of data to identify patterns in user behavior. The system recognizes anomalies that may indicate fraud or unauthorized access to data. This way, you automatically block transactions or authorization — before the action harms the customer and your reputation. At the same time, machine learning models are constantly improving the accuracy of identifying suspicious transactions.
Legal departments
Lawyers constantly work with a large volume of data, checking documents or searching for necessary information. And with the help of AI, specialists automate processes and devote more time to expert consultations.
The first thing that needs to be optimized is the document flow. AI creates initial versions of standard legal documents (agreements, contracts, non-disclosure agreements) that only need to be reviewed and edited.
Even an experienced professional may easily get lost in a pile of laws, regulations, or precedents. Allow AI to organize and analyze legal documents to facilitate search and decision-making. The same applies to compliance — ML models can be trained to understand specific rules and detect discrepancies.
Accounting
Accounting activities like data collection and entry, invoicing, or categorization are already automated through AI. It is also a great tool for calculating salaries — quickly and without errors.
As with lawyers, accountants undergo regular audits. AI helps professionals prepare financial statements and records, and tax auditors easily access and verify data.
Finance
AI application in business allows financial experts to swiftly work with big data, and calculating risks, screening borrowers, or determining investment directions is no longer a problem.
Fraud detection and anti-money laundering (AML) are difficult to do manually, as they are time-consuming and leave room for errors. Upon detecting suspicious activity, the system alerts experts for further verification.
Forecasting is an integral part of financial activity. By studying internal historical data, market trends, or economic indicators, AI algorithms predict future results and trends, simplifying decisions about resource allocation or budgeting.
Can AI Fully Replace Humans in Business Management?
There are many horror stories surrounding artificial intelligence in management. While more technology-savvy people are excited about new prospects, more traditional ones fear artificial intelligence for business will steal their jobs. For example, KPMG reports that 31% of workers believe technology will render their jobs obsolete. However, 60% of surveyed employees noted the impact of technology on their work as extremely positive.
But what do employers think? Many may remember IBM CEO Arvind Krishna’s words that the company plans to stop hiring for roles that can be replaced by AI. But not everyone is so skeptical about human workers.
Research by the World Economic Forum emphasizes that the application of artificial intelligence in business will create jobs rather than displace them in the next five years. At the same time, the number of positions related to data processing and business analytics will increase by 30-35%.
Companies in the automotive and aerospace industries will experience the greatest growth in employment. Representatives of real estate, entertainment, consumer goods production, and mass media have more disappointing predictions.
In any case, today, there is nothing to fear because only 34% of all business operations are performed by machines, and 66% still require human intervention.
According to the IBM report, interviewed managers emphasize that due to artificial intelligence business integration and automation, about 40% of their workforce will require retraining. Within the framework of 3.4 billion working-age people, this is about 1.4 billion. At the same time, 87% of managers believe that employees will be rather augmented by technology than replaced.
Forrester predicts that the percentage of jobs that will be lost (1.5%) due to the use of artificial intelligence in business by 2030 is much lower than those that are influenced (6.9%) by technology.
What conclusion should we make? Employees should be more focused on understanding the use of AI in business and adapting their skills than competing with technologies.
Practical Tips for Integrating AI into Business from an Expert
For this chapter, we asked for a comment from our CTO, Dmytro Voitekh. But first, a few words about his experience:
Dmytro Voitekh has extensive expertise in artificial intelligence and machine learning. He led a team that created AI-based search algorithms for photo and video recognition. In addition, Dmytro successfully worked as a technical director in a startup that attracted significant investments, including from Google. In his free time, he is developing his AI-based pet project on Smart MicroGrid.
Here are the tips Dmytro gives for the successful integration of business AI:
- First, familiarize yourself with AI’s possibilities, technologies, and use cases — in general and for your industry. Also, learn about the technology’s limitations and the challenges you may face during implementation.
- Research how your competitors use AI, as well as the technology trends in your industry and niche.
- Analyze business management processes and determine which should be optimized and which will benefit the most from AI implementation. Specify use cases. For example, you might want to optimize your supply chain, personalize your customer experience, or simplify your tax audit.
- Set SMART (Specific, Measurable, Achievable, Relevant, and Time-bound) goals against which you can further evaluate AI’s effectiveness.
- Determine how ready your business is for AI transformation in terms of technology and business processes. Monolithic architecture, low-quality or incomplete data, and security obstacles will stand in the way of revolutionary plans. The same applies to staff’s non-acceptance of new technologies. Remember that all such issues should be determined by competent specialists.
- Engage qualified experts. You can hire developers, partner with an outsourcing/outstaffing vendor, or connect a ready-made solution. In the latter case, you will still need the help of a specialist.
- Upgrade your system if it is outdated. Invest in infrastructure and data quality because AI’s effectiveness will depend on them.
- To evaluate the profitability of AI application in business, it is better to start with small pilot projects. In addition, any radical changes in the processes should be implemented gradually.
- Constantly monitor the AI’s performance, the accuracy of the results, and their relevance to your goals in order to improve the models repeatedly.
But what to choose — ready-made solutions with artificial intelligence (SaaS AI) or custom AI models? It all depends on the specific needs and constraints of the business.
- Off-the-shelf solutions like LLM API ChatGPT or Claude are cost-effective and practical for many common uses (chatbots, data analytics, etc.). This is especially popular for startups creating proof of concept (PoC) or first-version (V1) products.
- At the same time, it is better to develop specialized AI models for unique business tasks or industry challenges. For example, you want to create a medical assistant to treat very rare diseases. To make it real, you should train your own large language model (LLM) created from scratch or customize an existing open-source LLM on your in-house dataset.
Conclusion
As AI develops, companies improve their processes and offer qualitative customer service. This allows them to increase profitability, free workers from monotonous tasks, avoid errors, and make better data-based decisions. However, to implement AI in the workflow, you should find talented developers to make the process smooth and efficient.
S-PRO has extensive experience delivering solutions for fintech, renewable energy, healthcare, hospitality, manufacturing, logistics, and other industries. Our specialists cover all AI technologies, from machine learning, computer vision, and NLP to predictive maintenance, recommendation systems, and neural networks. Contact us to discuss your business application of AI.
