As technology develops at an unforeseen rate, the role of tools like artificial intelligence in business intelligence strategies has become essential. Companies that want to understand and leverage their historical data, make strategic decisions that meet the needs of the present moment, and plan for the future with confidence and clarity are implementing data science, AI, and machine learning to reach their goals.
While the specifics will differ across industries, sectors, and corporations, most businesses want to operate with greater efficiency, lower costs, higher profits, and increased employee satisfaction. Studies show that artificial intelligence applications in business are effective at empowering companies to reach those goals:
- According to a McKinsey survey, 27 percent of companies reported that 5 percent of their earnings before interest and taxes could be attributed to artificial intelligence (up from 22 percent in the prior survey)
- Using AI in sales increases leads by over 50 percent, reduces costs by 40 to 60 percent, and reduces call time by 60 to 70 percent
- 81 percent of office workers say AI improves their overall work performance
The rapid evolution of artificial intelligence solutions for business will only enhance their capacity to benefit business intelligence, overall organizational approach, and company growth. With the right tools and plans, organizations can incorporate effective AI strategies in business intelligence that lead to positive effects for companies, customers, and consumers as a whole.
AI vs. BI: Definitions, Similarities, Differences, and Compatibility
Artificial intelligence refers to both the theory and implementation of computer systems that can perform tasks formerly only completed by humans. For example, artificial intelligence can:
- perceive objects visually
- forecast sales
- make decisions
- automate processes
- recognize speech
- provide online customer support
- perform translation services
Business intelligence, on the other hand, refers to incorporating and leveraging multiple data sources in order to make smarter business decisions. Components of business intelligence include data analytics, mining, visualization, and tools. The goal of business intelligence is to give companies the insights and information they need to make strong, data-driven decisions for their organizations.
When it comes to similarities, both artificial intelligence and business intelligence deal in data science. But while business intelligence primarily analyzes and provides insights into data to inform decisions, artificial intelligence can implement such decisions itself. For example, a banking business intelligence solution that incorporates artificial intelligence will not only be able to predict patterns of fraudulent activity, but perform processes to reduce their occurrence.
Artificial intelligence and business intelligence work well together when company strategy is heavily data-driven and goals are clear. Both business intelligence and artificial intelligence can be part of determining what those strategies and goals are. Once the goals and strategies are clear, artificial intelligence can be part of achieving them skillfully.
Through the examples of existing AI applications in business, corporate leaders can discover how to better define their strategies and achieve their goals effectively. Consider five case studies that illustrate the profound ways that artificial intelligence in business intelligence can strengthen an organization.
1. Improving Logistics Channels to Focus on What Matters Most
One of the incredible capabilities of artificial intelligence is its capacity to watch a product line around the clock and make predictions based on it. This may be an assembly line in a factory or it may be, as in the case of an Israeli potato farm, a field.
When the procurement department of the farming enterprise implemented AgroScout, a crop development artificial intelligence platform, they did so to monitor plant emergence. The platform was able to provide live data regarding field status, which improved the team’s yield estimates and the accuracy of their harvest time by 10 percent.
This AI and machine learning application highlights a key way to incorporate an effective AI strategy in business intelligence: deploy AI to monitor and measure what matters most to a corporation. By focusing AI efforts on areas of greatest potential profit, and greatest potential loss, companies can not only gather the data they need but rely on AI solutions that put that data to work for positive outcomes.
2. Reaching Target Consumers with the Information They Need
When CarMax began in 1993, the company disrupted an entire industry that most people wanted nothing to do with — used cars. Decades later, they are still improving and changing the customer experience to meet modern needs with modern solutions.
Take, for example, the AI-generated content on their website. CarMax leverages Microsoft Azure OpenAI Service to create text summaries for the care research pages on its website. In doing so, the company provides consumers with the information that they are looking for while car-hunting. They also boost their search engine rankings as the artificial intelligence creates SEO-friendly copy that meets customer needs and increases searchability. CarMax says that if they had created customer review summaries for 5,000 pages with their prior process, it would have taken 11 years to complete the project. With their AI solution, they met the goal in just a few months.
The CarMax study underscores a primary benefit of business intelligence in artificial intelligence: regularly, when AI is deployed in a strategic way, it does not only achieve one positive outcome. Instead, AI excels when it is wisely deployed to solve a specific problem, and, in doing so, it tends to produce secondary benefits like cost savings and greater efficiency.
3. Increasing Sales Outcomes through AI-Powered eCommerce
Swedish golf retailer Dormy wanted to roll out online sales across Europe but lacked the eCommerce infrastructure to do so. Enter Avensia Excite and Apptus eSales Product Discovery, AI-powered solutions that empower relevant customer interactions.
In just four months, Dormy saw a 27% increase in the company’s conversion rate and a reduction of 14.6% in search exits. By the end of the period, their revenue had increased 15.7%.
This emphasizes one of the most important overlaps between business intelligence and artificial intelligence. While business intelligence can discover that, for example, search exit numbers are high or conversation rates are low, artificial intelligence can interact with the specific customer who may otherwise exit the page or abandon their shopping cart. With AI, that customer can be presented with other items that are suited to their tastes, for example, increasing the likelihood of a purchase and quite likely a return visit.
4. Driving Vision and Values with Machine Learning
Today’s consumers are interested in companies that are interested in more than just a profit margin. In fact, 77% of consumers say that they prefer to make purchases from brands that share their values. As today’s corporations seek to contribute to the common good, AI applications can help them do so, specifically in the area of sustainability.
For example, Amazon has leveraged machine learning — a subset of artificial intelligence in which a machine performs based on automated analysis of past data — to reduce the company’s packaging waste significantly. Through a machine learning solution, Amazon now uses much less packaging, which results in less transportation and a large reduction in carbon emissions.
In other words, artificial intelligence isn’t just good for the bottom line. It’s good for society at large.
5. Cultivating Business Agility with Forward-Thinking AI Applications
Advance Intelligence Group (ADVANCE), a technology company in Asia-Pacific, helps thousands of companies and millions of consumers implement digital transformation, fraud prevention, and process automation solutions. During the COVID-19 pandemic, the capability of artificial intelligence to serve those customers became especially clear when many clients needed to transition as quickly as possible from traditional or offline models to online business.
ADVANCE deployed several business intelligence solutions connected to their AI and machine learning algorithms. This approach not only kept ADVANCE’s own company at the cutting edge of technology but guided their clients in fostering greater business agility themselves. In doing so, ADVANCE helped its clients optimize their costs, implement data security, and adapt to the digital world efficiently.
By deploying AI applications, organizations can become more agile in an ever-changing business landscape.
Be at the Cutting Edge of How to Utilize AI in Business With a DBA in Business Intelligence
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