6 Ways to Incorporate Artificial Intelligence into Business Intelligence
Blog Updated on December 19, 2024.
As technology develops at an unforeseen rate, using tools like artificial intelligence (AI) 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.
Most businesses want to operate with greater efficiency, lower costs, higher profits and increased employee satisfaction. Studies show that AI applications in business are effective at empowering companies to reach those goals:
- According to a 2024 McKinsey survey, 65% of respondents report that their organizations are regularly using AI, which is nearly double the percentage reported in a similar survey conducted in the previous year.
- Forbes Advisor reports that 56% of surveyed businesses in 2024 are using AI for customer service and 51% are using it for cybersecurity and fraud management, making these the most popular uses for AI tools.
- A People Management article reports that 85% of office workers in 2024 say AI has improved their overall work performance.
With the right AI tools and plans, organizations can incorporate effective AI strategies into their business intelligence processes to create positive effects for the company, its customers and consumers as a whole.
Earning a Doctor of Business Administration in Business Intelligence can help professionals learn critical leadership skills, applied research processes and data-driven strategies to embrace the power of artificial intelligence in business intelligence.
What Is AI?
Artificial intelligence refers to both the theory and implementation of AI systems that can perform tasks formerly only completed by humans. For example, AI technologies can:
- Perceive objects visually
- Forecast sales
- Make decisions
- Automate processes
- Recognize speech
- Provide online customer support
- Perform translation services
What Is BI?
Business intelligence refers to the data collected from multiple sources that can be incorporated and leveraged to make smarter business decisions. Processes used to collect and use business intelligence include data analytics, mining and visualization. The goal of business intelligence is to give companies the insights and information they need to make strong, data-driven decisions for their organizations.
Comparing Artificial Intelligence and Business Intelligence
Both artificial intelligence and business intelligence deal with data science. But while business intelligence primarily provides insights into and analyzes data to inform decisions, artificial intelligence also can implement such decisions itself. For example, a banking business intelligence solution that incorporates artificial intelligence will be able to not only predict patterns of fraudulent activity but perform processes to reduce their occurrence as well.
Artificial intelligence and business intelligence work well together when a company’s decision-making process is heavily data-driven and its goals are clear. Both business intelligence and artificial intelligence can be used to determine what those strategies and goals are. Once the goals and strategies are clear, artificial intelligence can be employed to achieve them skillfully.
6 Strategies to Incorporate Artificial Intelligence into Business Intelligence
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 six case studies that illustrate the profound ways that artificial intelligence and 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 what it observes. 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 the status of the farm’s field, which improved the team’s yield estimates and the accuracy of their harvest time by 10%.
This AI and machine learning application highlights a key way to incorporate an effective AI strategy into business intelligence: Deploy AI to monitor and measure what matters most to a corporation. By focusing AI efforts on the 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 Through AI Tools
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 their customers’ experience to meet modern needs with modern solutions.
Take, for example, the AI-generated content on their website. CarMax leveraged Microsoft Azure OpenAI Service to create text summaries for the care research pages on its website. In doing so, the company provided consumers with the information they were looking for while car hunting. They also boosted their search engine rankings, as the AI systems create SEO-friendly copy that meets customer needs and increases searchability.
CarMax said 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 systems, they met the goal in just a few months.
The CarMax study underscores a primary benefit of using artificial intelligence in business intelligence: When AI is deployed strategically, it doesn’t only achieve one positive outcome. Instead, AI excels when it is wisely deployed to solve a specific problem and, in doing so, produces secondary benefits like cost savings and greater efficiency.
3. Increasing Sales Outcomes Through AI Technologies
Swedish golf retailer Dormy wanted to roll out online sales across Europe but lacked the e-commerce 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 search exit numbers are high or conversion rates are low, for example, artificial intelligence can interact with the specific customer who may otherwise exit the page or abandon their shopping cart. With AI, customers also can be presented with other items that are suited to their tastes, increasing the likelihood of a purchase and quite likely a return visit.
4. Driving Vision and Values With Predictive Analytics
Today’s consumers like to do business with companies that are interested in more than just their profit margin. In fact, Google reports that 82% of consumers 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 a subset of artificial intelligence in which a machine performs in a certain way based on an 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 reduced transportation costs and a large reduction in carbon emissions.
In other words, artificial intelligence isn’t just good for the bottom line. It can be good for society and the planet at large.
5. Cultivating Business Agility With Forward-Thinking AI Applications
Advance Intelligence Group (Advance), a technology company based in the Asia-Pacific region, 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.
6. Enhancing Employee Productivity With AI Technologies
AI isn’t only used to improve customer-facing operations. These tools can also significantly boost internal productivity and efficiency. For example, AI systems like intelligent virtual assistants and workflow automation software can make routine tasks less redundant and time consuming. In turn, employees are freed to focus on higher-value, revenue-generating activities. AI platforms can manage scheduling, respond to common questions, or analyze data for actionable insights in real time.
A notable example is AI-driven employee feedback analysis. Platforms like Qualtrics utilize natural language processing to evaluate employee sentiment through surveys and reviews. This provides leadership with feedback on employees’ morale, culture and engagement levels — and allows for timely interventions that improve workplace satisfaction and retention.
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