Have You Forgotten BI in the AI Craze?
The proven unsung and less expensive option.
The Unsung Hero: A Brief History of Business Intelligence (BI)
Business Intelligence (BI)
Business Intelligence has been a cornerstone in business data analysis for decades. Emerging in the late 20th century, BI developed from simple data reporting to complex analytics. It was the first wave of digital transformation in data handling, allowing businesses to transition from instinct-based decisions to data-driven strategies. Over the years, BI has evolved to offer sophisticated data visualization, real-time reporting, and predictive analytics.
BI, a more budget-friendly and data-grounded technology, often aligns more closely with what companies truly need.
The Overlooked Efficiency of Business Intelligence (BI)
While the spotlight has shifted to Artificial Intelligence (AI), Business Intelligence (BI) remains integral to business operations, offering several key advantages that should be considered:
Budget-Friendly Development
- Cost-Effective Solutions: Unlike AI, which can be expensive to implement, BI offers more affordable solutions. BI tools often require less computational power and fewer specialized skills, making them more accessible to a broader range of businesses.
Meeting Actual Business Needs
- Real Needs vs. Perceived Innovation: Stakeholders are often swayed by the allure of AI. However, many business requirements like data visualization, reporting, and basic predictive analytics can be efficiently met with BI tools.
- Enhanced Productivity and Efficiency: BI tools streamline data analysis, leading to improved operational efficiency and better decision-making.
Powerful Impact on Business Operations
- Better Customer Service: BI helps in understanding customer trends and behaviors, leading to more effective marketing strategies and improved customer service.
- Accurate Predictions and Forecasting: Unlike AI, which can sometimes “hallucinate” or generate erroneous outputs, BI relies on actual, historical data, offering more reliable and controlled forecasts.
The Pitfalls of Over-Reliance on Artificial Intelligence (AI)
Don’t get us wrong. At Intertech, we can incorporate AI into your modernization or new software development project. It is not our intention to talk you out of something you have already determined as necessary, and you are now looking for a partner to help you move forward. We are still that partner. The audience for this article is the other core of our business – the many small to medium-sized companies and their decision-makers that are dealing with aging software, need to modernize, don’t want to start over, have a set budget, and want the benefits that software intelligence can bring to the company but don’t need all the bells and whistles that AI brings with it.
So let’s be clear… While AI’s capabilities are indisputable, its pitfalls are often glossed over.
Below, are a few aspects of AI you should be aware of when deciding if AI is right for your company or if BI will suffice.
Dependency on Quality Data
- Both BI and AI results are only as good as the data, but with Artifical Intelligence’s added feature, AI models are only as good as the data they are trained on and the team training them. Poor quality or biased data can lead to inaccurate or misleading outcomes. Imagine a chat with an AI customer service bot dealing with a medical issue, and the AI bot provides incorrect information that leads to a more serious medical problem or death. The data and training of the AI model are critical and expensive since AI fills in the blanks where BI stays within its data parameters.
The Phenomenon of AI Hallucination
- AI systems can sometimes generate false or nonsensical results, a phenomenon known as “hallucination”. This is particularly problematic in critical decision-making scenarios.
High Costs and Complexity
- Implementing AI can be resource-intensive, requiring significant investment in talent, technology, and time. The benefits can be amazing but their is more to the result than simply code.
Integrating BI for Sustainable Growth
For businesses looking to make the most of their data, a balanced approach that integrates both BI and AI might be the key. However, BI provides a solid foundation of data analysis, reporting, and visualization, which can be augmented with AI for more complex tasks like advanced predictive analytics and additional automation.
Items To Consider Before Selecting an AI Library or Framework for Your Client-Side or Server-Side Modernization Project
- In today’s fast-paced, jump-on-the-bandwagon world, as a decision-maker, you understand that selecting a library or framework that will give you the enhanced benefits of AI requires thoughtful consideration and a deliberate and informed approach. Why? Because AI isn’t a one-size-fits-all solution; it’s a spectrum of tools and techniques, each suited for particular tasks.
Understanding the Similarities and Differences Between Business Intelligence (BI) and Artificial Intelligence (AI) in Business Software
- In the ever-evolving landscape of business software, two powerful acronyms often come into play: Business Intelligence (BI) and Artificial Intelligence (AI). Both BI and AI offer valuable solutions for businesses seeking automation and data-driven decision-making. In this article, we will explore what BI and AI are, their differences, where they can be implemented, their impact on business services, and the pros and cons of each.
What is an AI Model and What Makes Up the Various Models That Are Often Incorporated into Business Automation Software.
- If you are new to AI one of the areas that can become somewhat confusing is why AI Models are not always so cut and dry. Take a look at the various AI Models and some of the unique aspects that make up each one.
Conclusion
As you navigate the ever-evolving landscape of business technology, remembering the enduring value of BI could be the key to balanced and sustainable growth and exactly what you need.
If you need an outside perspective and a trusted development partner who has been in business since 1991, consider speaking with our team. Our expert staff of consultants who combine soft skills and technical expertise can provide an outside perspective with a value-added approach that may help you get started and finish well.
Understanding the Similarities and Differences Between Business Intelligence (BI) and Artificial Intelligence (AI) in Business Software
In the ever-evolving landscape of business software, two powerful acronyms often come into play: Business Intelligence (BI) and Artificial Intelligence (AI). Both BI and AI offer valuable solutions for businesses seeking automation and data-driven decision-making. In this article, we will explore what BI and AI are, their differences, where they can be implemented, their impact on business services, and the pros and cons of each.
Items To Consider Before Selecting an AI Library or Framework for Your Client-Side or Server-Side Modernization Project
In today’s fast-paced, jump-on-the-bandwagon world, as a decision-maker, you understand that selecting a library or framework that will give you the enhanced benefits of AI requires thoughtful consideration and a deliberate and informed approach. Why? Because AI isn’t a one-size-fits-all solution; it’s a spectrum of tools and techniques, each suited for particular tasks.