Artificial intelligence plays an important role in our lives today. However, it can still demonstrate its greatest value for businesses. In deploying business intelligence systems, AI enables shifting away from traditional data processing to a more complex, data-driven approach, helping companies to extract valuable insights from large datasets – to predict market trends, identify customer behavior patterns, etc. – everything that allows them to act proactively rather than rely on past events.
The Benefits of Using AI for Business Intelligence
Although artificial intelligence in business intelligence is not a new technology, many businesses believe that its implementation is primarily about automating complex processes. However, it is capable of much more.
Lowering the entry threshold for non-technical users
Finding a user-friendly BI solution is challenging since it often requires knowledge of SQL and filtering principles. If you want the one that gives answers to queries like: “Why sales have fallen in region N?”, you’ll need an AI powered business intelligence system with integrated natural language processing. Also, such solutions can:
- Provide hints and fill out reports;
- Detect trends without pre-setting triggers;
- Provide intuitive tools for analytics and planning.
Covering a wide range of business needs
AI-based business intelligence systems can be adapted to different contexts of use, so you don’t have to deploy a lot of them. In particular:
- In marketing, such solutions can predict customer churn and select communication channels;
- In logistics, they optimize delivery routes based on traffic forecasts;
- In HR, they determine staff turnover factors and generate ideal candidate profiles;
- In sales, they perform lead scoring and predict the likelihood of deals.
Building strong insights from raw data
Conventional BI systems provide reports in the form of graphs and tables. However, to obtain more comprehensive information that will be understandable to anyone, it makes sense to use their AI-based variations, as they:
- Provide NLP capabilities for generating text comments to figures;
- Able to independently explain the reasons for deviations from the norm;
- Predict consequences based on current trends.
AI in BI: Common Implementation Challenges and Solutions
Despite the above benefits of AI, its implementation can be problematic. Let’s look at the main barriers and how to overcome them.
Selecting the right AI tools
Many businesses decide to use AI for business intelligence because it is a mainstream technology, without considering the specifics of their existing IT infrastructure. Such an integration may prove to be of little or no use at all. That’s why it’s important to make this decision after analyzing your business goals and ensuring that the software you choose is compatible with existing data sources and other digital tools you use.
Personnel training and software development
No matter how advanced your AI tool is, if your employees don’t understand how to use it or it requires programming to adapt to your processes (and you don’t have an internal IT team capable of performing these settings), it will be useless. That’s why you should take care of training your personnel after its integration, with AI and business intelligence experts assigned.
Ethical concerns
When AI makes business decisions, it may provoke the question – what are they based on? This causes mistrust and legal risks, especially in departments related to finance, HR processes, and sales. To minimize them, try to look for Explainable AI platforms that monitor the absence of bias in training samples. Also, make sure that the product you choose operates in accordance with GDPR, CCPA, and other user data privacy laws.
Conclusion
Artificial intelligence in business intelligence today is not just a new-fangled add-on to classic BI tools, because with thoughtful implementation, such solutions can make analytics not just report-based, but strategically oriented, allowing your specialists to move from hypotheses and theories to solutions that can be immediately applied in practice. Just follow the recommendations for the challenges described above and after the first weeks after deployment, you’ll see a positive result.
FAQ
Unlike conventional BI solutions, those based on AI, in addition to collecting and visualizing data, are also capable of making forecasts, identifying anomalies, and consolidating patterns. Moreover, such software solutions can learn from historical data and adapt to new operating conditions.
Yes, they can identify patterns in customer behavior to anticipate their needs and optimize the user journey. In particular, based on previous data on all customer interactions with your business, AI can offer personalized recommendations or launch trigger campaigns before the customer demonstrates interest in certain products or services.
Business intelligence and AI together relieve business analysts of some routine tasks, including data consolidation and filtering, as well as manual search for insights and report filling. That is, instead of manual work with data, your specialists will now be able to focus on interpreting the identified trends and patterns to build effective strategies based on them.
