Many traditional reporting and business intelligence use cases will be disrupted once GenAI adoption gains momentum in large enterprises, although it is a non-trivial task, and will require dedicated effort and time. It will likely reduce the demand for static reporting and virtually eliminate the wait time or dependency on the central BI team to enable business views.
The transition to Agentic-AI (AI systems with autonomy and decision-making capabilities) will change where business logic is encoded, and how business reporting is enabled in the future. Here’s how the transition could unfold for the estimated 1-2 million BI engineers and the business community at large:
- Shift from Manual Reporting to Automated Insights:
Agentic-AI could automate many of the repetitive tasks associated with business reporting and data aggregation. BI tools that focus primarily on creating static reports might slow down in their relevance as AI systems can generate dynamic, on-demand insights and recommendations. For example, AI systems could analyze data in real-time and provide actionable insights directly to decision-makers without the need for a human intermediary to generate reports.
- Smarter Decision-Making:
As AI systems take on a larger role in business logic, they could potentially make decisions based on real-time data and predefined business rules. This would move some decision-making capabilities from humans to AI systems, which could reduce the need for traditional BI analysts to interpret and act on business data manually.
- Augmentation Rather Than Replacement (and Human Oversight):
However, BI isn't likely to completely disappear. Instead, it may evolve into a more strategic, high-level function where BI professionals focus on the development, customization, and oversight of the AI models, ensuring that business logic is accurately reflected in AI systems. In addition, there will always be a need for human oversight in business decision-making, especially when it comes to ethical considerations, bias mitigation, and understanding the broader context. BI professionals could also play a crucial role in interpreting and fine-tuning AI outputs.
- Integration with AI and Data Products:
Future BI systems may integrate more closely with AI-driven platforms, providing a more seamless experience where business intelligence is continuously derived from AI insights, rather than discrete reports. In this way, traditional BI tools will likely adapt to include more AI and machine learning components.
In summary, while BI might see a slowdown in some of its traditional reporting functions due to the rise of Agentic-AI, it will likely evolve into more consultative or governance roles to ensure alignment between business goals and AI systems.
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