This is a guest post by Ranvir Singhsachakul who is a project consultant at Message Spring. Ranvir has worked at startups across SEA such as Bolttech and Salary Hero, and closely monitors the latest tech trends as they rise to prominence. Ranvir lives in Bangkok.
Guest Post Series: Ranvir Singhsachakul
Business Intelligence, or BI as it’s more commonly known, has risen to prominence in an increasingly digitized world. Along with BI, Artificial Intelligence, or AI, is the hot topic in the tech world today. Many investors, entrepreneurs, and tech enthusiasts place AI at the forefront of human innovation, and rightly so.
An interesting topic of discussion was brought forward in one of our team huddles last week at MessageSpring. The question was: “will AI be able to replace BI tools?” It’s an interesting question – AI has the power to do many things, so why can’t a company dump its data into a data lake, and have AI summarize that data without any human intervention?
Complementariness and Non-Replacement:
AI excels at pattern recognition and automation insights, but lacks the interpretability and user-driven exploration strengths of BI tools. Think of AI as a powerful engine and the BI tools as the control board. Both are crucial for navigating the data landscape, albeit in different ways.
Having a Human in the Loop Remains Vital:
At the present moment, AI summaries may lack context, nuance, and alignment with specific business goals. Human expertise is still needed to interpret the findings, ensure top-notch accuracy, ask the right questions, and ultimately guide the decision making. However, it’s likely that as AI continues to make the impossible possible, the current landscape will change.
Data Lakes Alone are Insufficient:
Simply dumping data into a lake without proper organization and preparation can lead to AI models drowning in noise, generating inaccurate and misleading insights. Data quality, structure and domain knowledge are crucial for effective AI utilization.
Customization and Personalization:
Different stakeholders across the organization – be it CEO, VP, manager, have diverse information needs. BI tools offer the flexibility to tailor visualizations, reports and dashboards for each audience and their proficiencies. AI on the other hand may produce summaries that are generic and miss crucial audience-specific details.
Explainability and Trust:
Understanding how AI arrives at its conclusions is crucial for building trust and buy-in. While AI is gaining Explainability features, complete transparency remains a challenge, unlike BI tools where users can readily trace analysis steps.
Conclusion:
Therefore, while AI may be revolutionizing the field of BI, it’s extremely unlikely to replace dedicated BI tools and BI experts in its entirety anytime soon. However, it’s important to note that the future of AI and BI likely lies in a symbiotic relationship where both fields are fused together. AI tools will automate routine tasks, uncover hidden patterns, and generate initial insights. BI will then enable users to refine, explore and contextualize these insights. Ultimately, BI experts will drive informed decision-making across all levels of the organization.
At MessageSpring, we are in the process of building a Business Intelligence Center of Excellence (COE) based right here in Bangkok, Thailand. Alongside our current offerings in the fields of omnichannel messaging and bespoke IT services, our vision with this COE is to build an efficient, highly skilled, and certified team that can tackle complex projects and deliver results in the field of BI.
