Generative Artificial Intelligence (GenAI) is a present-day reality reshaping industry. Beyond writing better code, GenAI is helping businesses run more efficiently. It improves fundamentals from taxonomy to content management — making data easier to find, consume, share, and trust. By automating repetitive tasks and enabling more sophisticated data analysis, GenAI allows companies to focus on strategic thinking and creative problem-solving.
There’s a catch. Without robust data integration and quality control, even the most sophisticated AI models will falter. A weak data infrastructure, messy data, bad data — all of these impede your organization’s ability to take advantage of GenAI’s opportunities.
Let’s dive into how you can avoid being left behind.
This Isn't New: Data Processing Evolution
We’ll start with a simple truth: this is all part an existing journey — for example, the move from handwritten ledgers to digitized databases marked a significant leap in data processing. Today, GenAI is that next step. Just as digitization transformed how we store and process data, GenAI is set to revolutionize how we analyze, use it and monetize it.
Even just high-level examples illustrate the magnitude we’re talking about:
- Imagine reducing a 6-month data cycle to just 6 weeks, saving your developers time and your company money.
- A cellphone company can significantly shorten its cycle of gathering, analyzing, and acting upon customer data, thereby speeding time to market and increasing revenue.
- Optimizing supply chains to reduce waste and improve customer experience.
Every efficiency and productivity win counts in a competitive market.
GenAI Needs Data Engineers
As organizations realize the opportunities GenAI technology offers them, they are also realizing the critical need for data engineers. Not long ago, the ongoing call was for data scientists — and their ability to analyze and interpret data . But the importance of data engineers cannot be overstated. Data engineers are responsible for the integration, quality, and infrastructure of data.
Given the current prominence of data lakes, organizations increasingly find themselves managing large, diverse data streams. They not only consume information from multiple sources but also generate their own data assets and subscribe to additional services. This multifaceted approach to data acquisition and management inherently raises the risk of data redundancy and raises concerns about maintaining data authenticity.
The volume and variety of data will only grow — making it harder and harder to preserve a single source of truth amidst a potentially fragmented environment. GenAI tools provide a sophisticated means to maintain data integrity, ensuring that organizations can maintain an authoritative version of their data assets.
. High-quality, accessible data is essential for any successful GenAI application. By ensuring that businesses have clean, structured data, data engineers provide that necessary groundwork.
Humans Remain "In the Loop"
The concept of "human in the loop" (HITL) . At a high-level, HITL refers to systems where humans need to be involved at certain, critical points to ensure the accuracy and reliability of automated processes. This was especially important early on in AI development, when errors were frequent and the consequences could be severe.
In a GenAI context, HITL is evolving into something more dynamic where humans and AI systems work closely together to enhance each other’s strengths. This is an area in which AI shines and is why anyone who only sees AI as a replacement isn’t thinking big enough. A true partnership between AI and humans will lead to more creative and innovative ideas than either one could create on their own.
To emphasize the need to keep humans involved, consider these situations:
- Accuracy and Reliability: Human oversight ensures that GenAI outputs are accurate and reliable, reducing the risk of errors in critical applications such as healthcare, finance, and legal fields.
- Ethical Considerations: Humans can address ethical and moral considerations that AI systems may overlook, ensuring that AI applications align with societal values and norms.
- Contextual Understanding: Humans provide context and domain-specific knowledge that AI systems may lack, enhancing the relevance and applicability of AI-generated insights.
- Continuous Improvement: HITL facilitates a feedback loop where human input helps refine AI models, leading to continuous improvement and adaptation over time.
Organizations must be thoughtful about positioning their employees and their technology such that each side is empowered to excel. Training people to interact effectively with GenAI is essential for maximizing its benefits.
There is no one right way to do this, it depends on your businesses size, audience, budget, and more. But some examples include:
- Healthcare: Physicians and AI collaborate to analyze medical data, providing more accurate diagnoses and personalized treatment plans.
- Finance: Financial analysts use AI to detect fraudulent activities, with human oversight ensuring that legitimate transactions are not flagged incorrectly.
- Retail: AI-powered chatbots handle routine inquiries, while human agents manage complex or sensitive issues, improving overall customer satisfaction.
To keep up every business will, to some extent, need to train their people to interact effectively with GenAI — from developing skills in prompt engineering, to recognizing when the technology has erred or given incomplete information.
GenAI is not just a tool for technologists; it can fundamentally change how businesses operate at every level. It helps make data easier to find, consume, share, and trust. Businesses are built by humans who have limitations on how much knowledge they can retain and analyze. GenAI, with no such limitations, can significantly enhance business operations by providing critical insights and enabling more efficient decision-making.
At BBI, we believe that the future of business lies in this seamless integration of human expertise and AI capabilities. Our approach emphasizes the importance of human judgment and creativity in guiding AI applications, ensuring that technology serves to augment human potential rather than replace it.
Building the Future
GenAI represents a transformative leap in how businesses operate, offering unprecedented opportunities for efficiency and innovation. However, its success hinges on having a robust data foundation.
BBI is uniquely positioned to prepare businesses for the GenAI revolution, given our data engineering focus — we are designed to build a solid data foundation. Our in-house tooling and accelerators speed up projects, reduce costs, and minimize errors. We’re ready to ensure you can take advantage of every new breakthrough — let’s build together.
