Is Your Data Prepared for Generative AI?

In a recent Gartner survey more than 75% of organisations said AI-ready data was one of their top five investment areas in the next two to three years. This statistic closely mirrors the trends we’ve identified within our own customer base.

As highly regulated industries embrace the era of Generative AI, data preparation for AI becomes more important than ever. This prompts a crucial question: Is your data prepared?

Below are some of the steps that your organisation can take to ensure the success of Generative AI initiatives through effective data preparation tools and data preparation best practices.

Embrace a Paradigm Shift

Generative AI signifies more than technological advancement; it marks a paradigm shift in the way organisations can harness data as a strategic asset. However, the effectiveness of Generative AI is directly tied to data preparation best practices, ensuring data is clean, structured, and optimised for AI-driven insights.

To position your enterprise at the forefront of Generative AI innovation and adoption, it’s crucial to view this technology as a key player in your digital transformation journey.  This means implementing data preparation for AI to establish a trusted foundation, reducing bias, improving accuracy, and ensuring compliance with evolving regulatory requirements.

Readiness for Generative AI involves encouraging a dynamic mindset where data is not just processed and protected, but actively contributes to the generation of new ideas, strategies, and opportunities. By leveraging data preparation for machine learning, organisations can unlock new efficiencies, improve predictive capabilities, and fuel AI models with high-quality, contextualised information.

In essence, Generative AI offers your organisation the chance to redefine its relationship with data while maximising its value.

Clean Up, Organise and De-Risk Organisational Data

At EncompaaS, our philosophy is to ensure that your organisation is not only equipped to leverage Generative AI today but is also positioned for the possibilities that lie ahead.

Achieving the capability to clean up, organise, and de-risk all organisational data is becoming increasingly imperative.

Whether managing the escalating data velocity across structured, unstructured, or semi-structured data in the cloud, on-premises, or hybrid environments, adopting a proactive approach to data preparation best practices is paramount.

Safely Accelerate ROI from AI Projects

The acceleration of AI initiatives is a critical objective for many organisations. However, this isn’t just about speed; it’s about leveraging technology and data ethically and responsibly – ensuring that each step taken is in the right direction, with the appropriate controls in place.

Central to Generative AI success is the integration of advanced data preparation processes, with data governance serving as a linchpin.

With AI data preparation, organisations can:

• Use data preparation software to automate repetitive data preparation processes
• Enhance compliance by organising and governing data properly
• Optimise datasets for machine learning and other Generative AI applications

The ability to de-risk every information asset across the enterprise and automate compliance obligations at scale bridges the confidence gap to ensure the success of Generative AI, while meeting evolving regulatory obligations and reducing your attack surface.

At EncompaaS, we know that the foundation of Generative AI success starts with data preparation best practices. Our platform enables organisations to discover, understand, govern and use their data using AI data preparation techniques that enhance data quality, governance and compliance.

With a strong data preparation process, organisations can confidently accelerate Generative AI adoption, maximise AI investments, and drive strategic innovation at scale.