AI is Only as Smart as Your Data: Why a Solid Data Strategy is the Real GenAI Superpower

As Data Month wraps up, one key insight has become crystal clear – no matter how advanced your GenAI tools are, they’re only as good as the data behind them. AI isn’t magic - it’s a mirror, and if you feed it poor data, you’ll get poor outcomes.

The AI Surge: A Double-Edged Sword

We have seen, and continue to see, a massive acceleration in AI adoption. For example, in South-East Asia, where AI usage jumped from 39% in 2021 to a staggering 76% of businesses in 2023. And that is not slowing down any time soon. According to Gartner, more than 80% of enterprises globally will be using GenAI APIs or models by 2026 – up from less than 5% in 2023.

But here’s the catch: a lot of that rapid adoption is happening without the right data foundations in place. It is like trying to build a skyscraper on sand – impressive on the surface, but shaky underneath. ​

Data: The Bedrock of Effective AI

There’s no getting around it - AI systems are only as good as the data they are trained on. If that data is incomplete, inaccurate or outdated, the results can be misleading at best and costly at worst. You could suffer from missed business opportunities, inefficient use of time and technology, and a loss of customer trust. High-quality data is a critical factor for extracting value from AI initiatives.

So, what does “good data” actually look like?

Without these attributes, AI models can produce misleading results, leading to poor decision-making.

Real-World Implications of Data Neglect

Imagine deploying a customer service chatbot trained on FAQs from five years ago. Customers ask about current services, but the chatbot responds with outdated info. Frustration rises, trust erodes, and the brand takes a hit. The problem isn’t the AI - it’s the data behind it.

On the flip side, organisations that invest in data quality are seeing strong returns. According to Microsoft and IDC, companies using generative AI alongside a strong data foundation, report an average ROI of $3.7 for every $1 spent. Some even see returns as high as $10.3. That’s not hype - it’s the power of clean, well-managed data.

Building a Robust Data Foundation

Before jumping headfirst into AI implementation and adoption, it is important to take stock of your current data landscape. At Solentive, we recommend starting with a comprehensive Data Assessment that covers:

• Data Quality: Evaluate the accuracy and completeness of your data.

• Data Management Practices: Review your current data management processes.

• Data Security: Assess the security measures in place to protect your data.

• Data Utilisation: Identify how effectively your data is being used.

• Compliance: Ensure your data practices meet regulatory requirements.

The outcome? A clear roadmap – with recommendations for implementation, KPIs to measure success, and actionable steps to elevate your data game and make it AI-ready.

The Strategic Advantage of Data Excellence

Getting your data in order isn’t just a technical exercise - it’s a strategic move. Companies that treat data as a core business asset are better positioned to pivot quickly, tailor offerings to customer needs, and make smarter decisions, faster.

As AI becomes more embedded in daily operations, the demand for clean, connected, and contextualised data is only going to grow. Future models will need even greater volumes of well-organised, high-quality data to function accurately and ethically; and the organisations that prioritise this now, will be the ones outpacing competitors tomorrow.

Wrapping Up: Data as the Cornerstone of AI Success

As we close out Solentive’s Data Month, the message is simple: the path to powerful, responsible, effective AI, starts with data. Prioritising data quality and governance isn’t just “good practice” – it’s your competitive edge.

Are you ready to strengthen your data foundation and maximise your AI initiatives? Contact Solentive today to explore how we can help you build a robust data strategy that sets you up for long-term success.