While 73% of executives plan to use AI to evolve their business model in 2025*, nearly half identify data quality as their greatest obstacle. In the race to adopt intelligent models, the winners won’t necessarily be those with the most advanced algorithms, but those with the strongest data foundations.
AI is a bandwagon you have to be on
Wherever you fall on the hype cycle, understanding the potential impact of AI is no longer optional for business leaders. It is a competitive imperative, with its benefits clear across multiple dimensions:
- Increased innovation and productivity through AI-optimised processes
- Smarter decision-making based on comprehensive data insights
- Lower operational costs through automation and predictive maintenance
- Smoother customer experiences through personalisation and responsive service
- Better risk management and compliance oversight
However, the rush to implement AI often overlooks a fundamental truth: AI systems are only as good as the data that powers them.
The true cost of messy data
According to Harvard Business Review, 46% of data leaders identify data quality as the greatest challenge to realising GenAI’s potential**. When data is fragmented across systems, inconsistently formatted or outdated, AI applications will make this worse by amplifying issues and accelerating mistakes. This leads to wasted investments, flawed decisions, scepticism about the potential of AI and missed opportunities.
Untapping proprietary data is your competitive advantage
While large language models (LLMs) like ChatGPT have captured the world’s attention, they’re built on publicly available data and deliver generic results by design – predictable, middle-of-the-road answers that work for everyone but excel for no one.
Applying AI to your organisation’s unique data assets is the real competitive advantage. When properly organised and leveraged, your proprietary information – customer interactions, operational metrics, historical performance and institutional knowledge – becomes your key differentiator, creating a sustainable competitive advantage that generic models simply cannot match.
Unified data platforms are the secret to AI success
If you’re running Microsoft in your organisation already, you’re well-positioned to leverage its integrated cloud ecosystem that centralises your data assets into AI-ready resources:
Azure Data Services enable unified data management, from ingestion to analytics
Power BI delivers real-time visualisation and reporting across previously disconnected systems
Microsoft Fabric provides end-to-end data analytics and AI capabilities
Microsoft Purview ensures comprehensive data governance and compliance
Microsoft Copilot puts AI at the fingertips of every employee
This integrated approach allows you to consolidate previously siloed data, from operational metrics to compliance information, into unified dashboards that provide comprehensive visibility. It also lays the groundwork for more advanced capabilities across diverse sectors such as manufacturing, logistics and healthcare.
By merging Operational Technology (OT) with Information Technology (IT), industrial operators can connect physical equipment to digital systems through the internet of things (IoT), creating intelligent operations that respond to real-world conditions in real-time.
Building a data foundations AI success
The path to AI success begins with strengthening your data foundations:
- Assess your current state: Understand your data assets, quality levels and governance practices
- Define clear business objectives: Identify specific, measurable outcomes AI should deliver
- Create scalable architecture: Build data foundations that can adapt to changing needs
- Measure and refine: Implement clear metrics to track progress and ROI
Organisations that follow this methodical approach typically establish their core data foundations within 6 to 8 weeks as the first step, positioning them to tackle specific high-value use cases quickly.
AI impact: Financial services firm achieves two-week transformation
When a major financial services provider faced a critical systems challenge, Nexon helped them migrate their entire customer service operation to an AI-enabled cloud platform in just two weeks.
Their prior investment in standardising data and processes meant they could focus on innovation rather than struggling with data integration. The result: reduced operational costs, improved customer experience and a foundation for ongoing AI-powered innovation.
Evaluate your competitive position in the AI race
Our AI Readiness Assessment will benchmark your organisation’s data foundation against industry standards and provide an executive roadmap for turning your proprietary data into a strategic advantage.
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Building AI-ready data foundations: A strategic leadership guide
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Contact our strategic advisors to discuss how we can help strengthen your organisation's data foundations for AI success.
* PwC: 2025 AI Business Predictions
** Harvard Business Review, Is Your Company’s Data Ready for Generative AI?, 2024
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