ARTICLE | ARTIFICIAL INTELLIGENCE| Modern Data Platform
Why Your Data Platform Is Holding Back Your AI Ambitions
20 October , 2025
– Rousseau Kluever, Executive: Data & AI, Decision Inc.
Every organisation wants to take advantage of AI.
Executives are exploring where it fits, data teams are experimenting, and business units are eager to see what it can deliver. For many, progress slows before they see any real value.
The challenge isn’t always with the AI tools or the people driving them. The real issue lies in the data foundation these ideas depend on. Most companies are still trying to build modern AI solutions on platforms that were designed years ago for a very different purpose.
Legacy Data Foundations: The Real Issue at Hand
Traditional data platforms were built to answer one question: What happened?
They were designed for reporting and historical analysis, not for prediction, automation, or real-time decision-making. These systems still have their place, but they were never built for the kind of intelligence that organisations now expect. They start to fall short when you need to bring together large or complex data sets, or when the business wants insights in real time. Most legacy platforms weren’t designed to support machine learning models, real-time data streams, or the level of flexibility AI demands.
Data is spread across multiple systems, pipelines are slow, and governance relies on manual checks that make it difficult to trust or scale what’s produced.
In practice, this looks like late reports, conflicting numbers across departments, and data teams spending more time fixing problems than delivering new insights. Over time, that slows innovation and keeps AI initiatives stuck in planning mode instead of driving measurable outcomes.
So, while the business is ready to move forward with AI, the data platform keeps holding it back.
Traditional vs Modern, AI-Ready Data Platforms
If you compare the two, the difference is clear.
Traditional Platforms
- Built for reports and static dashboards
- Relies on batch data updates
- Hard to scale and integrate
- Manual governance and security
AI Ready Platforms
- Built for continuous analysis and learning
- Operates in real time
- Unified across all data types
- Centralised and automated controls
Traditional platforms were designed to describe what happened. AI-ready platforms are designed to predict what will happen next and to keep learning as new data arrives.
An AI-ready data platform doesn’t replace analytics; it builds on it. It creates a single environment where data engineers, analysts, and AI developers can all work from the same trusted source of data, with the flexibility and speed that AI-driven decision-making depends on.
Platforms like Microsoft Fabric and Databricks play a crucial role in this transformation. Both simplify complex data landscapes by unifying engineering, analytics, and AI within a single, scalable environment. The choice between them depends on your organisation’s ecosystem and goals. Fabric is ideal for Microsoft-centric businesses looking to extend Power BI and Azure investments, while Databricks offers deep flexibility and open-source compatibility for multi-cloud strategies.
Bridging the Gap with Modern Platforms
Microsoft Fabric
Microsoft Fabric brings together everything a modern data platform needs – data engineering, warehousing, real-time analytics, data science, and BI – into one unified, cloud-based environment.
For organisations already using Power BI, Fabric is the natural next step. It builds on the tools they already know and extends them into a full, scalable data platform built for AI.
Fabric simplifies the complexity that’s been slowing data teams down:
Unifies data across business domains and systems
Unifies data across business domains and systems
Streamlines governance and access management
Enables faster, more accurate decision-making through real-time analytics and predictive modelling
Databricks
Databricks offers an equally powerful foundation, designed for organisations that want an open, flexible, and scalable approach to data and AI. Its Lakehouse architecture combines the reliability of data warehouses with the flexibility of data lakes, allowing teams to:
Ingest and analyse structured and unstructured data at scale
Build, train, and deploy machine learning models efficiently
Enable cross-functional collaboration across data engineering, science, and analytics teams
Both platforms empower organisations to move from fragmented, reactive data systems to unified, intelligent environments that accelerate AI adoption.
What This Looks Like in Practice
The benefits become clear once you see these platforms in action:
• In financial services, they combine customer, transactional, and risk data to improve fraud detection and credit decisioning.
• In retail, they unify sales, marketing, and supply chain data to enable accurate forecasting and reduce stockouts.
• In mining and manufacturing, they help teams stream and analyse sensor data in real time to predict maintenance issues and improve operational safety.
One example is our recent work with NEOM, a global smart city initiative. By implementing Microsoft Fabric, the organisation reduced time-to-insight by 80% and increased data engineering productivity by 25%, creating a single, governed data environment that now supports their wider AI and analytics strategy. You can read the full case study HERE.
How to Accelerate This Transition
Modernising a data platform is often a complex and time-consuming task. It can take months to design, build, and align teams before any value is realised. But there is a way to move faster.
The Decision Inc. 4-Week Data Platform Accelerator, available for both Microsoft Fabric and Databricks, helps organisations make this transition quickly and confidently.
In just four weeks, we work with your internal teams to:
Connect a key data source
Set up a production-ready environment
Establish governance and best practices.
Equip your people to manage and grow the platform themselves
It’s a focused, low-risk way to modernise your data foundation and prepare for AI without long project timelines or heavy consulting overhead.
For organisations unsure where to begin, the Accelerator pinpoints the highest-value starting point where connected and governed data can deliver visible results quickly and create momentum for broader adoption.
If you’d like to learn more about how the Accelerator works, you get all the information in our brochure
About Decision Inc.
Decision Inc. is your advisory-led cloud & AI partner, combining deep contextual insight and Architecture expertise with the scale to accelerate your move from strategic intent to measurable outcome.
Learn more at www.decisioninc.com.