Underneath the flurry and enthusiasm for agentic AI lies a consistent challenge that all CXOs contend with – the goal to harness emerging technologies without getting bogged down by complexities and integration challenges. Enterprises want to embrace the latest wave of innovation, but often adoption runs into friction.
A recent PwC survey found that 37% of leaders rank data availability and quality among the top barriers to scaling AI initiatives, highlighting a fundamental truth – a robust data strategy is key to AI success.
As we head into an agentic AI-driven future, the question for organisations is clear: how to drive tangible, needle-moving benefits with AI? With enterprises accelerating their shift toward data-centricity, they need to recognise the importance of AI-ready data to unlock timely insights and realise the ROI on AI investments. Gartner predicts that by 2026, 60% of AI initiatives unsupported by AI-ready data will be abandoned, underscoring the importance of data readiness.
The AI data readiness gap
Today’s data landscape is highly distributed and fragmented, with data spanning hybrid, multi-cloud, and on-premises environments. Companies operating in hyper-competitive business environments need to scale data usage significantly. Data engineers and scientists need access to trusted data, regardless of where it resides. Enterprises want to unlock and share data seamlessly across hybrid, multi-cloud environments to fuel AI, machine learning, analytics, and data-driven applications.
As businesses strive to scale data usage across diverse environments, they need to overcome significant hurdles in data discovery, quality, and governance to fully realise the value of their data assets.
Recent research underscores the critical data management challenges confronting Chief Data Officers today. Data and Analytics teams grapple with over 400 disparate data sources across enterprise environments, making data discovery a significant hurdle. Additionally, 46% of leaders cite data quality as a key concern, while only half of organisations fully comply with data governance mandates.
Moving beyond centralised data architectures
As data sources multiply, centralised data management solutions that once defined enterprise data strategy are now showing their age in the AI-driven economy. While traditional data management solutions provide foundational capabilities, they fail to deliver a unified view of data and distributed governance essential for agile, data-driven decision-making.
Moreover, organisations tethered to monolithic data architectures risk losing their edge to fast-moving competitors. Thus, necessitates the need for federated and scalable data management strategies that unify governance across the entire data estate, enabling agility and real-time decision-making at scale.
Data Intelligence: The foundation for AI-ready enterprise data
With AI becoming the backdrop of innovation, data intelligence is no longer optional — it is foundational to delivering reliable, actionable AI outcomes. The age-old principle “garbage in, garbage out” is a timeless reminder that poor-quality data compromises AI models and, ultimately, critical business decisions.
Data intelligence elevates data into trusted, AI-ready assets by leveraging metadata across four essential dimensions: context (defining the meaning and relevance of data), quality metrics (ensuring data accuracy and reliability), lineage (tracking data origins, transformations, and flow), and usage (understanding data consumers). It empowers organisations to deploy AI applications with confidence, driving consistent and dependable results.
How Data Intelligence platforms change the game
The Actian Data Intelligence platform is engineered to address the scale and complexity demands of AI and beyond. At the heart of the Actian Data Intelligence Platform is the federated knowledge graph delivering key components to bridge data sources and data use cases through metadata management — enabling data discovery, search, and use at scale.
In decentralised, hybrid environments, maintaining data quality, control, and governance at scale is paramount.
By supporting decentralised data ownership, the platform breaks down data silos and fosters collaboration between business and IT stakeholders and streamlines data discovery and consumption, enabling users to rapidly understand and leverage the precise data they need.
It delivers on this by making high-quality data products accessible while maintaining integrity throughout the data lifecycle. Its federated knowledge graph-powered search engine provides contextually relevant insights, enforces compliance through comprehensive audit trails. Additionally, natural language query capabilities democratise data access, breaking down technical barriers and accelerating self-service analytics across the enterprise.
Compliance without compromise: Real-world applications across industries
In today’s complex regulatory and operational landscape, the Actian Data Intelligence Platform, powered by federated knowledge graphs, empowers organisations to harness distributed data while maintaining centralised governance and compliance.
Below use cases illustrate how federated knowledge graphs serve as the connective tissue across distributed data ecosystems, delivering centralised oversight and governance without hampering data sovereignty or speed.
Oil & Gas: In the regulated oil and gas sector, by streaming well-head telemetry to an edge cluster in Liwa and analysing it alongside historical drilling data housed on a private cloud in Dubai, operators can proactively detect vibration anomalies signalling potential downtime. This federated model ensures petabytes of sensitive data remain localised, while delivering actionable insights in real time.
Financial services: In banking, core banking records stored on-premises can be dynamically combined with cloud-based customer experience logs to generate real-time risk scores. This integration adheres strictly to the UAE’s data localisation mandates, demonstrating how federated approaches enable compliance without compromising agility.
Smart cities: Traffic, energy, and citizen-service sensor data are unified within a single knowledge graph, allowing urban planners to anticipate demand surges and prevent gridlock. Crucially, personally identifiable information remains within the region, preserving privacy and regulatory compliance while enabling holistic city management.
Building trust at scale
In today’s dynamic and regulation-driven Gulf region, UAE enterprises require a unified, holistic view of data across the edge, on-prem, and cloud environments — without sacrificing data sovereignty. Powered by the Actian Data Intelligence Platform’s federated knowledge graph architecture and aligned with HCLSoftware’s XDO Blueprint, organisations can securely connect distributed data sources while fully complying with localisation mandates. This approach also elevates data from a siloed afterthought to a strategic asset, enabling real-time, governed access to insights across legacy and cloud systems — breaking down barriers, building trust in data, and accelerating informed, AI-driven decision-making.
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