How to Break Down Data Silos and Scale AI with Forrester Report

🔍 AI Solutions Sunday Only 27% of government agencies say they use data effectively. (Source: IBM Center for The Business of Government, 2023) Fragmented data across departments leads to blind spots, duplicated efforts, and delayed decisions. Citizens get stuck. Teams operate in silos. Services lose effectiveness. The Fix: 💡 AI-Powered Data Fabric • Integrates structured and unstructured data across systems • Creates a unified view of citizens, services, and operations • Enables real-time analytics to support faster and smarter decisions • Supports predictive modeling to anticipate needs before crises occur The Impact: ✅ Breaks down silos ✅ Unlocks deeper insights ✅ Supports data-driven policymaking ✅ Builds trust through transparency and speed ⸻ 📢 Imagine a future where every service delivery is based on real-time data and proactive insight. What would that change in your agency or region? #AISolutionsSunday #GovTech #PublicSector #DigitalTransformation #AI #DataDriven #CitizenExperience #DataFabric #OpenGovernment #Modernization

🌪️ The AI paradox: more than 40% (!) of enterprise AI initiatives were reportedly discontinued in 2025, despite ever growing investments by companies ❌ Top obstacles appear to be data readiness, cost (and ROI), and security concerns ☁️ When it comes to data, it's more than 65% of AI projects that fail due to data readiness issues At Oliver Wyman, our experience with the AI transformation of our clients demonstrated the necessity to put as much effort in improving the AI-readiness of their data as in defining and deploying a roadmap of AI use cases This will allow to avoid some traps and adopt the right approach: 🪤 Beware of the POC trap! Successful proofs of concept are encouraging... but they come with a bias: they are often run on an AI-ready subset of data, giving the impression that scaling will be an easy next step. In reality, companies usually face limited data continuity across systems or business units, and variable data quality 🧭AI-readiness of data should even be one of the top criteria to prioritize use cases: on top of business impact and technology maturity, make sure to start your roadmap with use cases fueled by AI-ready (or easy-to-improve) data 🗺️ Deploy a structured and systematic approach to make your full data landscape AI-ready: initial mapping of data landscape, assessment of datasets on 3 main dimensions (accessibility, connectivity, quality), pragmatic action plans 🎆 To succeed in your AI transformation, discover our 7 key principles to successfully scale AI: https://owy.mn/4c91Rwb #AI #GenAI #transformation #digital #data

Integrating AI into your data pipelines is no longer just a luxury; it's becoming essential for businesses that want to stay ahead. Research shows that organizations employing AI are 2.5 times more likely to achieve business goals. This underscores the importance of synergy between data management and intelligent systems. Our latest article explores how Cortex AI-SQL simplifies this integration, allowing teams to leverage AI without getting bogged down by complexity. The ability to transform data processes not only enhances efficiency but empowers developers and data scientists to focus on innovation rather than routine tasks. We invite you to read about the implications of this technology and how it can redefine your approach to data management. We'd love to hear your thoughts on how AI is shaping your data strategies. #DataScience #MachineLearning #CloudComputing #AIIntegration #SnowflakeDevelopers https://lnkd.in/dK4fpHCQ

✦ Contrarian Insight: Many decision-makers assume that successful AI initiatives require massive amounts of data. In reality, just 10% of enterprise data can provide actionable, high-impact insights. ✦ Problem: The misconception that “more data equals more value” leads companies to pour resources into vast data lakes. Yet, up to 90% of this data often goes unused — overwhelming teams, increasing storage and management costs, and diverting focus from high-value opportunities. ✦ Solution: Shift your approach to data and AI by aligning strategy with specificity and impact. Here's how: ☑ Prioritize Data Relevance: Start with cleaner, curated data. AI thrives on signal, not noise. ☑ Create a Targeted Data Strategy: Define clear business objectives and map out which data types matter most to your AI use cases. ☑ Strengthen Data Ops: Invest in scalable data governance and infrastructure. Trusted, accessible data accelerates AI ROI. ☑ Apply AI Intelligently: Deploy AI models where the data is strongest and the outcomes are measurable—be it forecasting, process optimization, or customer insights. ✦ Let’s Talk: Effective AI doesn’t start with more data — it starts with the right data. At Promptly Solutions, we help organizations design smart data strategies that make AI work. Book a consultation → promptlysolutions.com. #AI #EnterpriseAI #TechStrategy #BusinessConsulting

More data isn’t the answer. Smarter use is. Only 15% of companies actually get value from their data investments (Turning Data Into Wisdom, 2025). The rest? Stuck making decisions with inaccurate dashboards and inconsistent reports. The takeaway: You don’t need more data. You need a team that knows how to use it. Here’s what high-performing teams do differently: - Align around one clear source of truth (no competing dashboards). - Build skills intelligence, knowing if the team has the capabilities to act on insights. - Treat AI as an enabler, not a replacement, embedding it into workflows that reduce noise and accelerate action. The result? Faster decision-making, fewer missed opportunities, and digital initiatives that actually meet business goals. 🖊In our latest blog, Carlos Saito shares how brands can move from data overload to data clarity, and why the real advantage isn’t just the tool, but the team behind it. 🔗 Read the full blog here: https://lnkd.in/eW4KXgFD #data #ecommercegrowth #strategy #ai #hatchecom

For mid-market enterprises, regulatory pressure and data complexity keep climbing. Without a governed foundation, even the best AI plans can stall. Being “data-driven” isn’t just a buzzword. It’s the difference between running on hunches or on actionable insight. But without clean, governed, well-structured data, AI adoption and analytics stall fast. Ntirety's expanded Data Services—including our Data Readiness and Managed Data Lakehouse offerings—give mid-market firms the enterprise-grade foundation they need to activate AI and modernize operations. And with more than 90% of enterprise data unstructured, Ntirety helps unlock that hidden value so it can fuel BI, AI, and analytics. Without governance, AI initiatives don’t just stall—they scale risk faster than value. Get AI-ready by getting data-ready. https://lnkd.in/eZEpH6xn #DataServices #AIReadiness #DataModernization #Ntirety #FutureReady #MidMarket #UnstructuredData

AI + Graph Meets Unified, Contextualized IT Data Reading Charles’s excellent post on Solving Tech Debt With AI + Graph: Charles Betz [https://lnkd.in/gQTqsaSQ] “What I believe is a powerful new substrate: a unified IT knowledge graph. This may be the true successor to the long-troubled configuration management database (CMDB).” At Flexera, our data strategy is built on one idea: make IT data consistent, contextualized, and connected so it’s truly actionable. Our foundations: Normalize and unify IT assets into a single, consistent view  Add business context (ownership, risk, compliance, cost)  Build relationships across assets, contracts, and dependencies  Power it all with AI + analytics to deliver clear actions and recommendations As Forrester highlights, the future of IT isn’t just collecting data — it’s understanding dependencies and making smarter decisions. At Flexera, our mission is simple: help customers reduce risk, optimize spend, and govern with confidence — powered by trusted, connected data. #TechnologyIntelligence #Flexera #AI #DataStrategy #ITGovernance 

Data is everywhere in the public sector, but too often it isn’t delivering its true value. As Scott Cutts points out in his new blog, data only becomes powerful when it’s treated as a product; designed for users, built for longevity and trusted to inform real decisions. So, what does that mean in practice? 🔹 Data-as-a-product – reusable datasets that inform planning and operations. 🔹 Insight products – dashboards and reports that guide policy and action. 🔹 Data-driven services – operational tools powered by trusted data. When public sector organisations adopt this mindset, the benefits are clear: 🔹 Faster decisions based on evidence. 🔹 Products that adapt to citizen needs. 🔹 Interoperable systems scalable across various domains. 🔹 Stronger foundations for responsible AI implementation. The catch? Many programmes stumble by focusing on tech over users, or by treating data as one-off project work rather than something to maintain, iterate and reuse. Scott’s blog unpacks how public sector teams can overcome these pitfalls and why a product-oriented approach is key to unlocking both today’s value and tomorrow’s AI opportunities. Read his insightful blog here: https://lnkd.in/eH73xyQa #PublicSector #DataStrategy #AI

AI has quickly become the headline act in almost every boardroom conversation. Leaders see it as the tool that will unlock efficiency, agility, and most importantly, growth. And they’re not wrong! When used correctly, AI absolutely has the power to grow businesses. For data professionals working with businesses, the best thing you can do to support this is to listen closely.👂 You may find that business executives are not usually talking about model optimisation, data quality pipelines, or governance frameworks. Instead, they’re framing AI in terms of high-level outcomes that feel achievable to them. So, things that connect directly to business growth. Quantexa lays out some great ways of achieving growth, built to be tangible for business leaders: ➡️ Automating processes to free up resources ➡️ Building searchable knowledge bases ➡️ Forecasting demand more accurately ➡️ Strengthening cyber-defences ➡️ Spotting anomalies that skew decision-making Now, for many data professionals, these aren’t groundbreaking concepts. But they will act as the common ground between executive expectation and the data team’s technical capability. That’s why understanding AI from this business-oriented perspective matters, because if you know the lens through which leaders see AI, you can meet them where they are. 🤝 Data professionals who can position themselves as the translator, who can turn broad AI ambitions into practical, data-driven outcomes, will increase the likelihood of future AI and data initiatives actually succeeding. Over the past few weeks, we’ve been sharing insights from Quantexa’s info-packed report all about AI and its growing role in business decisions. That’s all from us on this for now, but if you’ve missed any of our posts about it, or you fancy a longer read, we’d highly suggest popping over to the link below to access the full report!⬇️ https://lnkd.in/e7S-tbfj #AIInvestment #DataForAI #Metadata #DataStrategy #AITransformation