Challenges of Data Silos in AI

Your SAP AI is only as good as your Data infrastructure. No clean data → No business impact. SAP is making headlines with AI innovations like Joule, its generative AI assistant. Yet, beneath the surface, a critical issue persists: Data Infrastructure. The Real Challenge: Data Silos and Quality Many enterprises rely on SAP systems - S/4HANA, SuccessFactors, Ariba, and more. However, these systems often operate in silos, leading to: Inconsistent Data: Disparate systems result in fragmented data. Poor Data Quality: Inaccurate or incomplete data hampers AI effectiveness. Integration Issues: Difficulty in unifying data across platforms. These challenges contribute to the failure of AI initiatives, with studies indicating that up to 85% of AI projects falter due to data-related issues. Historical Parallel: The Importance of Infrastructure Just as railroads were essential for the Industrial Revolution, robust data pipelines are crucial for the AI era. Without solid infrastructure, even the most advanced AI tools can't deliver value. Two Approaches to SAP Data Strategy 1. Integrated Stack Approach:   * Utilizing SAP's Business Technology Platform (BTP) for seamless integration.   * Leveraging native tools like SAP Data Intelligence for data management. 2. Open Ecosystem Approach:   * Incorporating third-party solutions like Snowflake or Databricks.   * Ensuring interoperability between SAP and other platforms. Recommendations for Enterprises * Audit Data Systems: Identify and map all data sources within the organization. * Enhance Data Quality: Implement data cleansing and validation processes. * Invest in Integration: Adopt tools that facilitate seamless data flow across systems. * Train Teams: Ensure staff are equipped to manage and utilize integrated data effectively. While SAP's AI capabilities are impressive, their success hinges on the underlying data infrastructure. Prioritizing data integration and quality is not just a technical necessity → It's a strategic imperative.

“We were constantly reinventing the wheel. It felt like every project team was spinning up the same data pipelines - just in slightly different ways.” – A Lead Data Engineer I spoke with recently Data silos aren’t just a technical problem - they’re a very real, very human challenge. ↪️ Inefficiency is everywhere. Simple data requests take days or weeks, and teams unknowingly duplicate work. ↪️ Nobody trusts the numbers. Multiple versions of the same dataset exist, and no one knows which is correct. ↪️ Scaling only makes it worse. More teams, more tools, more data - without a plan, silos multiply. ↪️ Finding data is a nightmare. Without a single “home” for data, teams waste time searching instead of analyzing. ↪️ Budgets are bleeding. Redundant storage, duplicated tooling, and wasted engineering hours quietly drain resources. Silos slow teams down, erode trust, and burn budgets. But there’s a way out. The right culture and infrastructure ensure data is owned, governed, and easily discoverable

Agents are going to be everywhere, but the problem is they only know how to talk to other agents within the isolated environment of their platform. Your Salesforce agent doesn’t know what your Snowflake agent knows. Your Google Workspace agent is cut off from the other vendor-built agents you have operating within your company. Instead of a connected AI ecosystem, we’re creating islands of intelligence, each locked inside its own vendor’s world. We’ve seen this before. Data silos forced companies to consolidate data into warehouses and lakes. But AI silos are different, the solution isn’t just about aggregating data into a central repository. Agents don’t just store information, they act on it, and without real-time cross-platform communication, they remain disconnected, unable to collaborate. The fix? A shared language and communication platform for agents. Just as APIs unified SaaS, data streaming can connect AI agents, allowing them to work together in real time instead of operating in isolation. In my latest blog post, I wrote about what I call the AI Silo Problem. Check it out the link in the comments for more.

AI is only as powerful as the data behind it. Too many businesses are eager to adopt AI without addressing the biggest barrier to success: fragmented, unreliable data. In my latest piece for diginomica, I break down the four critical steps SMBs need to take to build a strong data foundation: ✔ Unify siloed data into a single source of truth ✔ Cleanse & prepare data to eliminate inconsistencies ✔ Implement governance for accuracy, compliance & trust ✔ Train AI models with business-specific datasets Taking care of your data first is essential, otherwise, AI-driven insights will be flawed at best and misleading at worst. Read the full article: https://acumati.ca/4jLF2lt

𝐂𝐈𝐎’𝐬 𝐍𝐞𝐱𝐭 𝐁𝐚𝐭𝐭𝐥𝐞: 𝐃𝐞𝐚𝐥𝐢𝐧𝐠 𝐰𝐢𝐭𝐡 𝐀𝐩𝐩 & 𝐀𝐏𝐈 𝐬𝐢𝐥𝐨𝐬 𝐭𝐨 𝐀𝐈 𝐀𝐠𝐞𝐧𝐭𝐬 First, we had application silos within the enterprise - every team hoarding their own applications to move fast but nothing was talking to other and pure chaos leading to data and workflows fragmentation. Then APIs and enterprise integration rolled in, promising magic fixes, but half the time they just piled on more knots for technology and IT teams to untangle with brittle data formats and messy API versions. Now, AI agents are the new kid on the block and guess what? Without a grip, we’re heading for silos all over again - smart ones this time, but still a nightmare. Every department cooking up its own AI agents? That’s a recipe for IT overload and business fumbles. We all have been around the block and I’m not here to panic - just to share what works. Here’s my take for CIOs and IT leaders like us: 𝟏. 𝐒𝐞𝐭 𝐒𝐢𝐦𝐩𝐥𝐞 𝐑𝐮𝐥𝐞𝐬 𝐄𝐚𝐫𝐥𝐲: Lay down clear guidelines for how AI agents get built and used. Keep data, security, and goals in sync across the board. It’s not about locking things down - it’s about making sure we don’t trip over ourselves later. 𝟐. 𝐌𝐚𝐤𝐞 𝐓𝐡𝐞𝐦 𝐏𝐥𝐚𝐲 𝐍𝐢𝐜𝐞: Pick AI tools that talk to each other, demand this from your vendors and fit with what you already have. Build AI agents team for your business, not a bunch of lone agent wolves. All of us in tech, have seen this movie before - app silos, API messes and none of us want a rerun with wild AI agents. Let’s tackle these silos now, keep it simple and turn AI into a win for everyone in the business. #AI #EnterpriseIT #SilosSuck #IT #CIO #CTO #EX #DX #SAAS