Modern businesses are investing heavily in AI, but outdated, disconnected systems often stand in their way. Without addressing how data flows between platforms, even the smartest tools can fall short. Is it time to stop patching problems and start building a foundation that works?
According to To Win With AI, Businesses Must Face Their IT Frankenstacks in Forbes, companies are struggling with complex technology systems that prevent them from using AI effectively. Many organizations have built their tech infrastructure by connecting different tools and platforms over time, creating hard-to-manage systems that don’t work well together.
A recent survey of over 500 marketers found that 57% faced technical integration problems when trying to implement AI, mainly due to disconnected or outdated systems. Instead of simplifying workflows, these systems pieced together over time often increase workloads for IT teams, who end up focusing on managing these systems rather than working on strategic initiatives.
The article suggests that success with AI doesn’t start with buying new tools – it begins with creating a solid framework of well-organized, connected data. Even linking data from just a few platforms in a broader setup can help companies uncover insights they hadn’t identified before.
Why This Matters
Most companies have spent significant resources updating their tech tools but have not addressed fundamental issues with how their data connects and flows between systems. This creates a significant challenge for AI implementation, as even the most advanced AI systems can’t deliver helpful insights when working with fragmented, disjointed information.
Benefits
- Less time spent on managing outdated systems
- Improved synergy between teams and tools
- More efficient application of AI for decision-making
- Easier access to actionable business insights
Concerns
- Costs and efforts associated with overhauling or refining existing systems
- Potential interruptions during system updates
- Requirement for training staff on new workflows
- Possibility of dependency on new platform vendors
Business Applications
- A data integration service designed for small businesses to connect current tools without replacing them
- Software that visualizes and tracks interactions between various business systems
- A consulting service aimed at helping businesses restructure data systems to enable AI readiness
As businesses adopt AI technologies, they face a choice between temporary fixes and sustainable changes. The organizations that thrive won’t simply rely on acquiring the latest AI tools but will prioritize establishing dependable systems for their technology. This involves making deliberate decisions about how to link systems and manage data in alignment with both their immediate goals and plans for expansion.
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