- Data Disparity: Your datasets are dispersed across multiple silos without a unified view, hindering effective data analysis for AI/ML.
- Unclear Business Objectives: Without well-defined business problems and corresponding data mapping, your organization cannot identify valuable AI/ML use cases.
- Cross-Functional Misalignment: Lacking a collaborative ecosystem among product management, domain experts, and AI/ML specialists can prevent meaningful integration of AI/ML into business processes.
- Limited Data Operations: Your data volume is insufficient for significant AI/ML insights, and without preliminary model testing, the utility of AI/ML is questionable.
- Technology Stack Assessment Gap: Your data science team has not yet evaluated major cloud AI/ML and MLOps offerings, which is essential before committing to an AI/ML platform.
- Model Deployment Inexperience: The absence of experience with deploying machine learning models at scale on cloud platforms indicates that your organization might not yet be ready for an AI/ML platform.
- Cloud Integration Deficiency: Running on a major cloud provider without having experience deploying models integrated with cloud-based databases or CDPs suggests a lack of technical preparedness.
- Business-Tech Disconnect: Missing alignment and understanding between your business goals and technology capabilities, coupled with uncertainty about data privacy and compliance, poses significant risks.
- Strategic Incongruence: If AI/ML initiatives do not align with your company's product roadmap, then investing in an AI/ML platform may not support your business strategy.
- Adoption Ambiguity: Not having a defined path for how AI/ML will be leveraged for text, video, recommendations, forecasting, etc., leads to uncertainty in the adoption of an AI/ML platform.
In many companies, I observed these challenges.
If you are a startup, or SMB looking to apply AI/ML in your solutions, We can connect and collaborate on your AI Strategy. My coordinates [sivaram2k10][at][gmail]
Keep Exploring!!!
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