A recent MIT Sloan Management Review and Boston Consulting Group study revealed that only 10% of companies using AI solutions are fully satisfied with the realized ROI. This disconnect often occurs because machine learning initiatives are highly technical and typically handled by data science professionals, leading to a gap between those developing AI models and the business stakeholders who could benefit from them.
As businesses increasingly recognize the potential of AI, this disconnect becomes particularly relevant when considering the choice between custom and off-the-shelf solutions. The decision regarding which type of AI solution to implement is not merely a technical choice; it is a strategic one that requires alignment between technical capabilities and business objectives.
Custom solutions may offer tailored functionalities that align closely with specific business needs, while off-the-shelf solutions provide quicker deployment and lower upfront costs. However, without effective communication and collaboration between data scientists and business leaders, organizations may struggle to determine which option will best serve their unique operational requirements.
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Amit Kumar Jena | Lead- AI/ML
Amit is an experienced AI professional with proficiency in Python libraries like Pandas, NumPy, Matplotlib, Seaborn, scikit-learn, and statsmodels. He comes from a strong background in data cleaning, preprocessing, and feature engineering. His expertise extends to statistical models, machine learning, predictive analytics, NLP, and deep learning techniques, including Ridge and Lasso Regression. At Kanerika, he leads the AI team with actionable strategies to help our clients navigate AI implementation and fully harness their data’s potential.
In this webinar, we’ll guide you through the crucial factors to consider when deciding between custom AI and off-the-shelf AI, while showcasing our custom-made solutions.
Kanerika is a leading provider of end-to-end AI, Analytics, and Automation solutions with years of implementation expertize.
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