Generative AI
Custom AI development: Why tailored models outperform off-the-shelf AI
Enterprises navigating the AI revolution must decide between custom-built models and ready-made solutions, each offering unique advantages. While off-the-shelf AI solutions offer convenience and speed, they often struggle to meet specific business needs. Custom AI solutions, however, provide the flexibility to optimise complex processes, improve customer experiences, and extract actionable insights from data. This article explores the key distinctions between custom AI and off-the-shelf AI solutions, examining their impacts on business performance and decision-making.
Custom AI vs. off-the-shelf AI: Key differences
Choosing between custom AI development and off-the-shelf solutions presents a dilemma for many organisations. Off-the-shelf solutions offer quick deployment with lower initial investment, while custom AI provides greater accuracy and relevance. However, understanding the differences between these two methodologies is crucial for making informed decisions.
Off-the-shelf AI solutions are pre-trained models specially designed to perform general-purpose tasks. They are readily available and require minimal integration effort. However, their generic nature does not make them optimised for specific data and business processes. This can result in suboptimal performance issues and limited applicability to specialised tasks.
On the other hand, custom AI development involves building and training AI models from scratch or fine-tuning existing models with an organisation’s data. This approach provides greater control over model architecture, training parameters, and integration with existing systems. While custom AI requires more time, resources, and expertise, it can deliver better results in terms of accuracy and efficiency.
The choice between off-the-shelf solutions and custom AI depends on several factors, including problem complexity, data availability, the level of expertise within the organisation, and the desired level of performance. Therefore, organisations with unique data characteristics, specialised requirements, or a strong focus on innovation often benefit more from custom AI development.
Limitations of off-the-shelf AI
Off-the-shelf AI solutions are specifically designed to cater to various use cases by utilising pre-trained models and generic datasets. While this approach may suffice for basic tasks, it often fails to address tasks with unique complexities and data characteristics. Several key limitations contribute to the underperformance of off-the-shelf AI:
- Data Mismatch: Off-the-shelf AI models are trained on publicly available datasets, which may not accurately reflect the statistical properties and domain-specific features of an organisation’s internal data. This discrepancy can result in poor performance and unreliable predictions.
- Integration Challenges: Incorporating off-the-shelf AI solutions into existing IT infrastructure and workflows can present significant integration challenges. Data format inconsistencies, compatibility issues, and the need for extensive customisation can offset the initial cost savings associated with generic solutions.
- Inadequate Accuracy: Off-the-shelf AI models often exhibit lower accuracy compared to custom-built models trained on specific datasets relevant to the business. This can lead to suboptimal decision-making and reduced operational efficiency.
Advantages of custom AI development
Custom AI model development provides a strategic way to leverage AI, enabling organisations to overcome off-the-shelf limitations and unlock their data’s full potential. By tailoring AI models to specific needs, organisations can achieve significant improvements in accuracy and efficiency. The key advantages of custom AI development include:
- Tailored Solutions: Customised AI models are specifically designed to address particular challenges and objectives, offering more precise and effective solutions compared to generic alternatives. This tailored approach ensures that the AI model perfectly aligns with the organisation’s unique requirements and data characteristics.
- Data Ownership: Organisations gain complete ownership and control over the data used for training custom AI models. This ensures data security, privacy, and compliance with regulatory requirements. This level of control is crucial for organisations handling sensitive and proprietary data.
- Competitive Advantage: Custom AI development allows organisations to innovate faster, develop unique products or services, and stay ahead of competitors who rely on generic solutions. By leveraging customised AI solutions, organisations can optimise operations, develop personalised customer experiences, and gain deeper insights into their data. This helps them establish a sustainable competitive edge.
Industry applications of custom AI models
Several industries have leveraged custom AI development to achieve superior operational efficiencies and business outcomes. Some notable applications include:
- Manufacturing: Custom AI models facilitate anomaly detection in production lines by using statistical process control (SPC), time series analysis, and machine learning-based classification techniques. These models enhance predictive maintenance and operational reliability.
- Healthcare: AI-driven predictive models assist healthcare providers in forecasting patient readmission risks. By, leveraging Electronic Health Records (EHR) and employing advanced algorithms such as logistic regression, support vector machines (SVMs), and gradient boosting models can improve patient care and reduce readmission rates.
- Supply Chain Management: Custom AI solutions can automate repetitive tasks, enhancing productivity and minimising human errors. Techniques such as natural language processing (NLP) streamline document analysis, while robotic process automation (RPA) facilitates task execution and operational efficiency.
How can Infosys BPM help?
Infosys BPM recognises the transformative potential of AI and offers end-to-end custom AI model development services. With deep domain expertise and advanced AI capabilities, Infosys BPM delivers enterprise AI solutions designed to enhance operational efficiency, drive digital transformation, and ensure competitive sustainability.
