Pursuing an AI Strategy: Construct, Acquire, or a Combined Approach?
In today's business landscape, AI (Artificial Intelligence) has become a common term, but the term "AI-powered" is often used excessively without substantial AI capabilities. Forbes Technology Council outlines key factors to consider when deciding between building in-house AI solutions, buying off-the-shelf AI products, or adopting a hybrid approach.
- Cost and Budget
- Building in-house requires significant upfront investment in talent, infrastructure, and ongoing development, which can be a steep cost for many organizations.
- Off-the-shelf solutions tend to have lower initial costs but may involve subscription or licensing fees.
- A hybrid approach balances costs by combining custom development with existing tools.
- Time to Market
- Purchasing ready-made AI solutions typically allows for faster deployment, ideal for businesses looking for quick results.
- Building in-house takes longer due to development and testing cycles.
- Hybrid solutions can accelerate timelines by leveraging existing components while customizing specific features.
- Customization and Control
- In-house development offers maximum customization and proprietary control over the AI system.
- Off-the-shelf products might lack flexibility to fit unique business needs.
- Hybrids give some level of customization while leveraging proven technologies.
- Expertise and Talent Availability
- Building AI solutions requires skilled data scientists, engineers, and developers who may be scarce or expensive.
- Buying off-the-shelf reduces dependency on in-house AI expertise.
- Hybrid approaches depend on balancing available internal skills with external solutions.
- Integration with Existing Systems
- In-house solutions can be built for seamless integration with current IT infrastructure.
- Off-the-shelf products might pose integration challenges or require workarounds.
- Hybrid solutions can tailor integration strategically.
- Scalability and Maintenance
- In-house systems require ongoing maintenance and scaling efforts handled internally.
- Off-the-shelf solutions often include vendor-managed scaling and updates.
- Hybrid models split these responsibilities accordingly.
- Security and Compliance
- Sensitive data or strict regulatory environments may favor in-house for greater control and compliance assurance.
- Vendor solutions must be carefully vetted for data security and compliance.
- Hybrid approaches negotiate these concerns by design.
- Innovation and Competitive Advantage
- Custom solutions can provide unique capabilities that differentiate the business.
- Off-the-shelf AI tends to be more generic but benefits from vendor innovation.
- Hybrids allow combining innovation with proven technology.
In conclusion, the choice depends on balancing cost, speed, customization, talent, integration, maintenance, security, and strategic goals, often leading organizations to select a hybrid approach that optimizes benefits while mitigating drawbacks. Hybrid solutions protect ownership of proprietary features, while also enabling the integration of external AI capabilities and large datasets.
It's essential to remember that the practice of overhyping AI capabilities is known as "AI washing." Building an AI solution from scratch can provide customization and control, but it may be expensive and time-consuming for smaller organizations. Off-the-shelf AI solutions may be ideal for teams with limited AI expertise, but they may struggle with industry-specific compliance requirements and differentiating their offering from competitors using the same tool.
Vall Herard, the CEO of Saifr, a company offering powerful safeguards against compliance risks, emphasizes the importance of moving past AI washing and implementing AI with intent for potential competitive advantage. Hybrid AI solutions, combining build and buy, can be an effective approach for many organizations, accelerating innovation while preserving flexibility.
- Vall Herard, the CEO of Saifr, advocates for the implementation of AI with intent, discouraging the practice of "AI washing", which overhypes the capabilities of an AI system.
- Hybrid AI solutions, a combination of in-house development and off-the-shelf AI products, can provide a balance between customization, control, and the integration of external AI capabilities, ultimately accelerating innovation while preserving flexibility.
