AI Implementation - Evaluating External Vendors

Evaluating External Vendors

When considering the implementation of AI solutions, the role of external vendors is crucial. They provide the necessary expertise, technology, and support that can accelerate the AI journey. However, if an external vendor is to be used, selecting the right vendor requires a careful evaluation of various factors.

Business Needs and Objectives: Define the problems AI is expected to solve and the business objectives to guide the vendor selection process.

Vendor Portfolio and Experience: Review the vendor's portfolio, client references, and expertise in relevant technologies.

Proof of Concept: Request a PoC to understand the vendor's approach to your problem, ensuring it works with realistic data volumes.

Scalability and Adaptability: The vendor should demonstrate their ability to handle data challenges and scalability needs.

Engagement Model: Choose an engagement model (staff augmentation, project-based, hybrid CoE, or outcome-based) that aligns with your AI strategy.

Scope of Work: The vendor should provide a detailed scope of work, including timelines, milestones, and costs.

Key Performance Indicators (KPIs): The vendor should understand your KPIs and articulate how their solution will improve your business results.

Stakeholder Inclusion: Include all stakeholders in the vendor selection process.

Additional Considerations: Check if the vendor provides knowledge sharing, has competencies beyond building machine learning models, and offers pre-built technologies for expedited projects.

Key Questions to Ask Each Potential Vendor:

1. How long have you been offering AI solutions?
2. Do you have any use cases and/or examples you can share that align closely with my industry or organization’s needs?
3. Do you have alliances with multiple vendors and an ecosystem to deliver me a complete solution?
4. Do you have the resource bench to assist me in deploying this solution across the enterprise and across geographies (probe for roles like data scientists, data engineers, machine learning architects, service engineers, etc.)?
5. Can you integrate the AI solution with my existing IT footprint?

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References:

https://connect.comptia.org/content/guides/business-considerations-before-implementing-ai

https://indatalabs.com/blog/data-science-vendor-selection-guide