Commercial Procurement of AI-based Solutions

The Challenge

Nearly all C-suite executives view artificial intelligence (AI) as an enabler in developing a digital mindset and enterprise culture that drives real-time insights into business decisions. However, due to the lack of a clear definition and scope, AI tends to be deployed in silos such as enterprise resource planning (ERPs), workplace solutions, and IoT platforms, often by teams with nominal expertise and strategic integration goals. To strategically procure and integrate AI into data-rich organizations, it is crucial to assess commercial considerations, risk factors, critical control points, algorithmic transparency, IT integration, and implementation challenges with a holistic, equitable, and ethical lens. A framework to navigate the complexity of commercial AI procurement can help organizations overcome the difficulties associated with procuring and integrating AI into various functions. ​

The aim of this workstream is to create robust guidelines and a practical toolkit to facilitate effective, optimized, and responsible procurement of AI/ML in commercial organizations. The underlying baseline framework will provide practical guidance to companies as they procure an evolving spectrum of AI and machine learning technologies.​

The Opportunity

This project aims to simplify the terminology surrounding existing AI technologies to improve practical understanding and engagement by procurement and business professionals while facilitating their communication with technology experts. ​

Second, mapping AI and ML algorithms embedded in commonplace enterprise software across organizational functions is crucial to building a holistic AI/ML deployment approach capable of achieving various organizational goals. ​

Third, the toolkit can help commercial organizations evaluate AI/ML technologies through a robust procurement framework that takes a holistic view of business, technology, risk, and equity considerations. The toolkit combines these variables and provides a starting point for executives to make informed and agile decisions for AI procurement.​

Key dimensions of the anticipated commercial procurement toolkit:​

  • Baseline terminology and structure in IT/software procurement​

  • Landscape map of existing AI/ML systems embedded in commercial applications​

  • Map and analysis of stakeholders supporting the AI procurement process​

  • Overarching guidelines and framework for AI procurement ​

  • An “AI Procurement Decision Model” to benefit procurement practitioners​

How to engage

Nominate experts, policy-makers, or senior executives to provide ongoing input on the project.

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