In today’s rapidly evolving technology landscape, the term “AI” gets thrown around frequently, often leading to more hype than substance. As an executive, you’re likely bombarded with vendors claiming to offer “AI-powered” solutions, making it challenging to separate reality from marketing fluff. When it comes to source-to-pay (S2P) platforms, understanding the true capabilities and underpinnings of a vendor’s AI offering is crucial for making informed decisions.
To help you navigate this complex terrain, we’ve expanded on our initial list of questions to ask about AI and compiled a list of essential questions you should ask your S2P vendors to gauge the depth and authenticity of their AI capabilities:
1. How much data do they have to train AI models?
The quality and quantity of data used to train AI models directly impact their accuracy and effectiveness. The larger the global pool of data, the more you can slice it up into aggregated and anonymized peer groups, such as benchmarks by industry, region, company size, and commodity. A larger data pool ensures that the recommendations and insights from these peer groups will be relevant and actionable.
Inquire about the volume of data your vendor has access to, as well as its relevance to the S2P domain.
2. Is the data privately or publicly sourced? Where did the data come from?
It’s essential to understand the origin of the data used for training AI models. Privately sourced data from real-world business transactions is often more valuable and relevant than publicly available datasets. One reason is the data quality. Private data is collected from real customer transactions, which makes it more accurate, granular, and reflective of real-world scenarios.
3. How are AI models trained, and on what kind of data sets?
Inquire about the vendor’s AI model training process, including the techniques used (e.g., supervised learning, unsupervised learning, transfer learning) and the data sources leveraged (private, public, or a combination).
Private data models can share data from ongoing business operations, providing continuous insights, rather than only periodic ones that might be outdated by the time they are released. Public datasets are also often focused on specific domains, whereas private datasets can span multiple customer demographics, patterns, locations, and behaviors. This provides richer insights and more robust modeling.
4. How frequently are AI models updated and retrained?
AI models need to be regularly updated and retrained to maintain their accuracy and relevance as new data becomes available. Ask about the vendor’s model update cadence and processes.
Red flags to watch out for include:
- AI becomes stale, and new data patterns emerge if models are updated infrequently (annually or less often).
- Vendors do not have well-defined transparent models for model updates.
- There’s little to no human oversight or testing before deploying models.
5. What specific S2P processes are enhanced by AI, and how?
Understand the specific areas of the S2P cycle where the vendor’s AI capabilities are applied, such as strategic sourcing, contract management, invoice processing, or supplier risk assessment, and the tangible benefits they provide. Knowing this will help you ensure the solution is comprehensive to your needs, reduce errors upstream, and provide meaningful value to your organization.
If an S2P vendor cannot provide satisfactory answers regarding their AI capabilities and processes, it raises concerns. Collaborate with your IT team so you can thoroughly review the vendor’s AI competence before proceeding.
How much domain expertise should S2P AI vendors provide?
When considering a vendor’s generative AI capabilities for source-to-pay processes, it’s crucial to assess their domain expertise for several important reasons:
- Contextual understanding: Domain expertise ensures the AI model understands the nuances and complexities specific to source-to-pay processes. This leads to more accurate and relevant outputs.
- Data quality and relevance: Vendors with deep domain knowledge are more likely to have access to high-quality, relevant data for training their AI models. This is especially important in source-to-pay, where the quality and specificity of data directly impact the AI’s effectiveness.
- Avoiding “AI-washing”: Some vendors may exaggerate their AI capabilities without having the necessary expertise to deliver truly valuable solutions. Domain expertise helps distinguish between genuine AI innovations and superficial implementations.
- Tailored solutions: Vendors with strong domain knowledge can better customize their AI solutions to address specific challenges in the source-to-pay process, rather than offering generic AI tools.
- Compliance and risk management: Source-to-pay processes often involve complex regulations and risk factors. Domain experts are better equipped to ensure AI solutions comply with industry standards and effectively manage procurement-related risks.
- Integration capabilities: Expertise in source-to-pay allows vendors to create AI solutions that integrate seamlessly with existing procurement systems and workflows, maximizing efficiency and user adoption.
- Continuous improvement: Vendors with domain expertise are more likely to understand evolving trends and challenges in source-to-pay, enabling them to continuously refine and improve their AI models.
- Practical application: Domain experts can provide real-world examples and use cases of how their AI solutions have improved source-to-pay processes, demonstrating tangible benefits.
- Strategic alignment: Vendors with deep knowledge of source-to-pay can better align their AI solutions with your organization’s procurement strategy and goals.
- Support and training: Domain expertise allows vendors to provide more effective support and training, helping your team maximize the value of the AI solution in the context of source-to-pay processes.
By assessing a vendor’s domain expertise in source-to-pay when considering their generative AI offerings, you can ensure that you’re partnering with a provider who truly understands your needs and can deliver AI solutions that add real value to your procurement processes.
The benefits of Coupa’s community-generated AI
At Coupa, we recognize the immense value of real-world, privately sourced data in building robust AI models. Our platform harnesses the power of “community intelligence” – a massive $6 trillion dataset of transactional data flowing through our system from over 3,000 customers and 10 million suppliers globally.
This unparalleled dataset, contributed by our extensive customer community, provides a rich and continuously evolving source of real-world business spend data. By training our AI models on this proprietary, privately sourced data, we can deliver intelligent insights, recommendations, and automation capabilities that are tailored to the unique challenges and nuances of the S2P landscape.
By combining comprehensive S2P data, process visibility, domain expertise, community intelligence, and prescriptive capabilities, Coupa delivers highly accurate and actionable AI-driven insights to help customers drive efficiencies, mitigate risks, and maximize value across their business spend operations.
Here’s a quick rundown of what makes Coupa stand out:
- Comprehensive AI models with vast rich data spanning all aspects of spend management to uncover insights and patterns that solutions with a narrow focus would miss. This translates to reduced errors upstream, such as in matching purchase orders to invoices.
- Domain-specific training allows our AI models to learn the nuances and complexities unique to S2P processes, leading to more accurate and relevant predictions and recommendations.
- Collective intelligence of a vast total spend community provides a continuous stream of real-world training data to keep AI models current and high-performing.
From optimizing strategic sourcing decisions and supplier management to automating invoice processing and detecting fraud, our AI models leverage the collective intelligence of our customer community to drive tangible value and operational excellence for your organization.
As you evaluate S2P vendors and their AI offerings, remember to look beyond the hype and dig deeper into the data sources, training methodologies, and real-world applications of their AI capabilities. By asking the right questions, you can make informed decisions and partner with a vendor that truly harnesses the power of AI to transform your S2P processes.
