First and foremost, we need to ask ourselves whether Artificial Intelligence (AI) and Machine Learning (ML) have been bolted on as an afterthought, or incorporated into builds and implementations from the start.
Trendy, noisy marketing promises massive transformation in the near future thanks to these emerging technologies, but without specialist, strategic intent and knowledge, the output is only as good as the input.
Garbage in, garbage out, as they say. Therefore, when considering any conversation with a software vendor, but especially vendors of contract management software, it is crucial to keep a checklist of the right questions to ask top of mind — which is exactly what this practical guide covers.
Why Vendor Evaluation Matters
In this scenario, you are not simply buying software; you’re making a long-term operational investment that you need to bring value to your organization. So let’s evaluate the decision seriously.
To ensure that your legal and procurement teams - and other departments for that matter - benefit the most from the new software, you’ll want to make sure vendors can answer challenging questions rather than simply point you to the latest buzzword on the website.
Choosing the wrong software not only risks the credibility of the purchasing department internally, but could also stall adoption and expose the organization to risk through lost funds, errors, or cybersecurity concerns. Choosing the right vendor is just as much about asking sharp questions as it is about features, and if a buying committee is involved, make sure every stakeholder hears the same answers.
Before you book any software demos, ensure that the representatives you speak to can meaningfully answer questions in the following arenas:
Aligning software with business goals
Understanding and clearly communicating your business goals will quickly show whether a vendor’s current features and roadmap align with them. It’s also worth weighing day-to-day usability for the teams who’ll actually use it.
If you’re expecting significant revenue growth from new business, will the tool scale with you — whether you’re an enterprise organization or a mid-sized team? Can it handle the automation of Non-disclosure agreements from the sales teams to a growing number of advanced prospects, reducing manual workload as organizations scale?
Mapping the features of a chosen piece of software against specific organizational (or departmental) goals and objectives also helps validate the use case and build the business case internally to acquire the tool in the first place, helping to prove the value it will bring before it brings it.
Conversely, this practice will also reveal gaps and show if tools aren’t fit for purpose: if you need to be able to search deeply through dozens of documents for specific terminology, but the tool you’re looking at only automates routing for signatures and just creates friction — a new bottleneck instead of solving one, that’s no good.
Understanding AI capabilities
Many organizations get swept up in AI hype before checking the fundamentals. True Artificial Intelligence is incredibly powerful if and only if it has been well-trained on high-quality data. If vendors have simply taken an old open-source dataset and applied some basic machine learning pattern recognition to it — without any real data science behind it — while marketing the tool as AI-driven, that’s not going to deliver results.
You’ll need to ask whether the AI and ML present within the software are capable of understanding semantics and intent, rather than simply recognizing a pattern. Further to this, you could ask whether the AI is proactive rather than reactive, operating on your data and responding to changes in real-time.
Questions About AI and Machine Learning
Now we need to take it to the next level and evaluate more detailed questions using a simple framework. Remember that you can document vendor answers, benchmark them against competitors, and weigh outside references like case studies or a Gartner report; it’s good to know your options.
How does the AI learn?
We’re looking for specific, detailed answers, real insight, not vague reassurances, for this and the rest of the questions. Vendors must be able to articulate, ideally straight from their data scientists, how their AI algorithms learn clearly and concisely:
- “Is the model already trained, or do we have to train it manually?” If you need to spend time uploading all your documents before you can deploy the tool, you need to know that, because it will affect time-to-value
- “Can the tool account for non-standard provisions?” Your organization is likely to feature some unique or inconsistent terminology; can an admin feed it to the AI to standardize how those clauses are handled?
- “Will our data be used to train your models?” This question has massive implications for privacy and competition reasons, and must be considered. Look for reassurance that your data never goes to the vendor and stays with you locally.
Naturally, there are more questions you could ask about how the AI learns than this, for instance, whether it uses RAG (retrieval-augmented generation) or a fine-tuned model, and you should feel comfortable asking as many as you like; any good vendor should be prepared to spend time answering your questions; you’re a prospective new client to them.
What contract review tasks are automated?
Ideally, you want a solution that offers end-to-end automation across the entire contract lifecycle, including approval workflows, so you can ask specific questions about the early and late stages of contract management such as:
- “Can the AI provide redlining and first-pass reviews? A “Yes” answer ensures that the algorithm can ingest drafts, compare them to your playbook, and automatically make changes or flag non-compliant areas for your attention within a single review cycle, keeping clear version control across every draft
- “Can the tool automate the management of post-signature obligations?” What we’re looking for here is to understand whether executed documents can be ingested, understood, and automatically update calendars based on key dates, etc
How accurate are the results?
Naturally, any hallucinated outputs will create more work to fix, when the whole point is optimization — fewer manual interventions overall. You’ll need to be 100% confident that your chosen tool performs well against key metrics like recall (finding specific clauses), and that its analytics hold up under scrutiny overall.
You could also ask how confidence is scored for predictive judgements; you don’t want a tool making guesses. Are there escalate-to-human points if a prediction falls below a confidence threshold?
Questions About Security and Compliance
By their very nature, contracts contain the most sensitive information related to the running of any business and therefore must be protected. Introducing new AI systems necessitates an internal audit and review of new security, compliance, and governance risks the tool may introduce.
Vendors should be used to fielding questions in this area, and will likely be upfront about addressing them, but it’s still worthwhile taking the time to gain reassurance and confidence:
Data privacy standards
- “Which data privacy, security, and regulatory certifications do you hold and which regulations do you comply with?”
- “Do you use public or private large language model APIs?”
- “Do you encrypt data and if so in what way?”
- “What does your data handling process look like, end to end?”
The hope here is that the vendor will have recognized certifications such as SOC 2, private LLM APIs, and data encryption both in transit and at rest. This is especially critical if you operate in regulated industries such as finance or healthcare.
User permissions and audit trails
These questions relate more specifically to actual workflows, but are no less important. There may be many business users of the new tool with different requirements for access and visibility. For example, you don’t want a junior HR admin to be able to see everyone’s employment contracts. User or role-based access controls should be a built - in feature of the new tool.
Further to this, you’ll want to ask whether the tool has immutable audit trails that can track who accessed a contract when, whether any changes changes were made, and whether this information can be reviewed in one place through a self-service dashboard, then easily exported and shared.
Questions About Integrations and Scalability
Finally, you want to ask questions around the futureproofing of not just this new tool, but your organization as a whole; every tool that you use should help unify data rather than exist as fragmented, isolated systems. Contracts touch every department and person across multiple teams within an organization, and you’ll need to account for that with tooling.
CRM and ERP compatibility
“Do you ship integration with popular Customer Relationship Management platforms like Salesforce out of the box, or do you need to build us that integration (and if so, how long will that take & cost?)?”
“Is the flow of data - or contracts - one-way or two-way?” If the tool makes a change to a contract, will that change be updated in the CRM, for example?
Ideally, and usually, modern platforms, especially those with AI and ML elements, should ship with existing major integrations, be easy to integrate with your existing stack, and be simple to customize to your needs. Data should flow in both directions, and the tool should be capable of scaling.
Future growth considerations
Large software purchases like this typically require annual subscriptions, and it may be beneficial to lock in a discount by going multi-year right off the bat. To do so confidently, you need to understand the pricing structure and ask how their pricing models scale in the future or with increased use as you grow.
Also, if you’re planning to launch in new markets or sectors, is the tool equipped to deal with additional languages, currencies, and legislative landscapes — including regulations like the EU AI Act?
Make sure you get the answer to these questions before signing anything.
Conclusion
Embracing Machine Learning-enabled Contract Management Software unlocks enormous potential for your organization, if you’re able to stick the landing. Do so by asking questions like those found above during your evaluation and listening intently to the answers… push straight past the marketing and jargon into serious discovery.
Already got answers to these burning questions? Schedule a demo today.