Experts from Rockhop team up with Kevin Chaplin from HQforAI to demonstrate how GenAI can automate common tasks within the contract review process, saving time and ensuring thorough and accurate reviews.
Fantastic, should we get started? We're three minutes in; I think it's a good time to get rolling. Again, thank you everyone for joining our webinar. This is a joint webinar between Rockhop and HQ for AI. I'd like to start with an agenda and then we'll go into introductions.
On the menu for today: we'll be jumping into why Gen AI and automation, and how those things can work together. We'll then get into contracts and understanding the complexities of today's contracts, and how AI can help us accelerate that. Then we'll jump into a demo to show you how we've thought of accelerating the contract process with AI, and use that as an example for other contracts that can be accelerated within your business. We'll close with a question and answer session, where you can ask us questions about the webinar itself or anything else related to AI.
Our presenters today are Dave Grieve (myself, with Rockhop), Michael Buckman (also from Rockhop, who will be leading our demo), and Kevin Chaplan (from HQ for AI, who will go into the depths of how AI and automation can work together). They will each introduce themselves in their sections as we go through the slides and demo. To start off, I'll pass it over to Kevin to talk about why Gen AI and automation.
Thanks, Dave, and great to see everyone here today. We're going to talk through Gen AI and automation, and then how they connect together.
Quick intro of myself: as Dave mentioned, my name is Kevin Chaplan. I'm the co-founder of Headquarters for AI. We focus on AI literacy—helping to make sure every single team member understands and uses this amazing new technology. We also deal with AI strategy—helping to make sure that as this continues to grow and deploy at enterprise scale, there's a right center of excellence and policies in place to make sure we're using it safely and correctly. And finally, AI engineering—as you scale from self-service Gen AI all the way up into the enterprise level, we can continue to help support that. Excited to be here with everyone.
When we think about AI, there are three key mantras: it will not take your job, but someone using AI will. It's a technology, not a magic wand. And the people problem is bigger than the tech problem. People worry about hallucinations, governance, and compliance. But really, the bigger issue is adoption and making sure people know how to use it responsibly.
Traditional AI—predictive models, supervised learning—takes a lot of time, effort, data scientists, data engineering, and labeling. It’s very different from generative AI. With generative AI, it’s conversational, flexible, and available to more people.
Self-service is where people prompt chatbots like ChatGPT or Copilot. Enterprise AI is when organizations scale this into workflows, embed it in systems, and set up governance, policies, and security. That’s the maturity curve we’re moving along.
In contracting, for example, an individual could prompt: “Act as a lawyer. Review this contract. Here are my standard terms.” That’s useful, but limited. At enterprise level, we want repeatability, automation, consistency, and auditable processes. That’s what we’ll show later in the demo.
Excellent, thank you Kevin. Great slides and conversation about Gen AI and automation.
Now let’s jump into understanding the complexities of the contract process, using an example of a common MSA. Rockhop works with clients on Power Platform and AI. We see contracts as a universal pain point: they take too long, they involve multiple stakeholders, and they delay revenue.
The benefits of AI and automation in contracting are clear: huge time savings, faster speed to agreement, fewer bottlenecks, more deals closed, and ultimately increased revenue. Beyond MSAs, think about leases, loans, vendor agreements—any repeatable contract process can be accelerated with AI.
So I'll stop there—let’s get to the demo. I'll pass it to Michael Buckman to introduce himself and walk through an MSA use case.
Michael: Thanks, Dave. Let's get started. I’ll walk through the app I built—a Power App for contract review. First, I'll show you manual prompting through Copilot. Then I’ll show how we scale it into an enterprise-ready app.
In the app, you upload an MSA draft. AI analyzes it, highlights risky clauses, compares them to standard terms, and suggests edits. With Power Automate, this runs in the background, and the results are stored in Dataverse. You get structured outputs: summaries, flagged issues, suggested revisions. You can accept, reject, or edit them. Finally, it generates a clean revised contract or a redline version to send back.
This combines the flexibility of generative AI with the structure and governance enterprises need.
Great, that leads us into Q&A. Are there any questions for Kevin about the process and how we demystify and leverage AI to our advantage? Or for Michael, about the demo and how we built the contract review process?
Audience questions:
We addressed each of those, emphasizing that security is always top of mind, human oversight is critical, and governance structures need to scale with adoption.
