How Armanino Builds and Scales Agents with DataSnipper
Q: What are the main challenges for people in audit and advisory today, and how does DataSnipper help?
A: People are stretched by everything on their plate, and some work is perhaps not getting the attention it requires. DataSnipper has given our team back some capacity. It takes over the ticking, tying, and documentation that need little thinking, so people spend more time on the knowledge work behind them. That time goes to more value added activities like analysis and judgment calls, which matter more as clients adopt AI amid economic and political uncertainty.
Q: What was your first impression of DataSnipper?
A: We were impressed and skeptical at the same time. Plenty of tools and fads have promised a lot and delivered little. Then we saw that possibility come to life in DataSnipper.
Q: How would you describe your partnership with DataSnipper?
A: They have been terrific partners, supporting us in so many different ways. They brainstorm with us whenever we have questions. The team is very responsive, and it helped us identify and fine-tune our use cases so we get the most out of the product.
Q: Which use cases are you working on?
A: We have identified around 10 agents in external audit, plus a handful in risk advisory. We're currently working on an agent that'll automate payroll testing. Our team also leverages DataSnipper’s basic functionality all the time in their daily work, like Document Matching for invoice testing. We're working on incorporating DataSnipper into our testing of the P2P process as well.
Q: What role does AI play in risk advisory?
A: AI is one of the tools that lets us bring solutions to clients faster, often enabling a more thorough and higher quality result. It has become an important one. Doing more in less time will let us provide a higher level of assurance and move away from small-sample testing. AI can help us look at more and cover more, which gives our clients a higher level of service.
Q: How do you ensure you use AI in a responsible way?
A: Every firm is still working out governance and quality assurance for AI. For us, it starts with people recognizing they are accountable for the results. We build confidence through controls, such as testing a model's output against expectations and reviewing results for reasonableness.
Traceability sets DataSnipper apart from other AI platforms. When a reviewer checks a result, they click into the cell and see the source document. Other tools can act like a black box, where you cannot see where a finding came from. Making sure a human is reviewing every Snip is really helpful.
Q: What stood out to you about Alwin, our new agentic platform?
A: We are very excited. Alwin answers some questions about how to scale and how to bring these solutions more broadly to our projects. It provides an opportunity to accelerate what we are trying to do with automation and AI. Running on the cloud takes the computing power off your local machine, which will help promote adoption.
Q: What do you want to achieve with DataSnipper in the future?
A: Our focus is on leveraging Alwin and expanding how it’s used in our work. DataSnipper will support the standardization of our workflows, as these agents can be shared firm-wide. We want a method, a strategy, and a plan for rolling them out. That way we use the tools in a methodical, intentional way that has the biggest impact on the firm and our clients.
Q: How was your experience at Connect?
A: Hearing what other people are doing, including their challenges as well as their successes, makes you feel inspired and less alone. We are all facing similar challenges in a changing world, and we are taking home ideas we had not thought of before. The perspectives come from professionals across industries, not only auditors, and we are all figuring this out together.
Armanino's experience shows what a partnership built on a plan can look like: a pipeline of agents across external audit and risk advisory, and a rollout the firm shapes with a clear method before it scales. DataSnipper looks forward to helping Armanino turn that pipeline into agents that teams across the firm can share, and to seeing more of their time go to judgment work.