BigTime Software, Inc. Innovation, Technology & Agility

What is the unique story that you feel your company has with AI? If you were writing about it, what would the title of your blog be?
BigTime has truly embedded AI into how we think, build and deliver value, both internally and for our clients, and our unique story is one of rapidly paced evolution and relentless experimentation. There are many exciting aspects of BigTime’s AI journey coming to fruition at this moment, such as the BigTime AI Assistant, Build AI Report Builder, AI-powered task-based resourcing in Foresight, with much more on the horizon. But these enhancements wouldn’t exist without the culture we’ve built around AI.

We leverage tools from Google and OpenAI not only to enhance our daily workflows but also to better understand how our clients use them. Rather than waiting for perfect use cases to emerge, BigTime urges us to move fast and learn faster. We run internal AI hackathons, host monthly AI tool enablement sessions (ex: ChatGPT, NotebookLM, custom GPT creation) and established a cross-functional AI Champions employee group that convenes with other companies to share and collaborate on the AI space.

And if I were writing about BigTime’s unique story, the title of the blog would be “DNAi: BigTime’s AI Evolution in PSA.”

What was a monumental moment for your team when it comes to your work with AI?
A monumental moment for our team came when we rolled out the BigTime AI Assistant to general availability. We had been testing it internally for months, watching its knowledge retrieval and conversational capabilities steadily improve. But when it went live for clients, it felt like we had activated a veteran BigTime employee.

It was amazing to see the immediate impact of near-instant responses to common support questions, capable handling of alternative workflows and a visible reduction in tickets routed to our support team. Seeing questions I’d seen flood our support queue in the past now answered seamlessly was a powerful “wow, what’s next?” moment. Beyond support, the BigTime AI Assistant also transformed our onboarding experience, helping new clients and internal new hires alike get accurate answers without waiting. Our onboarding program is fantastic, but it’s hard to have a human available 24/7. Now BigTime AI Assistant is!

What challenges did your team overcome in AI adoption? 

One of the biggest challenges we faced in adopting AI was rethinking how to test it. How do you get a grip on something as fluid and subjective as testing something’s intelligence — especially technology? In traditional software, testing is straightforward with clear workflows, expected behaviors and boundaries to validate success. AI, and especially conversational AI, doesn’t operate like that. It faces an almost infinite range of inputs, scenarios and a user set with their own approaches and hesitations in adopting this technology.

People and qualitative data can be a bit messy. So when it comes to testing AI, there is no standard best practice automated test case. At BigTime, we tackled this by building a new, more involved kind of QA process. We developed limited, scenario-driven test cases that could approximate real-world usage and even used AI itself to help generate edge cases and test inputs. It continues to be an ongoing effort without a real one-and-done checklist, but these iterations and improvements are building a standard of confidence in validating our AI products.

Tell us about your tech stack. What tools do you use to gather and organize data? Which tools do you rely on most in your daily work?

I separate my “tech stack” from “tools,” though both are essential. My current tech stack includes Gong, Outreach, 6sense, ChatGPT Enterprise and LinkedIn Sales Navigator, while my go-to tools are LinkedIn, YouTube, Wayback Machine, Clutch.co and G2.

Of these two are daily must-haves, LinkedIn and Gong. On LinkedIn, I go beyond personnel research — I uncover insights like open roles, headcount trends, current tools, KPIs, responsibilities, trigger events (mergers and acquisitions, awards, etc.), service offerings and geography details. Gong, meanwhile, serves as my safety net. Even though I take thorough notes, Gong helps me pressure-test my understanding and capture the small but crucial details that may not make it into notes. Those details often make the difference in vendor selection, as success can hinge on how well a rep understands the business and articulates how their solution drives it forward.

How has data helped you close a deal? 

The CEO of this 200-plus employee outsourced financial services firm had a few interviews published on YouTube. The one I referenced during the late stages of our evaluation had seven views. Not only did I show an unmatched level of “I do my homework,” but I also made light of the situation because I represented 14 percent of his video’s viewership. The emotional aspect of this had an immediate and obvious impact.

How does sales and customer data enhance your company’s sales org? What data do you find most important in the sales process?

I approach this from the perspective of new sales, whether in an evaluation process or business development effort and see it primarily as an exercise in preparation. The better prepared you are, the greater your impact and the more you stand out from the crowd. For example, being able to name-drop a prospect’s peers or perceived stakeholders demonstrates credibility and relevance. When engaging with private equity-backed companies, I focus on tying the solution to an eventual exit event, showing direct alignment with their long-term goals. And if there’s precedent for mergers and acquisitions, I reference a proven playbook that not only highlights how the solution can be leveraged but also how it can streamline onboarding for future acquisitions.