Big Time’s CPO, Mark Johnson, discusses the company’s AI-driven evolution, emphasizing productivity gains, adaptive product development, and the role of AI in enhancing workflows while maintaining human oversight and strategic decision-making.
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Mark Johnson: I’ve been at BigTime for almost three years now, leading our product and UX teams. BigTime is a professional automation platform that helps customers make smarter decisions and drive profitability. My career has largely revolved around this theme, improving productivity and retention across industries. Before BigTime, I worked at Deluxe in payments and SaaS, particularly in payroll, and also spent time at Home Depot leading product teams for field services. My focus has always been on making tools that help people be more efficient, whether they’re in the field or managing projects. I also have experience in consulting, which helps me relate to the personas we serve at BigTime.
Mark Johnson: Like many SaaS companies, we’ve been on a journey with AI, and that journey is accelerating rapidly. Initially, we introduced a GenAI-powered assistant to help users navigate our platform more efficiently. But we quickly realized our customers need more than just guidance, they need deeper insights from their data. That led us to develop co-pilots, which serve as AI-driven teammates that assist with specific tasks across an organisation.
Looking ahead, we see AI evolving from assistants to co-pilots to autonomous agents that take the lead on workflows. The ultimate goal is to reduce the manual workload, allowing humans to focus on reviewing, approving, and making strategic decisions. We’re actively building out all three AI layers simultaneously, enhancing the assistant experience while pushing forward with co-pilots and agents to maximise automation and efficiency.
Mark Johnson: This is one of our biggest challenges, but also one of the most exciting opportunities. Traditional roadmap planning often took months, involving data aggregation, customer input, and financial planning. With AI, we can complete that process in days rather than weeks.
We’re already seeing productivity gains internally. For example, one of our engineers built a new expense extraction process in just six hours, which previously would have taken months. This changes how we prioritise projects. What used to take multiple quarters can now be done in weeks. We’re rethinking sprint planning, product roadmaps, and engineering workflows to take full advantage of AI’s acceleration.
Mark Johnson: AI adoption cannot be limited to product and engineering, it has to be embedded in the entire company culture. That’s why we’ve launched an internal program called “Big Time AI Champions.” This group consists of employees from various departments who experiment with AI tools, explore different use cases, and share best practices. Right now, about 40% of our company actively uses AI, and our goal is to keep increasing that adoption.
AI isn’t just about efficiency, it’s about making better decisions. For instance, our sales team is using AI to generate real-time competitive analysis and battle cards based on deal trends. The key is helping people become comfortable with AI and guiding them on how to use it effectively.
Mark Johnson: Education and transparency are critical. Many of our customers aren’t ready to fully embrace AI yet, so we’re focused on building trust. For example, we recently launched an AI-powered resourcing tool that recommends the best candidates for a project, but it also explains the reasoning behind its suggestions. This transparency helps customers understand and trust the AI, increasing adoption over time.
We’re also balancing innovation with accessibility, moving too fast could alienate some customers. Even though AI enables us to build and deploy faster, we still apply product management fundamentals: research, user experience design, and ongoing customer engagement. The goal is to help customers learn and gradually integrate AI into their workflows at a pace that works for them.
Mark Johnson: It’s a bold statement, and I think there’s some truth to it, but also a bit of a media play. The idea of moving away from large, monolithic enterprise software is appealing, especially for a company with Klarna’s scale and engineering resources. But for most businesses, the reality is more nuanced.
The key question is: What should you build versus buy? Companies like Salesforce and Workday exist because of their domain expertise and vast data capabilities. While AI can speed up software development, it doesn’t replace the deep industry knowledge these platforms provide. What we’re seeing is a shift toward a hybrid model, companies are leveraging foundational enterprise software while integrating AI-powered best-of-breed tools to enhance flexibility and automation.
Interestingly, research from BCG suggests that AI is actually increasing the number of tools in tech stacks, not reducing them. Companies are adding AI-driven solutions that complement existing systems rather than replacing them outright. The shift is more about making these systems more modular and adaptable, rather than eliminating them completely.
Mark Johnson: AI is fundamentally changing the way work gets done. We’re moving from static systems of record to dynamic systems of intelligence, where AI agents can adapt workflows in real time. This means businesses can operate with more agility and efficiency, reducing time spent on mundane tasks like expense reports and time tracking.
For us at BigTime, the goal is to free up professionals so they can spend more time on high-value activities: serving clients, delivering great projects, and making strategic decisions. AI should handle the grunt work while humans focus on creativity, problem-solving, and relationship-building. That’s the future we’re building toward.
