The Larridin Story: Measuring AI Workforce Productivity

Published: April 2, 2025

After 25+ years building enterprise tech, we realized the biggest gap in the AI revolution: nobody can measure if it's actually working.

Key Takeaway

Larridin enables organizations to measure and optimize AI workforce productivity—the new equation of people working alongside AI tools and generative AI systems. We built a platform to fill the measurement void after hearing from thousands of business leaders about outdated productivity measurement tools. Our solution measures productivity gains from AI-powered workflows, automation of routine tasks, and AI-driven decision-making through real-time metrics and datasets that track the impact of AI technologies. The insights help prioritize investment decisions across people, processes, and AI adoption.

Key Terms

AI Workforce Productivity: Measuring and optimizing performance of humans working alongside artificial intelligence, AI tools, generative AI systems, and machine learning to achieve productivity gains through automation and AI assistance.
Productivity Gains: Measurable improvements in output and efficiency from AI adoption, including automation of routine tasks, enhanced decision-making, and productivity growth through AI-powered workflows.
AI Adoption: Process of integrating artificial intelligence and generative AI tools like ChatGPT, GPT-4, and Copilot into workflows to boost productivity and optimize specific tasks for early adopters.
Measurement Void: Gap in metrics and baseline datasets for tracking the impact of AI on workforce productivity, requiring new technologies to measure AI-driven advancements in real-time.

The Vision: Human-AI Collaboration

The future of work is collaborative—humans and artificial intelligence working in tandem to boost productivity through AI-powered workflows. That's why we launched Larridin. Our platform enables organizations to continuously measure and optimize AI workforce productivity—this new workforce equation of people working alongside their AI counterparts using generative AI tools, machine learning, and automation.

Many tech luminaries understand the importance of this vision for measuring the impact of AI on productivity gains, which enabled us to raise $17M in seed funding led by Andreessen Horowitz with contributions from Gradient, Bloomberg, Haystack, Homebrew, and others.

The Problem: The Measurement Void

Over the last year, we talked with thousands of our former customers and partners—CEOs, CFOs, Heads of HR, and other business leaders—about AI adoption and measuring productivity growth. Again and again we heard the same thing: the current tools to measure and understand corporate productivity are severely outdated and not helpful in a world of generative artificial intelligence.

Every company now has humans working alongside AI systems and AI tools—using ChatGPT, GPT-4, Copilot, and other generative AI technologies for specific tasks. In some cases, machines and robots handle routine tasks through automation. Early adopters of AI have seen productivity gains, but lack metrics to establish a baseline or measure the real impact of AI assistance on workflows and decision-making.

The adoption of AI is accelerating across use cases—from healthcare to the labor market—yet business leaders don’t have datasets and algorithms to optimize their AI-driven initiatives. This measurement void creates uncertainty: Are AI technologies delivering productivity growth? Which AI tools actually boost productivity? How do we measure AI workforce productivity improvements beyond anecdotal evidence?

The Solution: Real-Time AI Workforce Productivity Measurement

Larridin fills the measurement void through real-time metrics that track AI use across workflows. We help organizations prioritize investment decisions across people, processes, and deployment of AI by measuring:

Productivity Gains: Quantifying improvements from AI adoption, automation of routine tasks, and AI-powered decision-making using baseline datasets and algorithms.
AI Adoption Impact: Understanding which generative AI tools and AI systems deliver measurable advancements in specific tasks and use cases.
Workforce Optimization: Identifying where AI assistance enables teams to function more effectively, revealing opportunities for upskilling and addressing concerns about job displacement through data rather than assumptions.
Strategic Initiatives: Providing takeaways for business leaders on where to invest in new technologies, which AI-driven workflows boost productivity, and how to optimize the balance between human expertise and artificial intelligence.

What economists and macroeconomics experts can tell us about productivity growth from new technologies provides context, but organizations need their own metrics—not aggregate labor market statistics—to understand the impact of AI on their specific function and workflows. A percentage point improvement in productivity growth at the macroeconomic level doesn't help business leaders make real-time decisions about AI adoption in their organizations.

The Team: 25+ Years of Enterprise Experience

After 25+ years building enterprise technology companies with my co-founder Jim Larrison, we're ready to equip organizations for the AI-powered future. Along with our new partner, Ameya Kanitkar and our amazing growing team, we're bringing together deep expertise in artificial intelligence, machine learning, generative AI, and enterprise software to solve the AI workforce productivity measurement challenge.

We're not just building another AI tool. We're creating the measurement infrastructure that enables organizations to understand whether their AI adoption is delivering productivity gains—whether generative artificial intelligence and AI-driven automation are actually optimizing workflows and boosting productivity, or just adding complexity.

Let's Build the Future Together

The future of work is human-AI collaboration. But unlike previous technological advancements in the labor market, we have the opportunity to measure the impact of AI technologies from the beginning to establish baselines, track productivity gains, optimize AI use across specific tasks and use cases, and make data-driven decisions about AI adoption.

We're working with early adopters across industries—from healthcare to financial services—helping them measure and optimize AI workforce productivity. The respondents to our research consistently emphasize the same need: real-time metrics for understanding how artificial intelligence, generative AI tools, and machine learning are changing workflows, automating routine tasks, enabling better decision-making, and delivering genuine productivity growth.

Let's build the future of work, together with measurement, not guesswork. With datasets and algorithms that reveal the real impact of AI. With platforms that help organizations optimize the balance between human creativity and AI assistance. With tools that turn the promise of productivity gains from AI adoption into measurable reality.

Reach out if you're interested in learning more about how Larridin can help your organization measure and optimize AI workforce productivity!