Lattice Targets AI's ROI Problem, Shifting Focus From Usage to True Value

SAN FRANCISCO, CA – June 10, 2026 – As businesses pour billions into artificial intelligence, a critical question echoes through boardrooms: Is it actually working? Today, HR technology firm Lattice offered a bold answer, declaring that the AI revolution is not about replacing people, but empowering them—and it has built the tools to prove it.

At its Lattiverse conference, CEO Sarah Franklin introduced a suite of solutions aimed at tackling what she calls a "people and process transformation." The company unveiled AI Leverage Insights, a workforce intelligence tool designed to measure the qualitative impact of AI on employee performance, and Lattice MCP, an infrastructure play that securely pipes trusted performance data into the AI tools managers use daily. The announcements position Lattice at the center of a growing debate, arguing that the key to unlocking a purported $10 trillion in productivity isn't just adopting AI, but understanding its real value.

"The companies that will win aren't the ones cutting people the fastest," Franklin stated in her keynote address. "They're the ones figuring out how people and AI succeed together." This vision directly challenges the simple narrative of AI as a cost-cutting automaton, reframing it as a partner in human growth.

The Quest for Quality: Moving Beyond AI Usage Metrics

The most significant challenge for executives championing AI has been demonstrating tangible return on investment. While many platforms can track AI usage—counting API calls or "token" consumption—these metrics reveal little about the quality or business impact of that usage. Lattice's new AI Leverage Insights tool aims to solve this very problem.

"Token counts are a quantity signal, not a quality signal," Franklin explained. "For the first time, people leaders can answer not just 'how much is AI being used?' but 'are we getting value, is it being used wisely and solving business problems?'"

The system works by connecting AI usage data with performance outcomes, manager feedback, and other output signals already housed within the Lattice platform. The goal is to separate employees generating high volume with little substance from those leveraging AI to produce high-quality, impactful work. This provides leadership with a crucial "quality signal" to identify what's working and scale those effective strategies across the organization.

This move directly addresses a pressing need in an industry where virtually every HR technology vendor, from Workday to SAP SuccessFactors, has integrated AI features. While competitors use AI to summarize performance data or suggest development plans, Lattice claims to be the first to directly link an employee's AI usage patterns to their measured performance, a distinction that could give it a significant edge.

A New Standard for AI and People Data

Underpinning this new layer of intelligence is Lattice MCP, the company's implementation of the open-source Model Context Protocol. First introduced by AI safety and research company Anthropic in late 2024, MCP is rapidly becoming an industry standard, described by some analysts as a "USB-C for AI." It provides a universal, secure language for AI models to interact with external systems and their data.

By adopting MCP, Lattice allows managers to access an employee's complete performance history—including past reviews, 1:1 meeting notes, feedback, and goal progress—as live context inside the AI tools they already use, such as ChatGPT, Claude, and Slack. A manager preparing for a performance review no longer needs to hunt through disparate systems to build a complete picture; the context is served up directly within their workflow.

"Performance reviews have always been one of the most important and most dreaded processes in any organization," said Sophie Hurcombe, Chief People and Operations Officer at Lattice. "Lattice MCP changes the game. When managers have real context at their fingertips, reviews stop feeling like a compliance exercise and start feeling like the meaningful conversations they were always meant to be."

Crucially, MCP is designed with security and permission controls at its core. It creates a structured channel that respects existing data access rules, ensuring AI models only see the information they are authorized to, a non-negotiable requirement when dealing with sensitive employee data.

'People + AI': A New Philosophy for Performance

Together, these innovations anchor Lattice's broader vision of "People + AI is the new way to work." The company is betting that the most successful organizations will be those that use AI not to replace their workforce, but to augment it. This philosophy stands as a counterargument to the narrative of mass displacement, instead focusing on growth, coaching, and making work more meaningful.

This approach is echoed across the competitive landscape. Oracle HCM uses generative AI to personalize employee journeys, while Cornerstone OnDemand's "Workforce AI" focuses on identifying and closing skills gaps. The common thread is a shift from periodic, backward-looking reviews to continuous, forward-looking development. AI agents that provide personalized coaching, like the one Lattice announced for 1:1 meetings, are becoming table stakes.

However, Lattice's insistence on measuring the qualitative impact of AI itself sets its strategy apart. By providing a feedback loop that shows how AI is contributing to business outcomes, the company is attempting to create a virtuous cycle where both people and the AI tools they use become progressively more effective.

Navigating the Ethical Tightrope of Workforce Intelligence

Of course, the prospect of tracking employee AI usage raises immediate ethical questions and fears of a surveillance state. The line between workforce intelligence and invasive monitoring is a fine one, and building employee trust is paramount. Industry experts caution that implementing such systems requires robust ethical guardrails, including strong data anonymization, transparent policies on how insights will be used, and a commitment to fairness.

Lattice's reliance on the secure MCP framework is a step in the right direction, but the cultural implementation will be just as critical as the technical one. Organizations must frame these tools as instruments for development and support, not judgment. Research has shown that while many employees are wary of AI, a significant number also believe it could provide fairer, less biased feedback than a human manager, highlighting a deep-seated need for improvement in performance management processes.

As Lattice rolls out early access to these tools, it enters a market hungry for solutions but cautious about the implications. The success of this new wave of AI-powered HR technology will ultimately hinge not just on its technical capabilities, but on the trust it builds with the very people it is designed to empower.