The technology headlines of 2025 were dominated by AI experimentation, but as we enter 2026, the reality is more sobering.
Despite 70% of Fortune 500 companies piloting AI tools like Microsoft 365 Copilot, actual enterprise-wide production remains stalled at a mere 5%. This is the AI Value Paradox: the costly gap where heavy investment fails to deliver measurable P&L impact.
Without objective, independent, and auditable data, leaders lack the AI intelligence to bridge the gap between “experimentation” and “impact.”
For many, Microsoft 365 Copilot has become a work “assistant”, a helpful add-on rather than a core productivity engine. The data suggests a widening divide: outside of specialized use cases like GitHub Copilot (where productivity gains for developers are clear), many users remain stuck in a “request-response” loop that is entirely assistant-led.
Instead of being integrated into an automated workflow, the AI waits for human commands. This creates a fundamental mismatch between the grand vision of transformation and the ground-level experience of a reactive sidekick.
Most organizations are currently “flying blind.” They rely on fragmented native vendor reporting that often misinterprets passive activity as meaningful usage, something we call “usage bloat.” Without objective, independent, and auditable data, leaders lack the insight to bridge the “change chasm” between strategic intent and users’ behavioral reality.
This is where Temporall and its unified platform, Tempo, deliver true AI Intelligence. We move beyond asking employees if AI is useful to seeing exactly how it is being used.
Tempo provides the objective data foundation required to move from experimentation to a measurable AI advantage:
Temporall’s approach to AI Behavioral Analytics has been honed since 2017. By unifying telemetry from co-existing productivity suites (Microsoft 365, Google Workspace), AI assistants (Copilot, Gemini, ChatGPT Enterprise), HR systems, and performance data, Tempo transforms fragmented signals into a single intelligence layer.
The result?
10x the decision intelligence at 10x the speed of traditional, qualitative-led methods. Smart leaders are no longer guessing about their AI investments; they are using real-time data to drive the deep organizational proficiency required for a true AI work transformation.
Andy Brown is a US-based technology executive and strategic advisor who co-founded and serves as CEO of Sand Hill East. His career includes roles such as Group CTO at UBS and Head of Strategy and Architecture at Merrill Lynch, with expertise in digital transformation, cloud security, and financial technology.
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