Governance

GenAI governance requires a different approach from traditional IT governance. With employees choosing tools and discovering new use cases, organizations must balance innovation with risk management. This blog explores 6 strategies to optimize GenAI governance and maximize ROI, from assigning the right licenses and mandating user training to calibrating data guardrails, managing emerging apps, and sharing successful use cases. Discover how monitoring real-world GenAI usage can help reduce data exposure, optimize costs, increase effectiveness, and identify opportunities to improve productivity.

In this issue, we’ll take a look at an Inc. magazine article on why GenAI usage is surging while effective use remains elusive. We’ll then take the conversation further with our on-demand webinar, Driving GenAI Effectiveness with Productivity-First Governance, featuring the latest enterprise usage benchmarks. Plus, we'll show how PetSafe Brand built a fact-based approach to GenAI governance in just six weeks. Let’s dive in. 

New guidance from regulators in UK and Ireland puts the burden of verification on the practitioner. Here's what it means for firms and legal departments — and how to meet the regulations without banning the tools your fee-earners are already using.

In this issue, we’ll sum up our research on GenAI effectiveness, based on actual usage from thousands of end users. We’ll also show how the NROC Security solution can deliver an assessment of your organization’s GenAI effectiveness, giving visibility to new apps like Claude Cowork. We’ll share how we helped the Commission for Regulation of Utilities (CRU) ensure NIS2 compliance. Let’s start with AI FOMO and how it boosts investments but expands the GenAI governance gap.

Learn the 8 capabilities every CIO should evaluate to avoid engine overrev in enterprise AI adoption

A CIO's Guide to enabling secure enterprise AI adoption

The full research report breaks down all of the 2Q26 benchmarks (in comparison to 1Q 2026) — adoption and weekly usage, the app landscape (including how Microsoft Copilot, ChatGPT, and Claude are actually being used), the prompting-skill level, data-exposure trends, and the GenAI Effectiveness Index methodology — along with the productivity-first governance framework for closing the GenAI productivity gap.

Increased employee productivity is the promise of AI, but measuring it remains elusive. This article explains why effectiveness is a better metric than productivity and how organizations can turn AI usage data into improving GenAI outcomes.

Although GenAI adoption is growing, productivity impact remains elusive. While 14% of employees use GenAI on a weekly basis, only 0.5% currently demonstrate the skill and frequency of effective use. The data underscores the importance of measuring GenAI usage, skill development, and business outcomes.