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78 clause is like using GPS to find the nearest coffee shop. Helpful, absolutely. But a workflow is the GPS plan- ning your entire road trip, including routing around traffic, booking the hotel, pre-ordering your coffee, and reminding you to stop for gas. A workflow might include drafting, validating against internal standards and authoritative external sources, routing for review, documenting decisions, and then preparing a final version for execution. I remember when one of our teams first moved from individual AI experimentation to a shared workflow for NDAs. The shift was not dramatic overnight, but within weeks, the conversations changed. People stopped ask- ing "What can this tool do?" and started asking "How do we make this the default?" The potential impact on ROI is significant. Individual AI use tends to deliver incremental gains, but shared workflows can achieve exponential impact: • Reduced variability drives predictability. • Standardization enables clearer measurement • Processes become scalable and repeatable. For legal professionals, this shift from tasks to workflows is especially critical. Workflow-driven AI simplifies complex work by automating repetitive steps and delivering consistent, quality outputs across teams. This allows professionals to redirect time toward high- er-value creative or strategic tasks. STANDARDIZING WORKFLOWS TO DRIVE ROI When organizations invest in standardized workflows, it unlocks new doors to a higher ROI. When teams rely on shared workflows, organizations start to see tangible change. Training time drops, quality becomes more predictable, risk exposure decreases, and metrics become comparable. For the first time, your quarterly review slides practically write themselves. Beyond these immediate benefits, standardized workflows can also serve as institutional knowledge systems. They capture senior expertise, reduce reliance on individual team members, and consolidate scattered knowledge into one clear and reliable system. Governance benefits naturally follow suit. Having a clear institutional hub makes standards, oversight, and auditability far easier, while security and compliance controls can be embedded directly into the workflow rather than layered on afterward like retrofitting seat- belts into a car already in motion. LEGAL AS A LEADING INDICATOR OF WORKFLOW MATURITY Legal offers a compelling case study for organizations of all kinds looking to achieve AI workflow maturity. Legal might not be the first industry people associate with agility, but that is exactly what makes it such a powerful proof point. As a high-stakes, heavily regulat- ed environment, legal work demands clear documenta- tion, repeatable processes, and strong governance. The key insight here is not that AI is performing these tasks, but that these tasks are embedded within struc- tured workflows that produce consistent, authoritative, and defensible outputs. Imagine a litigation team that once spent days assembling a motion to dismiss now completing it in hours, with built-in validation against internal standards and trusted external sources. That is the difference workflow-driven AI makes. Current examples in legal include: • Litigation workflows are designed to support disputes, motions practice, ediscovery, and case People stopped asking "What can this tool do?" and started asking "How do we make this the default?"

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