So, what can your GC learn from their wins—and even more importantly, their battle scars?

Take Saudi Aramco, the energy behemoth. When oil prices are high, Aramco doesn’t just rival—it outpaces the world’s top tech giants in market value.

Petrochemical companies aren’t usually known for chasing the next shiny thing in tech. As long as crude extraction stays efficient—at around nine dollars per barrel—the model works. So why would Aramco invest in AI for its legal department?

Why would Aramco invest in AI for its legal function, even with strong cash flow? Because rising regulatory complexity and geopolitical uncertainty now hit the bottom line hard. AI helps legal teams react faster to regulatory shifts, cut manual review costs, and mine insights from vast operational data—from upstream drilling sites to downstream chemical tracking. For a CFO, this means fewer surprises, tighter compliance control, and better risk forecasting.

By early 2025, Aramco had made headlines with its strategic push into AI, not just for production efficiency but to overhaul legal and compliance operations too.

While legal-specific cost savings remain confidential, analysts tracking their AI adoption point to significant efficiency gains. Automated document review and compliance monitoring have pushed cost optimisation results to 20–30% in Legal and Compliance functions.

Turning to Standard Bank—South Africa’s financial powerhouse, a financial services giant operating across a diverse and often challenging regulatory landscape spanning twenty-six countries.

Their AI adoption strategy and successes, particularly in customer service and fraud detection, are worth reading-up on. Less publicised, has been their exploration of AI within their legal and compliance departments.

For a bank, tasks like KYC/AML checks, regulatory reporting, and initial contract screening eat up huge operational budgets. Standard Bank used AI to automate the heavy lifting in those high-volume, rule-based areas.

The result? They’ve reallocated legal teams away from routine grunt work toward strategic advisory. Reports show 20–30% efficiency gains in those automated areas—plus improvements in speed and accuracy.

The Nitty-Gritty: It’s Not Just Plug-and-Play

It’s wishful thinking to expect an off-the-shelf legal tech platform to deliver the kind of transformational results seen at Aramco or Standard Bank. Those outcomes weren’t the result of plug-and-play tools—they came from strategic alignment, cross-functional design, and deep operational integration. For too long, AI in legal felt more like a pipe-dream. That’s finally starting to change—but only for those willing to build, not just buy.

The journey Aramco and Standard Bank underscored critical lessons that all companies should bear in mind when plotting their AI adoption strategy:

1. Data, Data & Data: The most sophisticated AI is useless without clean, well-structured, and relevant data. Both organisations invested heavily in data governance and infrastructure before attempting to scale complex AI in sensitive areas like legal. Why? AI is so powerful that it can easily spin up and reveal internal confidential documents to employees who had no idea they could see that data. Therefore, a GC pushing for AI without a CIO who’s mastered the company’s data is fighting a losing battle.

2. Fail to Plan. Plan to Fail: Neither company started with a vague mandate to “use AI in legal.” They identified specific, high-volume, rule-amenable pain points: first-pass reviews of contracts, analysing new regulatory instruments etc. The 25%+ savings aren’t department-wide overnight; they’re achieved by surgically targeting the right problems. And when lawyers put their minds together to identify those problems, it creates a shift change in mindset from “This is how we’ve always done it” to “Lets find a better way”.

3. Change Management is the Silent Killer (or Enabler): Introducing AI isn’t just a tech upgrade; it’s a cultural shift. Lawyers, by training, are risk-averse. Reports from similar large-scale AI adoptions (see McKinsey’s global AI surveys) consistently highlight that overcoming internal resistance and upskilling the workforce are as crucial as the technology itself. The successful GCs aren’t just AI champions; they’re master change agents. It sends strong signals to the rest of the enterprise when Legal master the art of prompting — colleagues outside Legal see this as a mind-shift change “Well if Legal are using AI, then so can I!”.

4. The “Black Box” Problem is Real, Especially for GCs: For legal, explainability is paramount. If an AI flags a contractual risk or suggests a compliance action, lawyers need to understand why. Both Aramco and Standard Bank, operating in highly regulated sectors, prioritised explainable AI or glass box AI solutions offering transparency and auditability, rather than opaque algorithms, a concern echoed by Stanford’s HAI research on ethical AI

The Takeaway for Your C-Suite:

Yes, Generative AI can deliver substantial cost savings in your legal department. But achieving that 25%+ benchmark isn’t about finding a silver-bullet AI tool. It’s about strategic planning, meticulous data preparation, targeted use case selection, and a relentless focus on change management. The GCs who are delivering these results aren’t just buying AI; they’re re-architecting their function from the ground up.

At SAIL, we work with GCs and the C-suite moving beyond AI hype and unlocking real, quantifiable savings in your organisation. SAIL’s AI implementation roadmap identifies high-ROI use cases, and how to navigate the change management maze, and deliver measurable results.

Contact us at khaled@sail.legal or book a free consultation.