Apertera

🎙️ Speaker Spotlight: Mike Haven

How is Meta measuring the value of AI?

As Global Head of Legal Operations at Meta, Mike Haven brings firsthand experience evaluating how AI translates into measurable business impact.

He uses a four-bucket model to evaluate AI investments, looking at work deflection, outside counsel avoidance, operating-cost reduction and new capabilities enabled by AI.

On October 28, Mike joins our panel for From Investment to Impact: Measuring the ROI of AI to explore how organizations can identify the KPIs that matter, measure productivity and efficiency gains, and demonstrate the value of AI investments to leadership.

📅 October 28 | 1:00 PM ET
🎓 1 hour of Substantive Content
🔗 Register: https://hubs.li/Q04yDd2l0

⚖️ You don't have to redesign your entire multilingual legal workflow at once.

Start with the part that needs the most attention.

Our Multilingual Legal Operations Maturity Assessment helps you score five areas of your operation, from intake and capacity to terminology, technology and professional oversight.

Then look at your lowest-scoring area. Is it unclear ownership? Too much reliance on bilingual colleagues? Approved terminology that's hard to find or reuse?

The assessment offers practical next steps for each area, so you can move from identifying friction to deciding what to improve first.

🔗 Assess your multilingual legal operation: https://hubs.li/Q04yzqjp0

⚖️ A faster first draft won't help much if the rest of the workflow still runs by hand.

Information gets re-entered. Work moves between systems and reviewers. Someone has to find the right terminology, coordinate the next step and check what changed.

Each task seems small. Together, they take time away from the legal work that needs professional judgment.

For multilingual legal teams, efficiency means deciding what can be automated, what should be standardized and where closer review is needed. Get that balance right, and the team gains capacity while maintaining the quality high-stakes work requires.

🔗 Read Building More Efficient Legal Workflows Without Sacrificing Quality: https://hubs.li/Q04yqQGc0

📊 How do you know if your AI investments are actually delivering value?

As AI adoption accelerates, organizations are moving beyond what the technology can do to a harder question: how do you measure its impact?

Join leaders with firsthand experience implementing, evaluating and bringing AI technology to market at Meta, American Express and Thomson Reuters for ‘From Investment to Impact: Measuring the ROI of AI’.

The panel will explore how organizations can identify the KPIs that matter, measure productivity and efficiency gains, and connect AI investments to measurable business impact.

📅 October 28 | 1:00 PM ET
🎓 1 hour of Substantive Content

🔗 Register here: https://hubs.li/Q04ygyS10

⚖️ Legal teams are supporting more of the business with increasingly lean resources.

New 2026 benchmarking data shows a median of 367 employees per in-house lawyer.

When capacity is already stretched, multilingual work that relies on scattered requests, manual coordination and internal employees to keep things moving can add pressure in places that are easy to overlook.

The opportunity is to make the workflow itself more scalable: structured intake, consistent terminology, clear review paths and technology that reduces repetitive work.

Our latest article looks at how legal teams can move from ad hoc translation requests to a more repeatable approach.

🔗 Read From Ad Hoc Translation Requests to Scalable Legal Operations: https://hubs.li/Q04yg2L30

Source: 2026 ACC Law Department Management Benchmarking Report, Association of Corporate Counsel and Major, Lindsey & Africa.

🤖 As more organizations build their own AI, the bigger question may be: what does it actually take to make it work?

That question stood out at ALL IN 2026 in Montréal last week, where one thing was clear: organizations aren't just experimenting with AI anymore. They're increasingly developing solutions for their own industries, workflows and teams.

But building the technology is only part of the equation.

AI needs context. It needs training. It needs people who understand the work it's being asked to do. And turning a promising tool into something people actually use requires implementation, change management and continuous learning.

We've seen that firsthand since beginning our own AI investment in 2018. The technology becomes more valuable when it learns from an organization's knowledge, preferences and feedback over time, while professionals provide the expertise and oversight that technology alone can't.

That's what makes this next phase of enterprise AI so interesting. The conversation is moving beyond who can build AI to who can make it work in the real world.

Thanks to the ALL IN team for bringing together so many perspectives on where AI goes from here.

⚖️ Where is your multilingual legal workflow actually holding you back?

It may be intake. Capacity. Terminology. Technology and AI. Or the way review and oversight are handled.

Our Multilingual Legal Operations Maturity Assessment helps legal teams evaluate all five, identify where their current approach is creating friction, and determine what to prioritize next.

Because when demand increases, knowing where your workflow needs attention is the first step toward making it more scalable.

🔗 Assess your multilingual legal operation: https://hubs.li/Q04y6QT10