Jens Erik Gould serves as the Founder & CEO of Amalga Group, an innovative Texas-based company specializing in nearshore outsourcing.
AI has made remarkable strides in legal services, from accelerating document review to organizing large volumes of data. But as its adoption spreads, so does a critical question: What can’t AI do?
My company specializes in nearshoring talent for law firms, and that topic comes up often in my conversations with legal operations leaders. Many legal services providers have been racing to develop proprietary AI-based software, and I’ve observed them roll out highly effective automation solutions in areas such as contract drafting, legal research, document review and records indexing. This has helped law firms accelerate their processes, save time and lower costs. Just take a look at the vendor displays on the floor of any major legal ops conference, and the impact these tools are having will become clear; it seems like nearly all service providers are out marketing their new AI tools in full force.
But there are many legal ops functions, from transcription to records to e-discovery, where engineering teams have not yet been able to develop a truly end-to-end AI solution that handles all stages of the process. As a result, in some of these areas, vendors don’t yet offer fully unsupervised, litigation-ready AI that runs from ingestion to production without human quality control. Additionally, in my work helping U.S. companies build and augment operational teams, I’ve seen how AI can improve speed and efficiency in many areas—but also where its limitations become clear. Legal operations often involve context, judgment and subtle distinctions that automation isn’t yet equipped to handle.
In all these areas, human teams composed of top talent remain the gold standard. That’s why scaling operations successfully in this new AI era depends not just on adopting automation but also on pairing it with the right operational talent.
Where AI Falls Short In Legal Ops
In conversations I’ve had with legal ops directors recently, one common thread keeps surfacing: They’re eager to use AI but unsure where to draw the line.
AI tools are excellent at predictable, rule-based tasks. They can sort, summarize and draft faster than any human. But legal work isn’t always predictable. It often involves ambiguity, exceptions and case-specific nuances that software simply isn’t built to handle. As a result, counting on skilled human professionals still matters in many areas, such as:
• Electronic Discovery: AI-powered systems can rapidly scan huge volumes of data and identify relevant keywords and metadata, but people are still needed to validate attorney-client privilege, understand tone and escalate gray areas.
• Records Retrieval: AI can generate request forms and track request status, but it can’t build relationships with custodians to ensure they fulfill records requests, and it can’t always ensure compliance with HIPAA and state laws.
• Transcription: AI can handle voice-to-text conversion, but humans are needed for accuracy, formatting, speaker attribution and legal context.
• Compliance Workflows: AI might surface deadlines, but human oversight is required to apply jurisdictional rules and account for real-world case management complexity.
What I’ve observed while overseeing teams in these areas is that AI can handle the “what,” but humans are still needed for the “why,” “how” and “Is this right?”
The Case For Top Talent
What this means for law firms and legal service providers is simple: You still need great people. Operational teams that can think critically, escalate appropriately, communicate clearly and adapt to the nuances of the legal environment are irreplaceable. You also need humans who are highly skilled at the extremely detail-oriented and sometimes repetitive tasks the above functions require. As AI continues to automate portions of the workflow, the value of skilled legal ops professionals becomes even more concentrated.
But there’s a challenge. Clients want faster service and lower costs. As a result, legal teams are under pressure to scale but not to overhire. This is where the delivery model becomes key.
Considerations If Turning To Nearshoring
To help meet this demand, I’m seeing through my company’s work that some legal leaders are turning to nearshoring legal operations teams. These professionals are fluent in English, aligned with U.S. legal standards and operate in the same or similar time zones, which can allow them to integrate with internal teams. The lower costs of working with nearshore talent can also allow firms to scale efficiently.
However, there are a few key practices legal leaders need to be aware of if they’re considering this option, especially if the team will be working alongside AI tools.
1. Remember that clarity is critical. Define roles, responsibilities and escalation protocols early. When it’s clear where AI ends and human oversight begins, teams can operate more efficiently and avoid costly gaps.
2. Invest time in onboarding and training. Nearshore professionals perform best when they understand the workflow and the firm’s culture, tone and decision-making norms.
3. Train your team on using AI tools. In areas where operational teams work directly with AI tools, such as transcription, it’s important to ensure talent is AI-enabled so they’re able to work seamlessly with your platforms.
4. Prioritize communication. We often advise clients to maintain close communication loops between nearshore and onshore staff. Regular huddles, shared documentation and integrated project management tools go a long way in aligning expectations.
Ultimately, while nearshore teams may be able to help with your operations, to ensure success, it’s important to view them as direct extensions of your legal ops team.
The Way Forward
AI isn’t replacing people in legal ops. It’s changing where they’re needed and how you empower them. I believe the firms that will thrive in the next chapter will be those that don’t just adopt new tools but also reimagine their staffing strategies.
The real innovation isn’t in replacing people. It’s in placing the right people where they’re most effective. The most successful firms won’t be those that adopt the most AI; it will be those that build the most thoughtful partnerships between people and technology.
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