Building a Legal AI Dream Team Means Prioritizing the Human Side

Building the right team with the right capabilities is the most overlooked aspect of legal artificial intelligence implementation, and it’s often the most decisive. This isn’t just about hiring—it’s about reimagining the skills, structure, and culture that drive legal innovation.

Integrating AI into legal practice creates demand for skills that didn’t exist in traditional legal organizations. It’s adding technical experts to legal teams as well as developing hybrid capabilities that bridge multiple domains:

• Technical fluency: Understanding AI capabilities and limitations
• Legal domain expertise: Deep knowledge of substantive law and practice
• Process design skills: Ability to reimagine workflows and systems
• Change management capabilities: Skills to drive organizational adaptation
• Data governance knowledge: Understanding of data quality and management

Don’t worry about finding individual contributors who possess all these skills (they rarely exist). Focus on building teams that collectively can cover these capabilities while creating enough shared understanding to collaborate effectively.

The most successful legal AI implementations rethink traditional organizational structures. Three models proving to be particularly effective are:

The fusion team model. Multidisciplinary teams combine legal, technical, and operational expertise in permanent, dedicated groups. Rather than maintaining separate departments that collaborate occasionally, these organizations create persistent teams where different perspectives are continuously integrated.

These teams would include attorneys, data scientists, process engineers, and client relationship specialists. These teams own entire workstreams, from client intake through delivery and feedback, ensuring technology serves business needs rather than existing as a separate function.

The advantage is deep integration and shared context, but it requires significant cultural change and leadership commitment.

The hub-and-spoke model. This structure contemplates a central innovation/technology team that partners with practice groups through dedicated liaisons who understand both domains. The central team provides technical expertise and consistent standards, while liaisons ensure solutions address specific practice needs.

This is often the model seen in central legal technology innovation centers where innovation leaders collaborate with selected practice groups while continuing to practice law and serving as translators between technical capabilities and practice needs.

The advantage balances centralized expertise with practice-specific knowledge, but it requires careful selection and support of boundary-spanning roles.

The ecosystem approach. Rather than building all capabilities internally, this model creates a curated network of partners, vendors, and specialists who can be deployed as needed. The legal organization maintains core expertise in legal-technical integration while leveraging external resources for specialized capabilities.

A small internal team focuses on strategy and governance while using a network of specialized vendors for implementation to develop standardized processes that allow quick incorporation of external expertise.

The advantage is flexibility and specialized expertise without permanent overhead, but it requires strong vendor management capabilities and clear standards. These models aren’t mutually exclusive. Hybrid approaches can be deployed to meet specific needs and constraints.

Roles for Success

Regardless of overall structure, several key roles have emerged as critical for successful legal AI implementation.

Legal solution architects. These individuals understand both legal processes and technical capabilities, allowing them to design integrated solutions that truly address practice needs. They translate between legal requirements and technical implementation, ensuring systems enhance rather than disrupt legal work.

The best legal solution architects aren’t necessarily the most technical lawyers or the most legally knowledgeable technologists. They’re bridge-builders who can navigate both domains while maintaining focus on practical outcomes.

Knowledge engineers. These specialists transform unstructured legal knowledge into structured formats that can power AI systems. They understand legal concepts deeply enough to identify patterns and relationships, while possessing technical skills to represent that knowledge in forms machines can use.

Knowledge engineers can come from a variety of backgrounds including legal practitioners, legal researchers, knowledge management specialists, or library scientists, with additional training in data modeling and information architecture.

Data governance specialists. These roles establish and maintain the data quality standards essential for effective AI. They develop classification schemes, quality control processes, and governance frameworks that ensure information is accurate, complete, and properly structured.

In legal contexts, data governance specialists need to understand the nuances of legal information, from confidentiality requirements to jurisdictional variations, while implementing practical governance approaches.

Change facilitators. These individuals focus on the human side of technology implementation: training, communication, workflow integration, and adoption. They understand both the technology and the practice context deeply enough to help others see the value and adapt their work accordingly.

Effective change facilitators combine technical knowledge with emotional intelligence, understanding that technology adoption is ultimately about changing human behavior.

The Path Forward

The most successful legal AI implementations recognize that technology transformation is fundamentally human transformation. The organizations that invest thoughtfully in building hybrid capabilities, reimagining team structures, and developing critical roles will be positioned to realize AI’s full potential.

This isn’t about replacing legal professionals with technologists or vice versa. It’s about creating new forms of collaboration that leverage the unique strengths of both domains while addressing the complex challenges of legal practice in a technology-enabled future. The organizations that get the human element right will win.

This article does not necessarily reflect the opinion of Bloomberg Industry Group, Inc., the publisher of Bloomberg Law and Bloomberg Tax, or its owners.

Author Information

Melissa Koch chairs Akerman’s technology transactions team and is a business and technology lawyer with more than 25 years of experience.

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