We9re seeking a Manager of AI-Enabled Knowledge Management in our Atlanta, GA office to help evolve how the firm captures, curates, governs, and activates knowledge in an AI-powered era. This role will play a strategic and operational part in strengthening the firm9s knowledge foundation-our competitive advantage-by improving content quality, discoverability, reuse, and integration into client delivery and business development workflows.

SUMMARY:

As part of the Knowledge & Strategy function within the Strategy & Growth team, the AI-Enabled Knowledge Management Manager will lead end-to-end knowledge lifecycle activities, from capture and curation to taxonomy, governance, and adoption. The role partners with IT / Data / AI owners to define KM requirements for RAG, semantic search, metadata, knowledge quality, source validation, and governance. The role will also incorporate applied and builder-level AI capabilities, helping design and implement AI-enabled knowledge workflows (e.g., copilots, metadata automation, semantic search) that improve speed, accuracy, and usability while maintaining strong governance and trust.
The role will partner closely with Practice leaders, account teams, Strategy & Growth, Marketing, Technology, and client-facing teams to ensure knowledge is high-quality, accessible, and embedded into how the firm sells and delivers work. The role will also cross-train with Research colleagues to support secondary research needs when required, though research is not a primary responsibility.

KEY RESPONSIBILITIES:

A) Knowledge asset lifecycle & IP reuse

• Oversee knowledge capture processes for priority assets, including project deliverables, proposals, qualifications, methodologies, and reusable client assets.
• Partner with subject matter experts and account teams to ensure content accuracy, relevance, and alignment with business priorities.
• Accountable for AI knowledge architecture and AI quality controls, partnering with AI COE, IT, teams
• Define and maintain content curation standards, including quality, context, sensitivity, and reuse guidelines.
• Identify content gaps, duplication, and outdated materials; drive refresh, consolidation, or retirement actions.
• Facilitate knowledge-sharing sessions and enablement activities for client-facing teams.

B) AI-enabled knowledge systems and workflow design

• Apply AI tools to improve knowledge workflows, including summarization, classification, metadata enrichment, and content discovery.
• Help design and scale AI-enabled KM capabilities (e.g., copilots, knowledge assistants, semantic search, metadata automation).
• Develop and maintain reusable prompt libraries, templates, and workflow playbooks for KM use cases.
• KM product owner / roadmap partner for Hub / search / AI-enabled knowledge experiences
• Partner with Technology and business stakeholders to define requirements for AI-enabled knowledge systems.
• Evaluate AI-generated outputs for accuracy, relevance, and alignment with firm standards.
• Support experimentation and adoption of emerging AI KM capabilities.

C) Taxonomy, metadata, and knowledge architecture

• Own and evolve taxonomy, metadata, tagging, and content structures to improve findability and reuse as enterprise search, AI, and semantic retrieval evolves.
• Translate business needs and user behavior into practical information architecture improvements.
• Establish and maintain metadata standards and controlled vocabularies.
• Enable AI-assisted tagging and metadata workflows with appropriate governance and validation.
• Use analytics and user feedback to continuously improve search relevance and knowledge experience.

D) Governance, quality, and trust

• Maintain governance practices for knowledge quality, lifecycle management, and content ownership.
• Define and enforce standards for content validation, freshness, and reuse.
• Partner with Legal, Compliance, and Technology to ensure secure and responsible knowledge use.
• Drive and promote responsible AI practices, including source validation, transparency, human-in-the-loop review, content provenance, confidentiality/permissions, AI answer-quality feedback loops, and AI-ready knowledge standards.
• Monitor and report on KM health metrics (quality, usage, adoption, gaps).

E) Adoption and knowledge-sharing culture

• Drive adoption of KM tools, practices, and AI-enabled workflows through promotion, training, and stakeholder engagement.
• Develop communications, playbooks, and enablement materials to support knowledge reuse.
• Build strong relationships across teams to encourage contribution and continuous improvement.
• Translate KM and AI concepts into clear, business-relevant messaging.

F) Insights integration & business value

• Support secondary research efforts (e.g., market scans, competitive intelligence, benchmarking) when needed.

Partner within Strategy & Growth, Marketing, Practices, and IT to improve reuse and speed to insight.

IDEALLY, WE9D LIKE:

• Bachelor9s degree in information science, Business Administration, Library Sciences, or related field; Master9s degree preferred
• 7+ years of experience in knowledge management, information management, or related field, preferably in consulting or professional services.
• Strong understanding of KM principles, taxonomy, metadata, and knowledge lifecycle management, with a focus on AI applications and use cases.
• Proficiency in enterprise knowledge platforms (e.g., SharePoint) and content systems.
• Practical experience applying AI tools proactively to transform workflows, enhance KM and content management activities, and drive quality decision-making.
• Strong analytical, critical thinking, and problem-solving skills.
• Excellent communication skills (including visual communication), with the ability to simplify complex concepts and demonstrate the business impact of KM solutions
• Emotional intelligence, relationship-building, change management, and stakeholder management skills to foster a knowledge-sharing culture.
• Posture of curiosity, open-mindedness, bias for action, and tolerance for ambiguity and 4always-on4 change in the business and KM landscape. A positive, can-do spirit.

Preferred Qualifications:

• Experience with enterprise search, semantic search, or AI-enabled knowledge systems.
• Experience developing taxonomies, metadata schemas, or information architecture.
• Familiarity with data visualization and reporting tools (e.g., Power BI).
• Experience supporting research or insights generation.
• Understanding of data governance and responsible AI practices.

Tools & Technology Expectations:

• Knowledge platforms (e.g., SharePoint, Teams)
• Enterprise AI tools (e.g., Microsoft Copilot, Claude)
• Data visualization and reporting tools (e.g., Excel, Power BI)
• Content and metadata management tools
• Workflow and automation tools (e.g., Power Automate)

Competencies:

• Knowledge curation and content strategy
• Information architecture (taxonomy, metadata, findability)
• AI-enabled workflow design and application
• Governance and quality management
• Stakeholder collaboration and influence
• Analytical thinking and insight generation
• Communication and storytelling
• Adaptability and continuous improvement mindset

Expectations:

• Productivity: Delivers high-quality work within expected timeframes.
• Accuracy of Work: Ensures precision and quality in content, data, and outputs.
• Business Acumen: Aligns KM activities with business priorities and client value.
• Relationship Management: Builds strong partnerships through responsiveness, collaboration, knowledge share, and a solution-oriented approach.
• Communication: Provides clear, effective messaging across formats and audiences to influence the business.
• Cultural Awareness: Demonstrates alignment with North Highland9s values and collaborative culture.

Applicants must be authorized to work in the United States, without the need for visa sponsorship by North Highland. Work visa sponsorship will not be provided, either now or in the future, for this position.

Reference: 50468