Artificial Intelligence Change Enablement Lead

K&L Gates•Austin, TX

25d•$111,000 - $209,000

About The Position

At K&L Gates, we are looking for smart, imaginative and hard-working people with diverse backgrounds, experiences and ideas to join us. Perhaps our search for talented visionaries and your search for important and impactful work lead to the same place. We are seeking an AI Change Enablement Lead to join the firm. The AI Change Enablement Lead promotes firmwide AI adoption by developing tailored training programs and materials for diverse teams. This role creates engaging content, establishes an AI Champions program, and implements effective change management strategies. By collaborating with leadership and tracking outcomes, the Lead fosters innovation, ethical AI practices, and continuous improvement. Successful candidates bring expertise in AI, change management, technical training, instructional design, communication, and project management.

Requirements

Possess Bachelor's degree in Education, Instructional Design, Organizational Development, Business, Communication, or related field
Demonstrate expertise in change management methodologies, such as Prosci ADKAR, Kotter's 8-Step Process, and McKinsey's 7-S framework.
Be knowledgeable in instructional design principles, adult learning theory, and training delivery methods
Demonstrate expertise in artificial intelligence technologies, prompt engineering, and practical applications within business environments, focusing on generative AI, large language models, and Microsoft Copilot.
Be familiar with Microsoft 365 ecosystem (Copilot, Power Platform, Teams, SharePoint)
Demonstrate proficiency using project management tools, learning management systems, and analytics platforms to manage multiple, concurrent initiatives
Possess excellent presentation and public speaking abilities with confidence delivering to groups of varying size, knowledge, and level of responsibility
3+ years of experience in change management, learning and development, or enablement roles, ideally in professional services or technology adoption
Demonstrate expertise in creating and implementing educational programs tailored for varied and professional audiences.
Demonstrate experience leading organizational change initiatives and managing stakeholder resistance
Demonstrate experience with AI technologies, digital transformation, or enterprise software adoption to support organizational advancements and technological integration.
Show ability to create a wide array of training materials and utilizing various facilitation techniques for end-user training and engagement

Responsibilities

Developing and implementing detailed change management strategies using established frameworks (e.g., ADKAR, Kotter) to support organizational transitions during AI adoption.
Developing and implementing the firm's AI Change Enablement strategy, creating clear adoption plans aligned with organizational goals and objectives.
Managing organizational resistance by creating and implementing multi-channel communication plans to clearly convey and emphasize the value proposition during the adoption process.
Partnering with leadership, practice group heads, and business unit leaders to secure sponsorship and drive top-down commitment.
Designing and delivering role-based AI training programs for diverse audiences using in-person, virtual, and on-demand sessions and supporting materials.
Using instructional design principles and adult learning theory to create accessible, relevant, and actionable customized for different groups across the firm. Identifying capability gaps, gather requirements, and design training solutions to address those needs.
Establishing a firm-wide AI Champions Network of individuals to serve as AI advocates, early adopters, and first-line support within their teams.
Designing programs and organizing meetings and activities aimed at fostering development and engagement of AI Champions.
Engaging in pilot initiatives and proof-of-concept programs to evaluate user experience and refine enablement methods. Working directly with end users to understand workflows, pain points, and training needs.
Developing deployment playbooks and creating adoption resources combining technical rollout with structured change management.
Partnering with legal, compliance and other IT teams to develop AI usage guidelines and policies, and promote responsible AI adoption.
Establishing KPIs. metrics, dashboards, and feedback mechanisms to track adoption rates, engagement levels, and business impact. Conducting retrospectives to identify process improvement opportunities.