It enters quietly:
AI-related decisions are often distributed across teams as tools and capabilities evolve.
We help leadership clarify which decisions require executive ownership—and where greater alignment can reduce risk and inconsistency.
AI tools are becoming embedded in everyday workflows.
We help define practical guardrails so teams understand what’s acceptable, what requires review, and where boundaries should be in place as usage expands.
AI interacts with existing data in ways that can influence outcomes and perception.
We help organizations understand where data introduces risk, and how decisions may impact trust—with stakeholders, donors, clients, or the public.
As AI becomes part of daily work, decision-making can vary across teams and contexts.
We design simple, usable frameworks that bring consistency to how AI-related decisions are made—without adding unnecessary complexity.
AI is often introduced through evolving tools, expectations, and external pressure.
We help organizations take a more intentional approach—aligning implementation with governance, priorities, and long-term direction.
Before decisions are made, teams need shared language and a clear view of what AI actually does—and what it doesn’t. This stage creates alignment so leadership, staff, and stakeholders are working from the same baseline.
We surface where AI is already in use, where decisions are being made informally, and where risk or ambiguity exists. This step helps leadership understand what requires attention now versus later.
Together, we translate insight into structure—defining decision ownership, boundaries, and practical guardrails that reflect how the organization actually operates.
With clarity in place, we support thoughtful implementation—whether that means introducing tools, shaping workflows, or guiding early use cases in a way that aligns with governance.
AI decisions don’t end at implementation. We help teams revisit decisions, refine guardrails, and stay aligned as tools, expectations, and conditions evolve.
AIColabs is a collaborative advisory practice built by three practitioners who independently saw the same pattern: organizations weren't struggling with AI capability — they were struggling with AI clarity.
Leadership, Learning & Organizational Practice
Rebecca is a strategic advisor, program designer, and leadership coach with over 15 years of experience advancing equity through education, leadership development, and systems innovation. She has guided high-performing teams in program design, strategic planning, and capacity building across education, nonprofit, and mission-driven sectors.
Rebecca's expertise lies in translating vision into practical frameworks that center people and equity at every stage.
AI Decision Clarity & Real-World Implementation
Trecia is a strategic technologist focused on helping organizations navigate AI with clarity, operational awareness, and human-centered implementation. With deep expertise in digital systems design, technology planning, and human-centered implementation, she supports organizations in navigating the complexities of digital transformation with clarity and care.
Trecia brings an engineering mindset grounded in mission alignment, trust, and purposeful innovation.
Leadership, Governance & Organizational Clarity
Jason is a social impact leader with 30+ years of experience in financial management, philanthropy, and organizational strategy. At Levi Strauss & Co., he oversaw a $70M investment portfolio and $10M in annual grantmaking. He supported DE&I efforts as an ally leader and contributed to shaping Levi Strauss & Co.’s global environmental vision.
Today, he works with nonprofits and mission-driven companies to strengthen financial planning, partnerships, storytelling and long-term sustainability.
We look at how AI is already showing up across the organization—formally and informally—and identify where decisions are being made, who owns them, and where clarity is missing.
We translate what we learn into practical structures—defining decision ownership, acceptable use, and boundaries that reflect how your organization actually works.
Where implementation makes We support teams in putting decisions into practice—applying frameworks in real scenarios, without adding unnecessary complexity.
We help organizations revisit and refine decisions over time—ensuring governance evolves alongside tools, risks, and expectations.
AI decisions are often shaped by tools, vendors, or urgency.
We take a different approach.
We begin by clarifying how decisions are made, who owns them, and what needs to be true before AI is introduced.
Phase Zero is a structured engagement designed to help leadership teams understand how decisions are currently made, where AI is already influencing work, and what needs to be clarified before further adoption.
We surface the realities that shape risk, trust, and implementation—so decisions are intentional, not reactive.
This is not tool training. It’s a structured learning experience that helps teams understand where AI fits into their actual work and how to make decisions about its use.
Through scenario-based learning and decision frameworks, teams develop the context and confidence needed to move forward together.
AI decisions rarely happen all at once. They surface over time—through tools, vendors, and internal use.
We work alongside leadership to navigate these decisions as they come up, helping maintain clarity, alignment, and consistency without overbuilding process.
AI decisions don’t happen in isolation. They emerge through conversations, real scenarios, and evolving conditions.
Our Labs bring leaders and teams together through focused workshops, facilitated sessions, and small-group environments to work through real questions in real time.
This is where ideas are tested, perspectives are shared, and clarity continues to develop beyond structured engagements.
Designed for organizations that value human expertise, trust, and responsible innovation.
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