When Docebo‘s Chief Learning Officer, Brandon Carson writes that “the greatest threat isn’t malicious actors but enthusiastic early adopters operating without adequate knowledge or guardrails,” he’s describing exactly what we at Brandon Hall Group™ are seeing across organizations at every maturity level. The statistic he cites — that 70 percent of AI implementation challenges relate to people and processes, not technology — tells a story our research confirms repeatedly: Organizations are trying to solve a workforce problem with technology solutions.
And it’s not working.
Only 4 percent of companies have developed AI capabilities generating real business value. That gap isn’t about better algorithms or more powerful models. It’s about the foundation that Docebo, a Brandon Hall Group™ Smartchoice Preferred Provider®, identifies as non-negotiable: strategic AI literacy and governance working in tandem.
The Literacy-to-Fluency Journey Is Real
Docebo’s distinction between AI literacy and AI fluency captures something critical that we’ve observed across 600 organizations: Competency development isn’t binary. You don’t simply “know AI” or not. There’s a progression that organizations must intentionally design and support.
AI literacy is the baseline. It means understanding fundamentals, recognizing risks, and applying policies. Every person in the organization needs this foundation. Our research shows that organizations in the earliest maturity phases (what we call Reactive/Ad Hoc) struggle precisely because this universal baseline doesn’t exist. People are experimenting with consumer-grade AI tools without enterprise security, unable to evaluate vendor claims, introducing bias without awareness.
But literacy alone isn’t enough. The concept of AI fluency where employees move from basic usage toward creative application and strategic innovation maps directly to what happens when organizations build genuine capability. Fluent employees don’t just use AI tools. They initiate process improvements, articulate AI’s role clearly, challenge and adapt AI outputs, and develop novel applications aligned with strategic goals.
We see this progression play out in our competency data. Organizations that invest in moving people from awareness to enabled to proficient capabilities report fundamentally different outcomes. They’re not just deploying AI. They’re innovating with it.
Governance Evolves With Capability
Here’s where Docebo’s framework becomes particularly valuable: the recognition that governance must evolve as organizational capability matures. Too many organizations treat governance as a static compliance checklist. Really, there are three distinct phases in the journey to true AI capability: centralized governance with clear rules, controlled expansion with domain-specific guidelines, and distributed intelligence with principles-based guidance.
Our research across organizations at different maturity phases validates this progression. At the beginning, most organizations have no formal AI governance framework at all. The result? Uncontrolled risk exposure. These organizations face the challenge of using consumer AI tools without enterprise security, lacking AI literacy, and having no budget allocated for AI initiatives.
By the time basic governance structures emerge with initial policies and guidelines, risk assessment processes begin including AI considerations. But here’s the challenge Docebo identifies well: inconsistent governance application across pilot projects. Those newly established frameworks get applied unevenly or incompletely across different initiatives. The opportunity centers on developing standardized AI governance processes and decision criteria that work consistently across all initiatives.
Once organizations achieve what Docebo describes as comprehensive governance with defined roles and responsibilities. Our governance structure model shows exactly what this looks like: Board oversight, executive leadership engagement, specialized committees for AI ethics, technical standards, and risk management. When an AI Strategy Committee meets monthly for strategic review and quarterly for comprehensive assessment, with clear decision authority for investments, that’s mature governance enabling innovation within appropriate boundaries.
The most mature organizations, representing just 29 percent of organizations in our research, have automated monitoring, real-time risk management, and predictive compliance systems. Some are approaching what Docebo describes as “adaptive frameworks that empower employees to make responsible decisions within established parameters.” They’ve shifted from prescriptive rules to principles-based guidance because their workforce has the literacy and fluency to operate responsibly.
The Timeline Matters
Docebo’s five concrete steps for executives are actionable precisely because they acknowledge something many organizations miss: this takes time and sustained commitment. You can’t build enterprise-wide AI capability in a quarter. This isn’t about checking boxes. It’s about building the foundation that makes everything else possible.
Learning and Development (L&D) professionals have a unique chance to simultaneously create AI programs and participate in governance structures. This dual role ensures that training aligns with governance requirements. It also provides governance teams with practical insights from the learning environment.
Measuring What Matters
We must move beyond simple training completion rates toward evaluating actual capability development. It’s important to track employee development from current AI levels to target levels and identify key skill gaps with assigned development priorities. But the real value comes from what Docebo describes: skills assessments that challenge employees with realistic scenarios, measuring how they navigate AI ethical dilemmas and apply appropriate judgment.
This assessment approach reveals something important: competency develops along a continuum, not through binary achievement. You can’t simply declare someone “AI competent” after completing a course. Capability builds through application, experimentation, feedback, and refinement.
The Integration Imperative
What makes Docebo’s approach right for this moment is the recognition that AI literacy, fluency, and governance must develop simultaneously, not sequentially. You can’t wait to build governance frameworks until after literacy programs complete. The frameworks inform what literacy programs must teach. Literacy programs prepare employees to operate within governance boundaries.
Our research confirms this integration imperative across all maturity phases. Organizations attempting sequential implementation consistently struggle. The successful transformations we document are those that build both capabilities and guardrails together from the start.
This extends to the cross-functional coordination that Docebo emphasizes. AI transformation affects multiple functions simultaneously, requiring sophisticated coordination to avoid conflicts and ensure synergies. Our enterprise AI governance framework shows that effective AI Strategy Committees include the Chief Executive Officer, Chief Human Resources Officer, Chief Information Officer, Chief Financial Officer, Business Unit Leaders, and AI Subject Matter Experts. This isn’t bureaucracy. It’s recognition that AI transformation is an enterprise challenge requiring enterprise-level coordination.
The Challenges Are Predictable
Governance challenges across maturity phases consistently line up. Organizations in early maturity struggle with lack of AI literacy and foundational understanding, fear and resistance among staff, absence of AI strategy or governance frameworks, and inability to evaluate AI vendor claims. While organizations which are slightly more mature face inconsistent governance application across pilot projects. As maturity increases, the challenges shift. Organizations must manage comprehensive framework complexity while maintaining innovation agility or encounter challenges managing interconnected AI systems, ensuring meaningful human oversight in automated processes, and adapting to rapidly evolving capabilities.
The good news? These challenges are predictable. Organizations can prepare for them. The governance opportunities Docebo outlines for each phase provide clear direction: establish foundational AI ethics and risk management frameworks early, develop standardized governance processes that scale, implement predictive governance models for proactive risk mitigation, and ultimately lead industry transformation in AI governance standards and practices.
Why This Matters
Some analysts and advisors forecast that AI will add close to $16 trillion to global economic output by 2030. That value won’t materialize automatically. It requires exactly what Docebo describes: organizations that build strategic AI literacy and governance as the foundation for responsible innovation.
The competitive advantage isn’t going to organizations with the most advanced AI technology. It’s going to organizations with workforces that can effectively collaborate with AI, innovate using AI, and operate responsibly within appropriate governance frameworks.
Docebo’s framework provides the roadmap. Our research validates it works. The question is how quickly can your organization build these foundational capabilities before the competitive gap becomes too wide to close.
Read the full Docebo article, “Building AI Literacy and Governance: The Foundation for Responsible Innovation,” for detailed insights on implementing these strategies in your organization.
