Kevin Jennings

My journey into learning and development did not start in a traditional way. I began as a founding member of a learning technology company, working across organizations of different sizes, industries and operating models. That experience gave me visibility into where learning programs worked and where they quietly failed. It also forced me to understand the problem from the outside in. It became easier to see patterns across organizations, where learning systems consistently broke down.

What became clear early on was that success had very little to do with content volume or participation. The difference came down to whether learning was connected to how work actually happened. That shifted my perspective. I stopped viewing learning as a collection of programs and started treating it as a system that either supports business performance or operates in isolation.

As I moved into internal leadership roles across industries such as insurance, manufacturing, pharmaceuticals, non-profit and recruitment, that perspective became more critical. Each environment defined performance differently and had its own tolerance for change. Applying a previous solution to a new context consistently creates gaps. Learning only works when it is built around the reality of the business it serves.

Designing Learning around Business Outcomes

In my current role within healthcare technology, I built a customer education function from the ground up in an environment where success depends on customers being able to use a technically complex product effectively.

In this context, learning is not separate from the business. If customers struggle to use the platform, adoption slows, support demand increases and renewal conversations become more difficult. Those are direct business impacts. Learning either addresses these problems or it does not.

My L&D strategy is essentially a customer success strategy. Every initiative is built to reduce friction, accelerate time to value and build confidence in users performing complex tasks. The focus is not on delivering training, but on enabling outcomes.

“L&D only earns its seat at the table when it’s visibly tied to business outcomes, not just completion rates and satisfaction scores.”

Alignment comes from staying close to the business. I spend time with product managers, support teams, sales engineers, customer success leaders and executives to understand where gaps exist. Those conversations define the problem. I work backwards from the desired outcome, clarifying what must change, what people need to do differently and the most effective way to make it happen.

Solving for Speed, Relevance and Scale

Three challenges consistently shape how I design learning systems.

The first is speed to relevance. Products and processes evolve faster than traditional learning cycles can support. By the time content is developed and deployed, parts of it are already outdated. To address this, I focus on modular learning architectures. Content is built in components so updates can be made without rebuilding entire programs. I also rely on digital adoption platforms that deliver guidance in the moment of need, reducing dependence on recall.

The second challenge is measurement. Learning is often evaluated based on inputs such as completion rates or satisfaction scores. These metrics do not reflect impact. I focus instead on operational indicators such as support ticket volume, onboarding time, product adoption and role transition rates. These are the points where learning either proves its value or does not.

The third challenge is AI. It is changing the nature of skills at a pace that is difficult to ignore. Some capabilities are becoming obsolete faster, while new ones are emerging just as quickly. At the same time, AI provides an opportunity to scale and improve learning through personalization, faster content creation and more adaptive delivery. But I think the more important conversation is about how AI functions as a multiplier for L&D practitioners, not a replacement. A single practitioner using AI effectively can now produce work that previously required a full team. That does not eliminate the need for expertise. It amplifies it. The judgments, the business context, the understanding of what learners actually need - those are still human contributions. AI just removes the bottlenecks that used to slow them down.

Measuring Impact and Staying Close to Execution

The way I evaluate learning is straightforward. I use what I refer to as the “so what” test. If I cannot explain what is different in the world because a learning experience happened, then it has not delivered value.

Measurement starts with behavior. Are people doing something differently? Are support agents resolving issues without escalation? Are customers completing workflows independently? These are direct indicators of change.

The next layer is business impact. Changes in adoption rates, time to productivity and support costs provide a clearer picture of whether learning is contributing to organizational goals. It is also important to note that not every initiative can be tied to strict ROI. In complex environments, outcomes such as confidence and capability are equally important.

One constant throughout my career is that I have remained a practitioner. I continue to build courses, systems and tools. Staying close to execution keeps my perspective grounded in what is actually difficult about the work.

For professionals in this space, the focus should be on two things. First, get comfortable at the edge of your expertise. The most meaningful work often comes from learning something new and that process keeps you empathetic to the learner. Second, understand the business. Learning theory is foundational, but business acumen determines impact.

Build, prototype and iterate rather than relying only on theory. Practitioners who can create and refine solutions build credibility that credentials alone cannot match. Stay curious about AI and experiment with it early rather than waiting for direction. Treat it as a multiplier for what you already know, not a shortcut around the expertise you still need to develop. Learning and development has to move beyond delivery. Its role is to drive measurable change. When it is designed as a system, aligned to outcomes and grounded in execution, it becomes a direct contributor to business performance.