Emerging technologies—such as artificial intelligence, virtual and augmented reality, and robotics—are likely influencing or disrupting every industry. L&D teams are uniquely positioned to lead through those massive changes because they play a strategic role in future-proofing organizations by upskilling and reskilling people, driving change, and fostering cultures of continuous development and innovation. For L&D teams to thrive in the current landscape of constant evolution, it is essential for them to be agile about building organizational fluency in emerging technologies.

Barriers to fluency

A team having fluency in emerging technologies means that it can apply new technologies productively at work and make informed decisions about new vendors. Fluency can also enable L&D professionals to be proactive about changes in employee expectations as the evolving technology changes their roles and the skills they need and increases their quality standards for learning solutions. The reality, however, is that many L&D teams struggle to keep up with emerging technologies, let alone be ahead of the curve with what's coming next.

Within McKinsey Learning, we aspire to foster a culture of sustained innovation in L&D through a function called the Research and Innovation Learning Lab. In the Learning Lab's projects, we have explored how to future-proof our organization's L&D teams by rapidly developing fluency in emerging technologies. Through surveys and interviews with L&D leaders, we have found common barriers to achieving such fluency.

The rapidly evolving technology landscape can lead L&D teams to be reactive instead of proactive. Technological advances have always transformed the work of L&D, but the leaps happening now are exponential. Myriad new technologies and products are appearing, and trying to sift through them to find the golden opportunities can be overwhelming.

It is rare for an L&D team to have a seat at the table to influence which emerging technologies the company will bet on in the future at an enterprise level. Often, L&D will reactively adopt technologies when pressured by the organization or the industry's digital transformation initiatives. That leads to potentially making fragmented, subscale investments in overhyped technology.

Gaps in technical knowledge can intimidate and overwhelm L&D professionals. It can be intimidating to approach a new technology when the information is wrapped in a language you don't comprehend. L&D practitioners often feel that the information they find requires a robust technical foundation to begin to understand. That can deter them from actively participating in strategic discussions with stakeholders and business partners because they are unsure about explaining new opportunities and the implications of integrating such technologies.

L&D teams face resource constraints to develop themselves. Most L&D teams are already stretched thin to get their regular job done and don't have enough time or resources to build their capabilities around emerging technologies. Such a resource constraint can be a significant barrier for L&D functions in planning, organizing, and delivering targeted fluency workshops.

The insights we have compiled about overcoming those challenges stem from reflecting on our team's efforts to develop fluency in emerging technologies in our talent organization. The process started organically and has evolved, but with the gift of hindsight, we can organize the process around three crucial questions.

How can L&D teams filter through the noise?

The technology landscape changes at a vertiginous pace, and there is an overwhelming number of signals about the next big thing in emerging technologies, most of which turn out to be only passing trends. The key to filtering through the noise is to start with your company's challenges and needs. Only after the organization defines the problem to solve can it recognize whether a technology will be a good fit. Often, a team will start with the technology and pursue it without having an apparent use for it. Doing so can result in a waste of time and resources in passing trends that may sound exciting but don't address the team's current needs or work in its context.

To decide whether a technology can be relevant to your team's needs and context, consider:

• Potential impact. Can the technology address L&D's biggest challenges or create new opportunities for your team and learners?

• Alignment with your company's goals and priorities. Does the technology align with the organization's objectives and forecasted needs?

• Practicality for L&D. Could competitors or the wider L&D community adopt the technology in the coming two to three years?

• Potential risks. Based on your knowledge, does the technology meet the organization's safety and compliance standards?

If you can answer yes to at least two of those questions, then it may be worth continuing to investigate.

One example of how our team used those questions to filter through the noise is the case of generative AI. The Learning Lab had been exploring AI for some time—mainly applied AI—but when ChatGPT came onto the scene in November 2022, we saw massive disruption in most fields and re-evaluated whether we were doing enough with generative AI and large language models (LLMs). Although imperfect, ChatGPT was an accessible consumer-grade solution that made everyone pay attention.

At that point, we asked ourselves the aforementioned four questions. We determined that generative AI and LLMs could be game changers in helping us address two main priorities: scale and personalization. We weren't yet sure whether generative AI and LLM tools would meet our organization's cybersecurity standards. Still, the other signals were so strong that we knew we had to start equipping our team with at least some essential fluency, even if we couldn't start using the tools immediately.

On what should L&D teams focus?

As much as some L&D leaders would like it, everyone on the team cannot become a super user of every emerging technology. Considering the constraints L&D teams typically face, it wouldn't be possible—and it's unnecessary. Instead, focus on a targeted skill development goal that fits your L&D team's needs and works within any constraints, such as resource limitations, difficulties finding subject matter experts with knowledge of both the target technology and L&D, and having stakeholders who are resistant to emerging technologies.

There are multiple dimensions to fluency in emerging technologies. Looking back at our team's efforts to develop fluency in generative AI and LLMs, we have categorized the different goals that we set into four dimensions:

• Discover. Foster a mindset of openness, curiosity, and readiness for change.

• Know and think. Build a foundation of technology knowledge and a perspective on potential opportunities, risks, and ethical considerations.

• Play and imagine. Ideate how the technology can solve problems, enhance learning experiences, and offer new opportunities.

• Engage. Exchange insights and promote a culture of collaborative learning and innovation within the L&D team.

Instead of trying to upskill yourself and your team in every possible area related to new technologies, narrow the scope to what will be helpful and relevant right now.

We began in January 2023 with the discover dimension during a weeklong event. Our relatively modest goal was to spark curiosity and introduce L&D colleagues to basic AI terminology and concepts. Starting with that goal helped the team to ease some anxiety about generative AI. We also collected new research questions and ideas for experiments, such as synthesizing large amounts of qualitative survey results and producing videos using firm-approved generative AI tools. Stakeholders were supportive because they co-created those insights.

We have repeated the goal-setting exercise a few times throughout the year for the AI and LLM fluency-building efforts and have covered all four dimensions little by little. For the other three goals, we started with more targeted workshops with cohorts of about 12 colleagues, including leaders and representatives from different L&D teams. Participants collectively created a perspective and identified high-impact opportunities throughout the sessions.

What can L&D teams do within their constraints?

Given how fast the landscape evolves, learning about emerging technologies must occur quickly. Your team shouldn't wait for all the conditions to be perfect; work with what it has.

After narrowing down which dimension of technology fluency the team will set out to achieve, take small, manageable steps that will work within the constraints. Break down big, ambitious initiatives into more manageable actions to make them more feasible and sustainable.

For example, to navigate resource constraints throughout 2023 to build fluency in generative AI, we focused on the following top three endeavors.

Direct, candid dialogues with in-house experts. We assembled a panel of internal leaders who had expertise in either AI or L&D and invited L&D practitioners to attend and ask the panelists questions. Because participants joined a conversation directly tailored to the organization's context, they built a sense of ownership in exploring the topic, and the safe space allowed for them to ask candid questions such as "Will I lose my job because of AI?" The L&D leaders also role-modeled curiosity and openness to change.

Bite-size content curation over creation. We curated small learning bites about basic AI concepts and terminology. They took about 10 minutes to consume via an internal messaging application.

Research and teach-backs. During a workshop, participants quickly investigated a specific topic related to AI, such as new skills and capabilities for L&D, mapping AI use cases in L&D and talent development, as well as risks and ethical considerations. Afterward, individuals taught the other participants what they had learned.

Change management plan

For L&D to lead the way through the disruptions brought on by emerging technologies, the team must develop fluency in an agile way and take a holistic view of the different levers influencing larger organizational change. Our L&D leaders looked for ways to drive the safe adoption of emerging technologies based on McKinsey's Influence Model (see sidebar), a framework the company uses to support internal as well as clients' change management initiatives. Although the fluency-building efforts we've described focus on one of the model's areas—developing talent and skills—our process also encompassed the other three. L&D teams should likewise leverage all the elements of the model to lead change.

For example, employees need to know not only how to apply a skill but also why they must change their behavior. If there's no understanding of conviction behind the reasons for a change, people won't be inspired to modify their behavior. Another element is role modeling. Ensure that the people with influence in your company are role modeling a culture of embracing emerging technology. Also remember that every organization has a set of formal reinforcing mechanisms—such as performance reviews—which may discourage people from changing instead of motivating them to do so. For instance, if a company primarily rewards staff for completed projects and not for experimentation and attempts at innovation, individuals may feel deterred from trying new tools.

To ensure that your team can sustain efforts over time, consider the following recommendations.

Leverage grassroots efforts in the L&D team. Identify and empower existing interest groups or colleagues who are enthusiastic about the topic. Change innovations should happen both top-down and bottom-up. A solely top-down approach will not only discourage people but also limit innovation opportunities.

Balance creation versus curation. Consider curating resources instead of creating new materials. Empower people to teach one another and create forums to co-create insights.

Prioritize one or two use cases. Choose emerging technologies and fluency dimensions that will bring the most value and be most relevant to the challenges your L&D team needs to tackle.

Continue paying attention to the signals. Regularly monitor technology updates and industry trends or follow influencers who can distill the information for you. Cultivate a community within the L&D team where continuous learning and knowledge sharing are the norm.

Enduring fluency

We invested in building fluency little by little, creating momentum that led to experimenting with new tools and developing perspectives to future-proof the L&D organization. After the success of the fluency-building initiatives in the L&D team, we radiated the same strategy to other parts of the talent organization.

Within a few months, the L&D function adopted our organization's AI tool, and learning leaders accelerated the integration of learning content and use cases into it. We are now much better equipped to evaluate AI tools and make pilot recommendations. Further, we expect AI to play a role in all our programs in the coming months. We have also started to formalize the successful experiments that occurred organically into official structures, processes, and support systems, such as assigning people to be AI adoption champions in their different L&D teams.

The journey to build enduring fluency in emerging technologies won't happen overnight, and the constraints won't disappear soon. But taking small, incremental steps can lead to a future-ready L&D team.

Influence Model

The Influence Model, developed by McKinsey & Company, is a framework that helps guide organizations through comprehensive transformations by addressing underlying mindsets and behaviors. It consists of four elements—understanding and conviction, role modeling, reinforcing with formal mechanisms, and developing talent and skill—which work together to drive organizational behavior change and achieve desired outcomes. The McKinsey Quarterly article "The Four Building Blocks of Change," explains that the model embodies the following construct.

I will change my mindset and behavior if:

I understand what is being asked of me, and it makes sense. (Understanding and conviction) I see my leaders, colleagues, and staff behaving differently. (Role modeling) I see that our structures, processes, and systems support the change I am being asked to make. (Reinforcing with formal mechanisms) I have the skills and opportunities to behave in the new way. (Developing talent and skill)