You’re a learning and development (L&D) leader who’s charged with allocating the upcoming fiscal year budget to projects that you believe will benefit your organization and its employees. You have so many options but don’t know which areas need the most attention and will result in positive change. You need to be able to tell the C-suite that you made good investment decisions and show how you prioritized program choices while showing a measurable impact.

Sound familiar?

Most L&D leaders struggle to determine whether their learning investments result in desired change. With the advent of modern technologies such as artificial intelligence (AI), there are new opportunities to leverage computing power to help L&D leaders achieve their goals.

You may wonder if technology like AI can help you better understand what areas are most likely to affect change. With AI, you can do two things to help improve L&D’s strategic value to the organization:

• Pinpoint problem areas before they happen.
• Track L&D initiative progress over time.

L&D Initiatives

Let’s explore some company initiatives that L&D leaders are often tasked with or play a large role in ensuring their success:

• Diversity, equity and inclusion (DEI) — Training professionals are increasingly being put in charge of DEI initiatives. Because driving inclusion is a long-term goal that requires an ongoing commitment to supporting equitable work and learning environments, programs that aim to address this area are frequently viewed as generic and a check-the-box exercise to show that the organization is doing something about improving DEI in the organization. L&D leaders are looking for ways to understand which DEI learning programs will have the greatest impact and how to sustain that impact over time.
• Reducing employee turnover — Retaining and growing talent is a top concern for human resources (HR) and L&D, especially in a tight economy, where the time and cost to replace employees is growing. Getting signals at the onset of potential areas that could cause an exodus of top talent is critical so that L&D leaders can respond with timely learning opportunities that help to keep employees engaged.
• Uncovering unfair workplace treatment — Every organization agrees on one thing: They don’t want to be the next negative headline. Recently, much of that has been due to revelations about how some leaders and/or organizations treat their employees, causing resentment, fear of speaking up and job safety concerns. L&D is usually asked to “fix it” without being given much direction.
• Improve culture post-merger – Many mergers and acquisitions fail due to cultural differences that are too great to overcome. Because culture is typically hard to identify and even harder to instill in others, it presents a challenge for L&D to identify specific ways that individuals and teams can exemplify cultural traits that the organization seeks to model.

Where AI Comes In

So, how can AI help L&D leaders achieve success in these initiatives? Consider these areas:

Solicited vs. Behavioral Data

Surveys are the most common type of solicited data. When an organization wants to get employee input on a specific topic, they usually ask them in some form of a survey. While this seems the most straightforward, it presents a few issues.

People often respond to surveys with what they feel like the organization wants to hear rather than what they truly think. This results in a high potential for biased results. Another challenge is survey fatigue, which can adversely affect the quality of data. Think about how many pulse surveys or similar feedback forms you were asked to respond to during COVID-19. Low participation rates are a symptom of survey fatigue.

Solicited data usually results in the squeaky wheel getting the grease. In other words, the loudest voices tend to get the most attention, whether it’s warranted or not. It’s just as important to understand who is not responding to surveys, why they’re not responding and what they may potentially have to say about what you’re looking to uncover.

Behavioral data captures what people are actually doing in the course of their work. Instead of asking what people think about a specific topic, AI systems can monitor activities related to achieving company objectives while aggregating and anonymizing the data to provide insights on trends that L&D leaders can act on.

An added bonus of behavioral data is that it is much more holistic and can include the entire organization, without the need for active employee participation. This level of observation helps to reduce any bias from overrepresented participants and topics in traditional forms of solicited data.

Quantitative Versus Qualitative Data

Most measurement tools and business key performance indicators (KPIs) focus on quantitative data, in part because making decisions based on hard numbers is viewed as an effective strategy. We see this in L&D as well, where training completion rates, course evaluations and amount of learning consumed are touted as quality metrics. What’s missing is balancing this with qualitative data.

AI systems can use sentiment analysis to better understand how people feel about different learning outcomes and use that information to drive strategic decisions. Sentiment analysis is a natural language processing (NLP) technique to gauge where people feel positive, negative or neutral about something. When applied to L&D strategy, sentiment analysis can be used to uncover blind spots and trends that, if left unchecked, could result in high risk for failure.

Historical vs Real-time Data

Old data drives decision making. And that’s not a good thing, since things move quickly in organizations that cause data to become outdated. Yet leaders constantly make decisions with old data because they feel there is no better alternative. Plus, it’s better than going on intuition.

AI can collect and analyze real-time data to arm leaders with the most current information for making strategic decisions. This equips L&D leaders with the capacity to get ahead of trending workplace topics and deploy targeted learning interventions. AI can also give L&D leaders a “superpower” to better predict learner needs at the right moment, resulting in a more engaged learning population and a more efficient use of resources.

AI’s Future in L&D Strategy

Humans are good at many things; machines are good at many other things. It would be prudent for L&D leaders to consider how AI can help them become more valuable in their organization. Leaders are good at understanding the nuances of their environment and figuring out how to best deploy talent and resources for maximum effectiveness. AI is good at collecting and classifying large amounts of data, looking for patterns and presenting high-level findings that leaders can act on. As L&D leaders look to define their strategy, plan programs and allocate resources, AI systems can be a valuable asset along the journey.