Maximizing business impact with AI: an actionable framework for people leaders

While AI is gaining more attention in the L&D community, one important question remains: how can people leaders strategically integrate AI to amplify the impact of learning and align it directly with business goals?

To collectively address these challenges, during our first Impact Lab 2.0 event of this season, we gathered a group of global L&D professionals and our impact and AI experts, Bo Dury and Dr. Clemens Lechner, to begin unraveling the exact ways people leaders can strategically incorporate AI into their work.

Read on to discover our key takeaways and an actionable framework you can use to effectively integrate AI into your learning and development strategy.

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‍Content:

1. Why is the topic of impact and the use of AI in talent development gaining so much attention?
2. The main challenges of implementing AI in L&D
3. How can AI improve L&D’s impact? It’s time to go beyond content creation
4. Start using AI in talent development with this 3-step framework
5. A list of AI tools for L&D

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Why is the topic of impact and the use of AI in talent development gaining so much attention?

Jobs and careers have evolved significantly over the past decades. In the past, individuals acquired a skill, settled into a specific role within their industry, and often remained in that position for their entire career. Today, people frequently switch industries, and career paths are less linear; many of us are working and learning simultaneously throughout our careers. 

In this dynamic environment, learning is emerging as a strategic priority within organizations to ensure the development of the right skills for the right talent at the right time, enabling them to respond to market trends and enhance competitiveness.

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"When we look at learning impact, the question remains: ‘How do we know what’s the most impactful thing to do, to help people develop, and to help organizations have more upskilled people to tackle the challenges at hand?’”  

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Bo Dury, Impact Lead at Lepaya

As intentional learning becomes increasingly important, and organizations focus more on its direct impact on business goals, the integration of AI in talent development must also be approached strategically. 

The initial phase of AI hype, when ChatGPT had just emerged and L&D leaders were trying to make sense of it, is over. We are now entering phase two, which is all about exploring how AI can help solve problems. L&D departments must assess the challenges they face and select the appropriate technologies to address them. And impact needs to be at the forefront of every conversation about AI in talent development.

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“Now it’s about separating the wheat from the chaff and using AI to solve specific L&D problems. AI is not an end in itself but a means to an end. And the end for L&D should be business impact.” 

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Dr. Clemens Lechner, Head of Learning Technology & Innovation at Lepaya

The main challenges of implementing AI-powered learning

The potential of AI to transform talent’s skills and careers is huge. But from new tools constantly entering the market to a lack of clarity on how they can actually fit into current workflows, defining an AI implementation strategy is no simple task. 

Insights from our discussion with Lepaya’s Impact Lab participants revealed that, despite a lot of initial resistance, buy-in for AI amongst stakeholders is no longer a big issue for organizations. Instead, other challenges are preventing people leaders from fully embracing the potential of AI. 

Here’s what we learned:

1. Not knowing which tools to start with

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With so many AI tools to choose from and so many theoretical possibilities for application, it can be overwhelming for HR and L&D departments to know where to begin. The question becomes how do you bridge the gap between what’s available and what’s feasible for your organization and its business goals? How do you work backwards from learner impact and decide which tool or method will help?

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“The biggest challenge we have is that a lot of our colleagues don’t know what AI tools are available and what possibilities there are. They are working the old-school way. So it’s about knowing what are the possibilities and what’s the value of them. You want to be innovative but don’t know where to start.”

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Impact Lab participant

2. Lack of clarity on impact that AI can deliver

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Another big question on people leaders’ minds is how do we measure if AI learning initiatives actually work? This feeds into the central question of how to link upskilling to business impact and measuring impact in general. While the experts agree that experimentation will be key, L&D professionals will also need to become skilled at setting targets and designing programs with analytics in mind.

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“There are lots of ways in which we can see AI working, but working backwards from what is impact for a learner, while looking at all possible tools and ways, how do we know which one is helping? That is what I would use to start thinking about the success of these AI tools,”

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Bo Dury, Impact Lead at Lepaya

3. Data privacy concerns

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With some companies blocking AI tools due to data privacy concerns, striking a balance between innovation and safeguarding sensitive personal information will be another big challenge to resolve moving forward. How can organizations ensure robust security measures and transparent policies for data handling? How can they account for issues like bias in AI algorithms and potential unintended consequences to maintain fair and equitable learning environments?

How can AI improve L&D’s impact? It’s time to go beyond content creation

Today, AI is most frequently used to increase efficiency and productivity — more content with fewer resources. But, as our discussion revealed, it’s time for people leaders to look beyond this towards applications that transform learning experiences, analytics, and impact measurement. Applications that go beyond the capabilities of ChatGPT alone.

Personalization is at the heart of this transition with compelling AI use cases for L&D currently falling into three main buckets:

• Personalization with generative AI

Generative AI such as ChatGPT, if used interactively with the learner, can lead to highly individualized learning experiences. Just think of an AI coach that can provide tailored feedback in real time, identifying areas for improvement and suggesting additional exercises to strengthen weak areas.

• Algorithmic/predictive AI 

This type of AI can help deliver the right content to each learner. By inputting a learner’s strengths and weaknesses, goals, language, demographics, and other preferences, organizations can build recommendation engines that give learners exactly what they need given where they are.

• Adaptive learning 

Also based on AI algorithms, this form of personalization leads to the learner getting the right content in the right order during their learner journey. Imagine a learning module that can analyze a learner's performance and preferences to dynamically adjust the learning path and content according to their learning style. This ensures that each individual progresses at their own pace and receives content tailored to their needs.

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“For me, personalization in the field of AI in the context of L&D means that the AI adapts its language and style to me as a user, and I can thus better absorb complex summaries of topics — so AI helps me learn faster through ‘personalization.’”

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Moritz Benjamin Hoffmann, Business Development Manager VIPM at Dell Technologies

Where to start with strategic use of AI in talent development: use this 3-step framework

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Before diving into choosing AI solutions, it’s important to get clear on business goals and align them with talent strategy. Our “AI in L&D Impact Plan” framework is designed to help you make the connection between the two. 

Use this framework to guide discussions with relevant stakeholders, including budget holders, department heads, IT, learners, managers, and other business partners. Once you have mapped out the foundations of your AI learning strategy, creating and tracking impact becomes much easier.

Step 1: Define business goals 

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Before anything else can be done, it’s essential to answer the basic question: what does our organization want to improve? 

This starts with defining business goals and the behavior changes needed to reach those goals. Involve stakeholders to understand the challenges involved with this as well as who needs to be included in the process. 

Next, reflect on what actual actions or processes need to be practiced or learned to drive learning transfer, so that you can ensure the initiatives will have the desired effect in the workplace. The final part of this process — and one not to be overlooked — is collecting data on the business challenge, learning solution, behavior (change), and targeted KPIs. Gathering this data upfront will ultimately allow you to track impact as you begin to design and implement AI learning solutions.

Step 2: Identify AI-powered learning solutions

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Before embarking on the research-intensive process of testing and selecting AI tools, you need to pinpoint the practical ways AI can help your L&D process and which options will be most beneficial for your organization right now. Through the framework, we have defined four main use cases you can use as a starting point:

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• Discover learning needs

‍The brainstorming and research process is an area where AI shines. Use it to help you uncover the learning needs, challenges, and goals of your learners and organization. For example, you can ask ChatGPT to come up with interview questions for stakeholders or to identify potential learning challenges based on data you already have. The focus is on linking these learning needs to business goals.

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“We do a lot of interviews, talk with team leads and ask what their team members need. Then I put my notes in ChatGPT and get an outcome on what are the most pressing learning needs.” ‍

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Impact Lab participant

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• Design learning content

‍When learning needs are clear, you can move into designing the learning materials. AI can help here by creating learning strategies, content, and assets (text, audio, video, etc.). This is currently where most people leaders are using AI right now. The key is to not only use AI to create more content but to use it to create more relevant, high-quality experiences aligned with business strategy. 

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“When looking at using AI to improve L&D, the focus for us isn’t just on content. It’s about training needs from a more holistic point of view, including using it to help with administrative tasks such as writing emails so that us L&D professionals can focus more on creating quality content.” ‍

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Impact Lab participant

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• Deliver learning experiences

‍One of the most exciting areas where AI can help is in creating more dynamic and interactive learning experiences (as detailed above). Think about skills like public speaking or negotiating that can be practiced and improved with an AI coach or how content can be personalized for more engaging experiences relevant to the learner.  

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• Analyze learning processes

‍The potential of using AI for analytics is huge, yet it’s an area that has been largely untapped by learning professionals. AI models have the ability to quickly analyze vast quantities of user data, especially qualitative data, that people leaders may not be able to effectively analyze on their own. Use specific prompts to summarize key takeaways and identify learning patterns and outcomes at scale.

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“We want to measure improvements in the learning journey, not only measure the impact of the training but long-term impact on behavioral change and how AI can have an influence on that.”

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- Impact Lab participant

Step 3: Plan next steps

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With the problem clearly defined and solution options identified, the final step is defining the concrete actions that will help you get the ball rolling. The goal is to keep the first steps small and iterate as you go.

Where to find existing AI tools for L&D

After your AI implementation strategy is mapped out with the framework, it’s time to find the ideal tools for your organization and start experimenting. Discover our sources for the latest AI tech below. 

AI aggregator websites and stores

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• OpenAI GPT Store
• Third-party aggregator websites (not related to the official OpenAI GPT Store):

• There’s an AI for That
• GPT Store

‍Cautionary note: Carefully vet quality and data security of off-the-shelf AI tools. Ensure the tools align with your organization's security and privacy standards.

‍Blogs, newsletters, and social media

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Follow blogs, newsletters, and social media accounts of L&D/AI influencers such as Donald Taylor, Egle Vinauskaite, Ross Stevenson, Donald Clark, or Josh Bersin.

‍Cautionary note: Some content may be paid and not really objective. Beware the hype.

Learn more about upskilling with AI

Want more support figuring out how to best integrate AI into your learning strategy? Check out our People Leaders' Guide for Strategic AI Use.

Plus, stay tuned for our next Impact Labs here.

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