“My company won’t let me …”
How many times has this been your answer to a question about artificial intelligence (AI) within your training function? Since the release of ChatGPT in November 2022, AI has become the most talked-about topic in the field. It took over the top spot in this year’s L&D Global Sentiment Survey. It’s dominating conference agendas, industry publications and webinar schedules. Technology providers across learning and development (L&D) and human resources (HR) are slapping “Now with AI!” on their landing pages and expo booths.
The hype is clearly real. But what about workplace reality? After all, thought leadership doesn’t have to deal with red tape, information technology (IT) regulations or corporate politics. AI has been an integral part of the learning technology ecosystem for years. Live captioning, content tagging and course recommendations are common AI-powered capabilities. Generative AI has triggered a heightened level of corporate tech scrutiny due to concerns around data security, information accuracy and ethical practices.
It doesn’t matter if you’re in retail, finance or health care. Every business is trying to figure out how to gain value from AI. Generative AI spending is expected to double to $151 billion this year. While we still have more questions than answers, L&D is already at risk of falling behind when it comes to strategic planning. Eighty-nine percent of executives rank AI as a top tech priority for 2024, while only 1 in 5 L&D professionals consider it of similar importance. Unfortunately, this isn’t the first time we’ve been behind the curve with new technology. We’ve seen this movie before … a few times.
Dealing With Digital Déjà Vu
AI represents the next great shift in how we live and work through technology. It’s being compared to fire and electricity in terms of societal impact. Even more subdued estimates put this digital transformation on the same scale as the internet in the late 1900s. AI is quickly becoming how technology works.
What can L&D learn from past paradigm shifts, such as the internet, mobile technology and social media, to inform our approach to AI? Historically, L&D tends to lag behind the change, but this isn’t always our fault. For example, L&D cannot unilaterally decide to roll out a mobile device policy. There are rules we must follow when it comes to enterprise technology. Nonetheless, the original iPhone dropped 17 years ago, yet plenty of organizations are still trying to figure out where mobile devices fit in their learning strategies.
According to one study, 26% of organizations have AI policies in place while another 23% are actively working on them. Meanwhile, more than half of knowledge workers are already using GenAI weekly. Institutional thinking cannot keep pace with technological innovation.
If L&D waits for things to settle down, we’ll lose our “seat at the table” regarding the role L&D will play in the AI-enabled workplace. Rather than having the time to reimagine our practices through AI, we’ll end up doing something like sticking the classroom online and calling it “eLearning.” L&D may not make the rules, but we can control how we prepare for digital transformation.
3 Steps to Prepare Every L&D Team For the Impact of AI
1. Find out how work is changing.
Deploying new tech should not be L&D’s top AI priority. We need to keep a close eye on the tech marketplace and make time to experiment with new tools. However, if we just focus on the technology and how we can apply it today, our AI-enabled future will be subject to the whims of our organization. We may be stuck waiting for months (or years) while IT, HR, legal and compliance catch up. Meanwhile, stakeholders and employees will find their own ways to circumvent these roadblocks and leverage AI to improve their practices.
Instead, L&D must figure out how AI will change the workplace over the next few years. We must collaborate with operational stakeholders to determine what work will be prioritized and how that work will be done. For example, an organization that has adopted a “do more with less” mantra may look at AI as a timely opportunity to boost productivity while reducing costs and increasing profitability.
Logically, this may result in headcount reductions. Thirty-seven percent of companies using AI say technology has already replaced workers. L&D needs to know what our audience will look like moving forward. We must also understand their shifting knowledge and skill requirements. If AI is used to handle basic tasks, L&D may need to adjust our strategy to handle more complex learning requirements.
L&D risks missing the mark as we evolve our own processes if we don’t first investigate how AI is changing the everyday work experience.
2. Scrutinize your data practices.
Many organizations have deployed their own generative AI assistants or are experimenting with third-party platforms. Providing every employee with a super-intelligent digital co-worker who can solve common problems and automate repetitive tasks is pretty much a no-brainer. Plus, this concept aligns with common L&D practices like coaching and performance support. But where does L&D fit within this kind of enterprise AI application, especially when the technology is developed and managed by another team?
L&D is sitting on a mountain of data. We track people’s knowledge, skills and credentials. We have catalogs of rigorously reviewed training materials. We know what every function and role in the company needs to know. Today, the utility of this data is limited to our own walled garden. People need to visit the learning management system (LMS) to find the value.
In an AI-enabled workplace, we can leverage L&D resources in new ways to deliver value across the workplace ecosystem. Imagine providing employees with instant guidance for solving complex problems by using information contained within existing learning objects, without requiring anyone to complete a course. AI can do this today – but only if it has access to the right data.
L&D must take a hard look at what we measure, how we store data and how we integrate our resources with enterprise systems beyond the L&D tech stack.
3. Assess your willingness to change.
Can we let go? This is the most important question L&D must answer as we prepare for the impact of AI. Are we willing to rethink the value of L&D within our organizations? And are we willing to adapt what we do and how we do it to deliver value in new ways? AI is already changing how work gets done. It will also change how that work must be supported. As these decisions are being made around us, L&D must embrace our own shift in purpose.
L&D will still build courses. We’ll still architect learning programs. We’ll still be the go-to resource for complex skill development. Yet, every stakeholder will have access to the same AI-powered tools. They’ll be able to build courses with a few clicks. They’ll be able to send automated nudges and provide performance support via digital assistants. L&D can wrap our arms tightly around the stuff we own and try to maintain our current value proposition. Or we can lean into the change and leverage our expertise to enable an AI-powered learning ecosystem that provides the type of support experience employees need (and deserve).
L&D is the center of excellence when it comes to learning and performance. AI will present new opportunities to apply our expertise — without always being directly involved in the solution.
Thinking Beyond the Technology
AI is moving too fast. Every day there’s a new model or application or integration. Some of these tools, like automated translations, content generation platforms and adaptive learning systems, can provide immediate value to resource-constrained L&D teams. Conversely, if L&D gets too focused on using AI to improve our current practices, we may miss the larger picture as the organization rapidly evolves around us.
L&D should not break the rules. We shouldn’t use unapproved technology. We shouldn’t insert proprietary information into unvalidated systems. We shouldn’t use new software features without fully understanding how they work, even if they’re from trusted vendors. Still, we can’t allow the rules (or lack thereof) to stop us from preparing for the next wave of digital transformation. Otherwise, our stakeholders will make decisions regarding the future of L&D without us.
The key to L&D’s digital transformation isn’t technology. It’s the insight, capability and willingness to proactively evolve our role before technology forces our hand. This is how we make sure AI is a change we participate in rather than one that happens to us.
