While artificial intelligence (AI) is gaining prominence in learning and development (L&D), a noticeable division is beginning to emerge between L&D vendors/consultants and L&D professionals. This division is rooted in differences in mindset, mandates and AI adoption opportunities. Through numerous conversations within the AI and L&D community of practice, it’s evident that a gap in AI skill sets and adoption among L&D professionals will likely accelerate. Unfortunately, this will have a long-term effect on skill acquisition that’s greater than the digital divide in the past. This article will explore the causes, impact and solutions.
The Entrepreneurial Spirit of L&D Vendors and Consultants
L&D vendors and consultants are often known for their entrepreneurial mindset. They have the liberty to playtest and explore the latest AI technologies, and their credibility revolves around staying at the forefront of technology and innovation to provide cutting-edge solutions to their clients.
In this environment, embracing AI is a natural progression. These professionals understand the transformative potential of AI in enhancing training and development programs. They eagerly seek out new tools, conduct experiments and leverage AI’s capabilities to create innovative learning experiences while honing their skills in working alongside AI. The freedom to take risks and experiment with AI technologies is an inherent part of their job.
The Challenges Faced by L&D Practitioners Within Enterprises
On the other side of the spectrum, there are systemic issues that are preventing L&D practitioners within large enterprises to playtest with new technology and develop their digital skills. The nature of their roles demands that their responsibilities encompass the entire lifecycle of organizational learning, from planning and budgeting to implementation. Unlike vendors and consultants, they are not primarily focused on exploring cutting-edge technologies or just one aspect of the lifecycle.
Instead, L&D professionals are often swamped with day-to-day responsibilities, leaving them with limited time to delve into AI exploration. Furthermore, the use of AI tools in many enterprise settings is tightly restricted, and individuals who venture outside these boundaries may face reprimands. The fear of making mistakes and the absence of a trial-and-error culture can stifle their willingness to embrace AI.
Their mindset is generally risk-averse when it comes to adopting new technologies, especially when these technologies are not explicitly required in their roles. The pressures of time and the ingrained routines can make AI adoption seem like an additional burden rather than an opportunity.
A Culminating Skills Void
The impact of vendors and consultants being proactively allowed to innovate, while those within enterprise settings are limited by restrictions, is the emergence of a notable gap in skill sets among L&D professionals. The divide is exacerbated by the added restrictions placed on AI use within organizations as it becomes difficult for L&D leaders to upskill their own team and support digital adoption of AI technology.
However, this divide between “outside vs. inside” technology is not unique to L&D. In contrast, various industries outside the L&D realm, like marketing, adopt a “test and learn” approach. They recognize the importance of staying competitive by harnessing new technology. Enterprise L&D teams can take inspiration from these industries and adopt a similar mindset.
The Time for Change
Because the pace of the AI revolution is faster than prior technologies, there’s a compelling need for organizations to act now to mitigate a potential skill gap and be knowledgeable in technology-fueled vendor conversations. To do so, they can take several key steps:
1. Cultivate a culture of innovation. Encourage a culture of innovation within the L&D department. Create safe spaces for practitioners to explore AI and experiment with new tools without the fear of repercussions. This could be with enterprise-approved AI tools, but the key is to still provide some tools vs. cutting off all AI-enabled tools.
2. Provide learning support. Offer support for L&D practitioners to upskill in AI technologies. Equip them with the knowledge and confidence to embrace AI in their roles. This could be through free internal or external communities of practice, access to mentors, curated learning paths.
3. Collaborate with vendors. Foster closer collaboration between L&D vendors/consultants and practitioners within enterprises. Vendors can provide valuable insights and guidance, helping practitioners make informed decisions about AI adoption.
4. Set clear objectives. Define clear objectives for AI adoption within the team or organization. Ensure that AI initiatives align with the broader goals of the enterprise and are not perceived as additional tasks.
5. Measure impact. Implement mechanisms to measure the impact of AI on L&D initiatives. Demonstrating the tangible benefits of AI adoption can help overcome resistance.
Conclusion
The growing divide in AI adoption between L&D vendors/consultants and practitioners within enterprises is a challenge that can be addressed to decrease the digital adoption skill gap. By fostering a culture of innovation, providing support and training and promoting collaboration, L&D in enterprises can close this gap.
It’s time to embrace AI as a tool for enhancing training and development, ensuring that organizations stay competitive in an increasingly digital world. The rapid AI-fueled revolution is upon us, and it’s crucial that we adapt to prevent the growing skill gap between agencies and enterprises from becoming insurmountable.
