In today's rapidly evolving business landscape, organisations face constant pressure to scale quickly while maintaining operational efficiency and fostering employee development. This challenge is particularly acute for Learning and Development (L&D) professionals tasked with building robust training infrastructures amidst rapid growth and the accelerating pace of technological change, notably with artificial intelligence (AI). A recent Open eLMS discussion delved into these critical issues, featuring insights from Tara, Head of Learning and Organisational Development at an advanced recycling company. She shared her extensive experience, from federal compliance training to building L&D functions and AI governance from the ground up in a fast-scaling enterprise.
The conversation, hosted by Andy Howie, explored the foundational elements required for L&D success, the strategic integration of AI, and how to position learning as a vital growth lever rather than a mere cost centre.
Key Takeaways from the Discussion:
- Governance First: Establishing clear governance and guardrails for L&D systems and AI adoption from the outset is crucial to prevent widespread issues and ensure successful implementation.
- Foundation Matters: Investing in a properly configured Learning Management System (LMS) with correct roles and permissions is essential; retrofitting systems years later in a growing company is significantly more challenging and costly.
- Strategic AI Adoption: While AI offers immense potential, a cautious, safety-first approach with robust governance is vital, particularly for organisations handling intellectual property.
- Human in the Loop: AI outputs must be critically analysed, understood, and owned by human users. Transparency, explainability, and accountability are paramount to prevent misinformation and misuse.
- Impact Over ROI: L&D leaders should focus on demonstrating the tangible impact of training, such as reduced incidents or increased efficiency, to prove its value to leadership.
- Diffusion of Innovation: Leveraging peer-to-peer communication and making new technologies easy to access are key drivers for successful adoption, as highlighted by the Diffusion of Innovation theory.
- Protecting the Company: L&D plays a critical role in protecting organisations from compliance breaches, legal challenges, and reputational damage through effective, well-documented training.
The Foundation of Growth: Governance and LMS Adoption
When companies experience rapid growth, L&D functions are often among the first to encounter strain. Tara highlighted that the initial breakdown typically stems from a lack of governance and planning. Many organisations, eager to implement new tools, bypass the crucial analysis and planning stages, leading to adoption failures rather than technological shortcomings. As she explained, "If it's not rolled out correctly, if you don't plan the governance around it, put the guard rails on and tell people what lane it is and how to use it, that's where it usually breaks."
A common scenario involves the adoption of a Learning Management System (LMS). Tara recounted instances where organisations implemented an LMS based on familiarity rather than strategic need, resulting in systems that were either over-specified or insufficient. The real challenge emerges three to five years down the line, when a company that started with 100 employees scales to 5,000. Fixing a poorly configured LMS at that stage becomes an arduous and expensive task. The host, Andy Howie, echoed this sentiment, emphasising the critical importance of getting the foundations correct from the outset, especially in complex organisational structures.
Tara's pragmatic approach, even when inheriting an existing LMS tied to an HR system, involves working with what is available and planning for future growth. She stressed the importance of considering a company's projected size in three to five years when selecting technology, rather than merely addressing immediate needs. This foresight is crucial, particularly as L&D is often perceived as a cost centre, making initial investment in robust systems a challenge.
Navigating the AI Frontier: Governance and Human Oversight
Tara's current role involves not only building the L&D function but also leading AI governance within her rapidly scaling company. This dual responsibility underscores the growing intersection of L&D and emerging technologies. She identified the development of AI as a significant shift since she joined the company, necessitating a proactive approach to its integration.
The core of her strategy for AI adoption revolves around starting with governance and guardrails. Given her company's work with intellectual property and patented information, a cautious approach is paramount. Rather than prohibiting AI use, which she noted employees would likely do anyway, the focus is on creating a safe environment. "We would rather have them use it in a safe space than not use it," she explained. This involves establishing clear guidelines and educating a broad audience, from highly computer-literate staff to those who may only use computers occasionally.
A notable challenge in this journey, as Tara observed, is securing buy-in as an internal employee compared to the influence a consultant might wield. Consultants, often hired at significant expense, tend to command more immediate attention and adoption of their recommendations. This disparity highlights a unique dynamic L&D leaders face when championing new technologies internally.
The Power of "Human in the Loop"
A central pillar of Tara's AI strategy is the concept of "human in the loop," which she defined in practical, day-to-day terms for her organisation. This isn't merely about using an AI tool; it mandates transparency, explainability, and accountability. Key requirements include:
- Citing AI Usage: Any document created with AI must include a clear citation, even if it is a small note in the footer.
- Transparency and Explainability: Users must understand why the AI generated a particular answer and be able to explain it to others. The response, "that's what the AI gave me," is unacceptable.
- Critical Analysis: Employees are encouraged to question AI outputs, ask for alternatives, and verify information. Tara shared a stark example where AI generated a beautifully formatted list of APA-style references, none of which were real. This underscores the critical need for human scrutiny.
- Ownership of Output: Ultimately, the human user is responsible for the AI's output, requiring them to "own the output" and provide supporting evidence for any recommendations.
This safety-first approach has encountered pushback from "AI cowboys" within the organisation who desire faster, more powerful AI tools. However, Tara maintains a deliberate pace, citing the exponential cost of advanced AI tools and the need to assess actual user adoption before making significant investments. She also highlighted the importance of including dissenting voices, such as an "anti-AI" attorney on the governance committee, to ensure a balanced perspective and reinforce caution, especially concerning sensitive intellectual property.
The Cautionary Tale of AI and the Diffusion of Innovation
Tara's PhD research into the diffusion of innovation theory, particularly how people adopt new e-learning technology, directly informs her approach to AI. She explained that Everett Rogers' theory, which has been relevant since the 1930s, is fundamentally a communication theory. A key variable in predicting adoption is word of mouth from trusted peers.
Applying this, her company launched a nine-month pilot programme, developing "AI Sherpas" – internal champions who could provide trusted, peer-to-peer support. By integrating the third-party AI tool into the company's existing Teams chat functions, accessibility was maximised, making it easier for employees to engage with the technology. This strategy aligns with the theory's premise that making innovation easier to use, coupled with trusted recommendations, significantly boosts adoption.
Tara believes the theory remains highly relevant, even with the advent of instantaneous communication. She hypothesised that the traditional S-curve of adoption, which charts early adopters through to laggards, would now be far tighter and more vertical due to the speed at which information and recommendations spread.
L&D as an Impact Driver, Not a Cost Centre
A critical challenge for L&D leaders is positioning their function as a growth lever rather than a cost line, particularly in fast-scaling environments. Tara advocated for shifting the focus from traditional Return on Investment (ROI) to demonstrating tangible impact. For compliance training, this means showcasing fewer safety incidents or successful audit outcomes. For AI adoption, it means quantifying efficiency gains, such as staff completing tasks 50% faster.
When confronted with the question of what employees would do with the saved 50% of their time, Tara's response was direct and practical: in a growing, often overtaxed company, saved time can be redirected to more complex, strategic tasks. This allows employees to develop new skills and remain valuable, rather than simply doing "dumb stuff" or "easy stuff."
The argument that truly resonates with leadership, she explained, revolves around time savings and, crucially, protection. L&D, through effective compliance and safety training, protects the company from lawsuits, regulatory fines, and reputational damage. As a former federal contractor, Tara knows that in the event of an accident or investigation, training records are among the first items requested. Her advice to L&D leaders is clear: "Stop justifying L&D and prove it. Pick something, pick one thing and go prove it."
Her paramount takeaway for L&D professionals is to approach AI with caution, establishing governance first. It is not merely an IT project. By defining desired outcomes and working backwards, L&D can provide honest, expert advice, ensuring that AI is implemented safely and strategically to drive genuine impact.
Open eLMS understands the complexities of scaling L&D functions and integrating advanced technologies like AI. Our cloud-based Learning Management System (LMS) provides the robust foundations for managing personnel, tracking learning, monitoring skills, and ensuring compliance, all configurable to your organisation's unique needs. Furthermore, the Open eLMS Learning Generator, powered by AI, empowers L&D teams to create custom e-learning courses, videos, podcasts, and gamification in minutes, drastically reducing content creation time and cost.
Discover how Open eLMS can help your organisation build strong L&D foundations and safely leverage AI for transformative learning. Visit https://www.openelms.com to learn more about our LMS and AI-powered Learning Generator.