Learning & Development Solutions Get a Boost from Generative AI

Organizations recognize the pivotal role of learning and development (L&D) strategies in fostering growth and innovation. Yet, traditional methods of sourcing and delivering L&D solutions have often been falling short in addressing these evolving needs of the modern workforce.

The Shift Toward Managed Learning Service Providers (MLSPs)

MLSPs are a relatively new but rapidly emerging force in the market. MLSPs are specialized providers that collaborate closely with organizations to analyze learning needs, develop tailored strategies, and implement effective programs to enhance workforce skills and knowledge acquisition.

With their agile expertise, scalable resources, and cost-efficient models, MLSPs are reshaping the way organizations approach L&D, offering a holistic path to skill enhancement and knowledge dissemination.

In fact, the global market for MLSPs is projected to witness a CAGR of 11% over the next decade, reaching a value of $8.7 billion by 2033, accroding to a Persistence Market Research report.

The Growing Interest in Generative AI

Simultaneously, Generative AI (Gen AI), a large language model capable of autonomously generating content, solutions, or insights from patterns and data, is proving to be a potential disruptor in human resources and L&D services as well.

According to a survey by HR research firm i4cp, more 20% of participants cited Gen AI as a priority for the next 12 months, marking a massive leap in interest since its introduction.

Interestingly, a correlation with performance is already manifesting, with more than twice as many participants from market-leading organizations prioritizing spending on Gen AI for L&D uses over the next 12 months, shows the survey.

There is now a growing synergy between MLSP partnerships and the capabilities of Gen AI to help organizations unlock the full potential of their L&D strategies.

The Evolution of L&D Sourcing and the Emergence of MLSPs

Historically, organizations have faced challenges in sourcing and delivering effective L&D solutions, including fragmented vendor landscapes, inconsistent content quality and limited scalability. Navigating this space often comes with the additional difficulty of spend visibility and the presence of various pricing models.

Role of MLSPs

The emergence of MLSPs has changed the L&D landscape by offering integrated solutions that address these pain points. Serving as a one-stop shop, MLSPs provide dedicated help desks and expertise in course and curriculum development.

MLSPs go beyond being mere service providers. They catalyze value in enterprises through:

• Continuous learning enablement, establishing a strong learning culture
• Superior learner experiences, providing high-quality learning outcomes
• Technological integration that enhances end-to-end L&D requirements

By optimizing operational efficiency and managing suppliers effectively, MLSPs can reduce costs, enabling organizations to focus on strategic priorities while ensuring a seamless learning experience for employees.

Overall, the value realization is across three major levers:

• Better planning and scheduling: by avoiding unnecessary outlays for irrelevant programs
• Cost-effective development by minimizing costs for curriculum development
• Efficient learning administration guided by clearly defined workflows

Technological Edge of MLSPs

MLSPs possess a distinct technological edge that sets them apart, especially in the context of AI solutions. With the latest advancements in Generative AI , MLSPs have revolutionized traditional approaches to delivering L&D solutions.

Here are key aspects of the technological edge provided by MLSPs, with specific Gen AI use cases:

• Learning Requirements Mapping

The L&D space has already witnessed AI advancements that have resulted in personalization of learning paths, analysis of learner performance, and tailoring of skill needs with career trajectories.

MLSPs that engage with enterprises deeply are vested with the embedded understanding of organizational needs as well as skill-gap analysis. Armed with these requirements, MLSPs will be able to tap on to Gen AI to identify key concerns that need to be addressed, develop training framework, identify the right mix of incumbent and prospective suppliers, and plan implementation schedules effectively.

• Microlearning Modules

Platforms such as Axonify utilize AI to determine the optimal timing and frequency for delivering microlearning content. By analyzing user engagement patterns and preferences, AI ensures that bite-sized lessons fit seamlessly into employees' daily workflows, catering to shorter attention spans.

• Continuous Learning Culture

AI-driven platforms like Degreed foster a culture of continuous learning by curating relevant content from various sources and providing personalized recommendations. MLSPs also utilize AI to send nudges and reminders, encouraging daily practice and long-term skill development.

• Data Analytics

MLSPs offer robust data analytics capabilities to track and analyze employee learning patterns. AI-powered analytics tools on platforms like Cornerstone OnDemand process vast amounts of learning data to identify trends, predict learning needs, and provide actionable insights. This helps organizations understand learning behaviors, measure training effectiveness, and identify areas for improvement.

• Virtual Reality and Gamification

AI enhances VR training solutions provided by companies like Strivr, dynamically adjusting scenarios based on user performance and feedback. Additionally, AI-driven gamification elements such as points, badges, and leaderboards on platforms like Gamelearn increase engagement and motivation among learners.

• Program Management and Administration

The principal advantage with MLSPs is that they take care of the administrative burden entirely. Gen AI capabilities add a layer of benefit in this regard. Mundane tasks such as updating learning databases, organizing training schedules, and other such administrative responsibilities can be accomplished with the help of Gen AI. This helps the MLSPs focus on the strategic outcomes of the L&D intervention for enterprises efficiently.

• Contracts and Supplier Management

The key differentiator of an MLSP is effective supplier relationship management . Given that L&D contracts and pricing structure – per user, per session, one-time implementation, licensing fee, etc. – are structured differently for different suppliers and requirements, Gen AI offerings help in providing accurate analysis and summary of existing contracts , terms and conditions, supplier KPIs, expiration dates, and more. This helps identify and monitor supplier non-conformance, performance concerns, and enable well-planned sourcing negotiations and potential cost savings.

Unlocking Long-Term L&D Value with Gen AI

Considering its widespread adoption and proven benefits, incorporating Gen AI into your organization's L&D strategy is essential for staying competitive and driving long-term value

• Process Improvements

Gen AI streamlines learning processes, leading to an increase in training efficiency. MLSPs leverage AI-driven algorithms to deliver personalized learning experiences.

• Quantitative Value

The integration of Gen AI in L&D via MLSPs has demonstrated tangible quantitative improvements in learning outcomes. Organizations have witnessed an increase in employee productivity and decrease in time-to-competency for new hires.

• Cost Savings

Organizations utilizing Gen AI in L&D through MLSPs can expect incremental savings in training costs. This is because of automation of administrative tasks that reduce manual intervention and operational overheads.

Conclusion

The integration of Gen AI in L&D through MLSPs offers organizations the opportunity to unlock significant long-term value. Whether through cost savings, process improvements, or enhanced learning outcomes, Gen AI revolutionizes the way organizations approach training and development, paving the way for sustained growth and competitiveness.

Authors: Sonam Sharoff & Giridharan Raghuraman