Generative AI for Business 4 – Unlocking Learning & Development: 5 Target Groups Profiting Most from AI

As this is my field of expertise, this article is a bit longer than previous three articles (1, 2, 3)...yet precise, as I could write a book on how each of the groups below can profit and how they should prepare.

As Generative AI becomes increasingly embedded into organizations, it’s revolutionizing Learning & Development (L&D) strategies across industries. The impacts are far-reaching, providing tangible benefits to specific target groups within the organization. Here, we outline the five key groups that will profit the most from introducing Generative AI in L&D, each gaining unique advantages that transform their approach to work and learning.

1. The C-suite: Driving Organizational ROI and Strategic Alignment

The executive management team stands to gain the most from integrating Generative AI into L&D. For them, it’s about higher ROI, improved KPIs, and the scalability that AI brings at a lower cost. AI-powered L&D allows the organization to:

• Scale learning across regions efficiently, with localized content ensuring consistency in quality and compliance.
• Offer strategic insights, identifying skill gaps, aligning workforce skills with new technologies, and adapting faster to market changes.
• Leverage AI-driven succession planning, ensuring that future leaders are identified and developed early on.

A Korn Ferry study revealed that 82% of senior executives expect AI to have a significant impact on their business within the next 12–24 months. Moreover, 44% of these executives believe employees will need to reskill in the near future to stay relevant .

According to the excellent paper from McKinsey, businesses that harness AI effectively can achieve significant improvements in both productivity and strategic agility. McKinsey also highlights that 70% of companies are expected to adopt some form of AI by 2030, resulting in global economic gains. Importantly, executive teams that adopt AI-led strategies in key areas like talent development and upskilling will see higher ROI and improved organizational resilience

2. HR and Learning Teams: Streamlining Processes and Identifying Skill Gaps

Generative AI simplifies HR and L&D operations by automating administrative tasks, enhancing learner engagement, and providing powerful analytics to identify and close skill gaps. It also allows for:

• Easier management of L&D programs with increased completion rates, as learning paths can be personalized and continuously updated.
• The ability to align skills development programs with business objectives and provide real-time data on employee progress, compliance, and skill acquisition.

An essential step in this transformation is also ensuring HR leaders and business partners are properly trained on how AI can be utilized and how processes can be optimized. Without this foundational knowledge, AI implementation may not reach its full potential.

Additionally, many Human Capital Management (HCM) suites are using AI as a buzzword. It’s crucial to carefully evaluate and test whether these AI-powered features are adequate for the organization’s needs.

Before introducing AI, there must be a dedicated phase of data cleaning, preparation, and facilitation. This requires strong leadership commitment to ensure that data quality and consistency are achieved, as this phase is essential for successful AI integration.

This requires strong leadership commitment to ensure that data quality and consistency are achieved, as this phase is essential for successful AI integration.

3. Blue-Collar Workers: Hands-On Leadership and Practical Training

For blue-collar workers, Generative AI can provide tailored, hands-on training that is closely aligned with their specific job roles. Instead of relying on generic “out-of-the-box” programs, which often feel disconnected from the real challenges they face, AI offers the ability to:

• Tailor leadership development programs to shift leaders, ensuring that training is relevant, practical, and based on real-world scenarios and technologies that workers are already interacting with daily. This allows shift leaders to improve their decision-making, management skills, and team efficiency.
• Localize and continually update content to reflect the actual tools, equipment, and processes used in daily operations, ensuring that training is both timely and relevant. AI can update the training modules in response to feedback and improvements on the shop floor, creating a dynamic learning environment.
• Address diverse language and cultural needs by offering the same content in multiple languages, even within the same location. Given that blue-collar workforces are often diverse, offering training in their preferred language ensures better comprehension and engagement. Generative AI tools like Synthesia can be employed to translate content seamlessly, providing access to training in multiple languages without added complexity.
• Consider when and where the workforce can learn, as access to mobile devices and computers is often limited for blue-collar workers. AI-enhanced training can be integrated into shifts or delivered via offline formats, recognizing that many workers can’t access traditional e-learning platforms while on the job. AI can also offer training at strategic times, reducing the perception that learning is “lazy” or detached from the daily workload. Instead, AI can turn learning into a natural extension of work by embedding it into processes and workflows, ensuring a cultural shift toward valuing continuous improvement.

...reducing the perception that learning is “lazy” or detached from the daily workload.

By personalizing and integrating training with day-to-day processes, Generative AI can bring measurable improvements in safety, quality control, and operational efficiency. Additionally, when workers see that training programs are relevant to their specific challenges and tools, the cultural approval of learning and development as an essential part of work increases.

4. Sales, Product and Program Managers: Accelerating Innovation and Global Reach

For sales, product, and program managers, Generative AI offers a breakthrough in how innovation is distributed and adopted globally. AI streamlines the flow of product knowledge and ensures that teams are well-equipped to sell and support products from day one, regardless of their location.

Real-Time Knowledge Transfer

Today, many product and program managers struggle with ensuring that their knowledge and updates reach all regions effectively and on time. This gap is further complicated by training trainers who are responsible for disseminating the right information. AI can fill these gaps by ensuring instant and real-time updates to training materials and product information, making sure that all regions and sales teams receive the most current information.

By automating the delivery of localized training content, AI tools can distribute updates about new products or features immediately, ensuring that the message and strategy remain consistent across global teams. This allows the sales and product teams to deliver faster, reducing time-to-market and helping the company maintain a competitive edge in an ever-evolving marketplace.

Creating Community Networks for Trainers

AI can create community networks that ensure trainers across various regions are interconnected and always have access to the latest training methodologies and product knowledge. This enhances consistency and quality in how products are promoted and understood globally, across regions and time zones.

The real-time connectivity powered by AI also reduces the need for constant in-person retraining, enabling trainers to receive updates and new learning resources quickly and efficiently. The localization of content ensures that the materials are tailored to specific languages and cultures, making them more accessible and relevant to the workforce.

The localization of content ensures that the materials are tailored to specific languages and cultures, making them more accessible and relevant to the workforce.

Speeding Up Product Adoption and Sales

Sales and product managers benefit significantly from AI’s ability to reduce the lag between product release and understanding across markets. With AI, training programs can be distributed immediately after a product release, ensuring sales teams are prepared to promote and sell without any delays.

This results in faster product adoption, improved sales performance, and enhanced customer satisfaction, as the workforce is better prepared to handle new product features and details. AI-powered feedback loops from sales teams can continuously refine and update learning materials, ensuring that both product and training strategies are optimized for real-world conditions.

An example of this can be seen in Salesforce’s use of AI to provide localized and personalized training for sales teams across different markets. The AI tools also help in collecting real-time feedback from sales interactions, which can be instantly fed back into training programs. This helps create a continuous learning loop where sales teams are constantly updated with the latest product knowledge and market insights, making them more effective in their roles.

5. IT and Data Teams: Enhancing L&D Integration and Driving Digital Transformation

For IT and Data teams, the introduction of Generative AI into Learning and Development is more than just an operational shift—it’s a strategic transformation. Implementing AI-driven L&D platforms requires IT teams to significantly upskill, learning new AI-specific technologies, systems integration, and data management techniques. As AI becomes more integral to business operations, the demand for IT professionals with expertise in AI technologies will grow.

Key Responsibilities for IT and Data Teams:

Upskilling for AI Integration: IT teams must undergo continuous training to stay up-to-date with the rapidly evolving landscape of AI technologies, from understanding machine learning algorithms to deploying AI models in enterprise settings. The integration of AI into L&D systems like Human Capital Management (HCM) suites and Learning Management Systems (LMS) requires familiarity with new software, AI frameworks, and data handling standards.

IT teams must undergo continuous training to stay up-to-date with the rapidly evolving landscape of AI technologies, from understanding machine learning algorithms to deploying AI models in enterprise settings.

• Data Preparation and Cleaning: As highlighted in my previous article Generative AI for Business 2 – Preparing for AI: Data, Processes, and People, the quality and accuracy of data play a crucial role in the success of AI implementation. Data engineers and IT teams must allocate a substantial portion of their time to cleaning, structuring, and validating data before it is fed into AI models. This process often takes up 60-70% of the AI implementation time, but it is essential to ensuring AI models perform optimally and deliver actionable insights.
• Integrating AI with Existing Systems: IT departments are responsible for seamlessly integrating AI-driven L&D platforms with existing business systems, such as HCM and LMS. This integration allows for real-time reporting and analytics, aligning AI-generated learning content with broader organizational goals and metrics. By doing so, IT teams help ensure that AI-generated content not only serves employees but also drives business objectives.
• Automating Routine Tasks: One of the major benefits of AI in IT workflows is its ability to automate routine and repetitive tasks, such as data entry, system monitoring, and report generation. This allows IT staff to shift their focus to more strategic activities, such as enhancing the organization’s digital transformation strategy and ensuring the scalability and compliance of AI-powered systems.

By emphasizing the need for continuous upskilling, as well as the critical nature of data preparation and system integration, IT and Data teams can position themselves as key drivers of digital transformation and long-term organizational success. Generative AI not only lightens the load of routine tasks but also elevates the strategic role of IT in reshaping how organizations approach learning and development.

Mitigating Risks: Data Safety and Workforce Trust

Introducing AI-driven L&D processes comes with its own set of risks. Ensuring the safety of your workforce’s data and maintaining transparency are critical. Organizations must:

• Develop a detailed plan for how data will be handled and secured in AI-driven systems.
• Communicate clearly with employees about AI’s role in the organization to foster trust and reduce concerns about job displacement.

Using trained AI ambassadors from within the workforce to help answer questions, offer training, and gather feedback can smooth the transition and increase acceptance of AI technologies.

According to the Korn Ferry study, 40% of executives feel that a lack of AI-related knowledge within HR teams is a major obstacle to AI integration. Having AI ambassadors can alleviate these concerns by providing personalized support .

Next...

Generative AI’s integration into Learning & Development is transforming how organizations approach training, skill development, and employee engagement. By focusing on these five key target groups—C-suite, HR, blue-collar workers, product managers, and IT teams—organizations can unlock new levels of efficiency, innovation, and growth.

In the next article, we’ll dive into AI’s role in automating routine tasks, including how it enhances operational efficiency across the supply chain, customer service, and beyond.

Stay tuned for more insights on how AI is reshaping Learning & Development as well as business. Feel free to connect with me if you want to discuss Generative AI in Learning further or explore opportunities to bring it into your organization.