From training to human-machine skills architectures and neural interfaces
Our understanding of continuing professional development (CPD) has changed fundamentally over the past five decades, as have the requirements for organizations, managers and learners. Traditional CPD, which focused primarily on maintaining employees’ ability to perform their function and on upskilling, has evolved into a core strategic HR instrument: human resource development. Professor Dr. Mario Vaupel of the Steinbeis University – Schools of Next Practices GmbH sums up the key stages in this evolution and discusses likely future developments.
From traditional CPD to co-learning with AI
Enterprises started seeing CPD as an intrinsic part of integrated HR development strategies as long ago as the 1970s and 1980s. This shift in perspective was closely tied to major social and economic changes such as the transition from an industrial to a knowledge society, the growing importance of knowledge work, and the ever faster pace of technological change. The traditional approach to imparting knowledge – often in the form of seminars and classroom training – was no longer enough for HR development to keep pace with the new requirements.
Stage 1: From training to skills and talent development
Instead, the focus shifted towards the development of the person as a whole and their cultural alignment with the organization. Since the 1990s, the libraries of HR and organizational development experts have filled up with numerous methods and tools for promoting personal development, reflective thinking and independent learning skills.
A further shift started to occur during the 2000s. Digitalization, global competition for highly-skilled workers and demographic change resulted in CPD becoming more personalized and acquiring a more strategic focus. The more general concept of HR development evolved into talent management, an approach that tends to be specifically aimed at identifying, developing and retaining key individuals in the organization (see Cappelli, 2008; Collings & Mellahi, 2009). HR development was now focused on specific potential of high strategic value. Companies like General Electric, IBM and SAP developed systematic talent pipelines based on performance and potential analysis. Digital learning platforms were used alongside the talent pipeline to also ensure a broad spread of development topics in the organization.
These changes in organizational training during the 2000s formed part of the transition to current CPD trends while at the same time marking the start of the next shift from talent development to strategic skills architectures and co-learning with AI.
STAGE 2: From talent development to future skills
The dynamic development of the post-industrial knowledge economy calls for a new approach to learning where rigid occupational roles and linear career paths are replaced by agility, creativity and decision-making skills. At the same time, the labor market is also undergoing major changes: routine tasks are being automated, and there is more demand for complex cognitive and social skills – “21st century skills” like critical thinking, collaboration and digital literacy (World Economic Forum, 2023).
In this context, talent management alone is no longer enough. Instead, CPD should be seen as a dynamic skills management process that is constantly responding to change. Companies like Google and Siemens have been using the term “capability frameworks” for some time. These are continuously updated and incorporated into a feedback loop with strategic business models. The focus is no longer on identifying people with talent but on identifying the skills needed by the ecosystem today, tomorrow and in the longer term.
As well as requiring different tools, this new approach calls for a change in mindset where learning becomes part of the value chain. It is no longer just a means of adapting to change but – in keeping with the spirit of the founder of modern management, Peter Drucker – a requirement for innovation and future viability.
STAGE 3: From skills development to co-learning and co-working with AI
As with many other fields, artificial intelligence (AI) is set to bring far-reaching changes to HR development. In the future, lengthy training cycles, standardized learning paths and generic skills models will increasingly be replaced by data-driven, adaptive, context-intelligent systems. There are sound academic grounds to predict the following new professional development structures in years to come:
2025 – 2028: On-demand skill learning through personalized learning analytics
The incorporation of learning analytics, natural language processing and recommender systems enables ever greater fine-tuning of individual learning pathways. Within the organizational learning landscape, AI systems will increasingly analyze employees’ skill sets, usage patterns and performance data and suggest and provide appropriate learning modules or microlearning content aligned with the requirements of their role and the corporate goals, all in real time.
Recent studies indicate that platforms like Degreed, EdCast and IBM Watson Talent Frameworks are already developing adaptive learning paths based on semantic skills analysis (see McKinsey & Company, 2024; IBM, 2023). And in the field, companies such as SAP, PwC and Siemens are piloting AI-powered skills engines that, as well as making recommendations, are also able to predict development potential (see World Economic Forum, 2023; Siemens AG, Corporate Learning Report 2024).
Against this backdrop, the role of HR development is shifting away from the creation of learning content and towards the orchestration of AI-powered skills ecosystems (see Erpenbeck & Sauter, 2022).
2028 – 2032: Workflow integration of AI coaches
The next stage will see the widespread, seamless integration of intelligent performance coaches in the digital workplace. These agents observe operations context-sensitively and offer proactive support, just-in-time feedback and in-depth learning resources without interrupting the workflow.
Initial pilot projects with AI-powered assistance systems (at companies like Bosch, Fujitsu and Accenture) are demonstrating how learning support can be directly embedded in the digital workflow (see Deloitte Human Capital Trends, 2024). Platforms like Microsoft’s Copilot for Office 365 and Salesforce Einstein are among the first to offer “embedded learning agent” applications.
Increasingly, HR development is acting as the operator of a pervasive learning infrastructure where there is no longer any distinction between learning and the work process. The traditional training model (“train first, perform later”) is being replaced by a continuous performative learning approach (see Ifenthaler et al., 2023).
2033 – 2040: HUMAN-MACHINE SKILLS ARCHITECTURES AND NEURAL INTERFACES
“Human capability operating systems” are expected to start appearing from around 2033. Rather than simply orchestrating individual learning, these systems actively manage the transfer, combination and, where relevant, “outsourcing” of skills between humans and machines. AI agents won’t just support learning processes – they will actively co-develop skills models using real-time data from across the entire organization (see OECD AI in Education Initiative, 2024; European Commission, Human-Centric AI White Paper, 2023).
Developments in the fields of neural interfaces and brain-computer interfaces (BCIs) are also gathering pace. Companies like Neuralink (Musk), NextMind (Snap Inc.) and Kernel (USA) are already working on two-way interfaces that will eventually also influence learning processes (see R. Kurzweil, 2025). As Mario Vaupel concludes, “While these technologies are currently still experimental, the direct ‘installation’ or ‘outsourcing’ of skills could potentially become a reality from 2035 on – with as yet unknown ethical, social and organizational implications”.