By Mike Vaughan and Markus Bernhardt
Welcome to our Q&A blog, where we dive into the evolving landscape of Learning and Development in the age of artificial intelligence. As questions about the impact of AI on future jobs and workflows loom large, we explore the Thinking Effect approach, envisioning a future where AI relieves us of mundane tasks, and allows us to focus on critical thinking skills.
How is AI affecting future jobs and workflows?
The way we see it here at The Thinking Effect, AI will enter the job market by automating mundane tasks and workflows, especially those activities that have traditionally been labeled for knowledge workers. This will benefit both employees as well as clients in a number of ways. First and foremost, these tasks will be automated and take place instantly, 24/7. Secondly, the AI-supported processes will reduce ‘human error’ in bureaucratic tasks. From a learning and development (L&D) standpoint, AI will enhance the creation of knowledge-based resources and content. This will enable designers to dedicate more time to crafting experiences that cultivate higher cognitive skills such as critical thinking, creativity, and systems thinking. As AI technologies advance, their impact on the job market is expected to grow significantly. However, predicting the specific effects and their sequence remains challenging and largely speculative at this point.
What should L&D, HR, and Talent Leaders be doing right now?
In our view, there has been a lot of interest in AI, and early adopters have been exploring how to use AI tools to accelerate time-consuming tasks, and for ideation.
Organizations have largely adopted a cautious approach, closely observing the evolving landscape and pinpointing potential opportunities. While some have proactively engaged, many are holding off until their 2024 budgets are finalized. Consequently, we anticipate a significant increase in requests for proposals (RFPs), practical applications, and projects. These initiatives are expected to be more strategic in nature, going beyond individuals using standalone tools for isolated tasks.
This implies that organizations will soon start rolling out new business strategies, with communication flowing from top leadership through various departments, teams, and smaller units within the organization. However, the presence of a budget and a vision doesn't automatically guarantee that these efforts at departmental and unit levels will be effective or impactful. In fact, we anticipate many organizations may find themselves grappling with more questions than answers. Therefore, it's crucial to develop a well-defined, actionable, and communicable AI strategy. This strategy should cover everything from ethical considerations to balancing risks and rewards, and the decision-making process regarding the selection and application of tools and use-cases. At The Thinking Effect, we have long advocated for such a strategic approach. For more insights, explore our AI Advocate resources.
If you are interested in getting support to develop your business strategy, be it at the leadership level or within a business department or unit, do contact us for an explorative chat: firstname.lastname@example.org
What recommendations do you have for training programs to learn how to use AI responsibly and effectively? In our experience supporting organizations and teams with AI training and implementing an AI strategy, good facilitation, ideally in person and in small to medium groups works best.
This approach enables teams to create a common language and mutual understanding, constructively discuss concerns and opportunities, and unite around a well-defined AI strategy. A key challenge, however, will be maintaining the relevance of the AI strategy, given the rapid emergence of new tools and breakthroughs.
The AI strategy should be a consensus-driven, clearly communicated, and actionable guide to effectively navigate rapidly evolving technology. It must be tailored to each organization's unique structure, focusing specifically on its product, service, and client strategy.
If you are interested in delivering training within your organization, do feel free to get in touch with us for an explorative chat: email@example.com
What are the fastest-growing and fastest-declining jobs?
We don’t feel like we have the data and global perspective to answer this question, so we recommend checking out resources from McKinsey, IBM, the World Economic Forum, and BCG.
How can AI be used to make their jobs easier? AI tools like predictive text have been part of our devices and applications for some time. Despite significant attention in the past year and the availability of many new generative AI tools (over 400 featured for L&D professionals on The Thinking Effect), their integration into the workforce is just beginning. A notable development is Microsoft's launch of Microsoft Copilot on November 1, an optional feature for enterprise clients within the Office 365 package. The extent and timing of its adoption and visibility in the public sphere are yet to be determined. It is possible that significant uptake may not occur until after 2024 budgets are allocated. However, a major shift is on the horizon: Until now, individuals had to actively seek out AI tools like ChatGPT, signing up for a login or a free trial to experiment on their own. With AI tools becoming integrated into the everyday tools we depend on, we expect a rapid increase in their adoption.
So how will this make jobs easier? We could give you a full overview here, in writing, but we’ve provided the link to Microsoft’s intro video for Copilot above, which we think will give you a much better picture of what is already possible. Just imagine the possibilities when capabilities improve further over the next rounds of releases.
How will AI shape the future of corporate training and learning as a whole?
At The Thinking Effect, we say content is no longer king - experience is.
What we mean is that AI is getting better, and at the moment weekly, at creating and packaging content. We anticipate AI will replace eLearning, micro-learning, personalized and just-in-time learning, knowledge and performance management, and other knowledge-level learning modalities. Therefore, we suggest letting AI do what it is good at and equipping humans to do what we’re good at - creating experiences that develop higher cognitive skills, and with a human touch.