Published on November 27, 2023, 6:27 pm
Knowledge workers, employees with technical expertise, and high-level executives alike can benefit from training in generative AI. Companies across industries are recognizing the importance of equipping their employees with the knowledge and skills to effectively use AI tools. For instance, Mercedes-Benz plans to invest over $2.2 billion by 2030 to train its workforce in AI and enhance data skills.
Consulting firms like McKinsey and PwC are also upskilling their employees to become better AI prompters and spot any potential issues or biases in the outputs generated by these systems. Even commercial real estate firm JLL has rolled out an internal generative AI tool for its employees, complete with demos and instructional videos.
However, it’s not just individual contributors who need assistance. High-level executives and other upper management personnel also require support as technology becomes more integrated into workflows. A Freshworks survey revealed that more than 9 in 10 IT leaders and upper management respondents currently use AI on the job, highlighting the widespread adoption of this technology among top executives.
To address the growing interest in generative AI, vendors have released instructional videos and courses specifically targeting skill gaps. Amazon Web Services (AWS) launched a generative AI primer course for executives consisting of five videos covering foundational elements, historical context, and use cases of the technology. This course aims to provide executives with a baseline understanding so they can effectively communicate about generative AI within their organizations.
One key takeaway from AWS’ generative AI primer course is the importance of executive involvement on a practical level. While executives typically handle strategies from a higher level, successful execution of generative AI experiments requires them to engage directly with employees at all levels of an organization. Effective communication is crucial as more than half of workers admit to having “no idea” how their employers utilize AI according to a UKG survey.
By sharing goals and explaining how these goals will be achieved using generative AI, executives can alleviate fears and gain the trust of their employees. Transparency around AI usage can lead to improved workplace culture, with more than half of surveyed employees reporting that they would be happier and go above and beyond in their jobs. Additionally, nearly two-thirds believe it would increase job engagement and satisfaction.
When it comes to the technical aspect of generative AI, hyperscalers like AWS are enhancing their capabilities and infrastructure to handle compute-intensive workloads. Generative AI models require specialized hardware such as graphics processing units (GPUs) or tensor processing units (TPUs), which excel at running parallel workloads necessary for training models with billions of parameters. Companies like Nvidia have positioned themselves as leaders by providing optimized chips for enterprise technology vendors.
Advancements in computing power combined with access to big data have also allowed the fine-tuning of foundation models for a wide range of tasks using ML-optimized Transformer architecture. Such advancements have made specialized learning chips more affordable and accessible, further driving progress in generative AI.
Despite concerns over job displacement, vendors and analysts emphasize that generative AI should be viewed as a tool rather than a replacement for human workers. Existing employees hold valuable knowledge about the company’s processes, people, and systems. Therefore, it is pivotal that organizations provide their employees with the necessary skills to review generated responses for accuracy and bias while also improving their prompter abilities.
Technically skilled employees particularly need training on emerging security risks specific to generative AI and strategies for defending against potential threats. Developing comprehensive policies surrounding acceptable use of generative AI can also guide employees’ responsible utilization of these tools within organizations.
In conclusion, the widespread adoption of generative AI across various industries highlights its growing importance in business operations. While executives must possess a baseline understanding of this technology, continuous training programs are essential to equip all types of employees with the skills needed to leverage generative AI effectively. Through transparent communication, executive involvement, optimized hardware, and policies that promote responsible use, organizations can fully harness the potential of generative AI and ensure its integration into workflows benefits both employees and the company as a whole.