North Dakota has the potential to become a leader in artificial intelligence (AI). From tech startups to large enterprises to government to education, AI use is burgeoning. However, to become a leader in this space, we need to put aside concerns about AI decreasing jobs and focus on the need for more skilled people.
Investments in data centers, GPUs and other compute resources, as well as in software and supporting capabilities, will be unable to reach their full potential without an adequate level of human resources. This is a significant challenge due to the national (and worldwide) demand for individuals with these skillsets. Developing a pipeline to train these individuals, regionally, is crucial to the success of most AI initiatives that have been or could be proposed. Thus, each initiative would be well served to consider the AI workforce and workforce development as part of its plans.
These workers can be grouped into four categories: AI technology users, technicians, developers and educators. Each has an important role to play in the labor ecosystem and, nationally, they are in high demand.
AI Technology Users
AI technology users integrate AI into their business processes and products. Individuals doing this work must know how to use the AI system and how to get it to perform well. In generative AI, these individuals are commonly called prompt engineers. For other types of AI, they may be called system integrators or go by other titles. The key thing here is that these individuals should have knowledge of both the AI technology and the domain that it will be used in, either on their own or as part of a combined team. While it could be helpful, they don’t necessarily need to know how to install or maintain the AI software, or how to develop new or enhance existing AI systems.
A specialized component of this group is the security staff who deal with securing the operations of AI software, such as implementing protections against undesired data retention and disclosure. These individuals need to know how to use an AI system and how to secure its functionality (although they may not need as much application domain knowledge as others in this category).
Companies looking to implement AI will want to be clear about what they need, so that they don’t pay for potentially more expensive AI technique developers who may be disinterested in integration work and leave. Generally, individuals hired into these user-level positions will have experience in an AI technology that the company plans to use or one very similar to it. Some firms may hire and train these staff members, particularly if they cannot find pre-skilled workers or don’t want to pay the wage levels that these individuals demand.
Technicians
AI technicians are also needed. These are individuals with an information technology (IT) background who can configure the hardware and software needed to operate AI systems. They need to know how the AI system works—and how to install, configure and optimize it—but they don’t need to know how to make it perform from a system design or implementation perspective. These individuals may be IT generalists, who have received specialized training in AI system configuration and operations, or specialized AI technicians. The security staff who protect the hardware, operating system and configuration of the AI software also fall under this category.
Companies should not assume that AI user-category staff will be able to perform technician duties (or vice versa). Those who have only a limited need for technicians (or other AI staff, for that matter) may be well served to hire a consultant with these skills as opposed to trying to find an individual with skills in both areas, as this could result in an unnecessarily expensive hire, issues from the staff member not having sufficient skills in either area (or both areas), or disinterest in the less skilled work, leading to their departure.
This is a key time in the development of AI in the U.S. and worldwide. It’s also a key time for north dakota to claim its place within the ai ecosystem.
AI Developers
AI developers are also essential and often overlooked. Many people confuse the ability to integrate AI or develop prompts to elicit desired capabilities with the ability to build or alter AI systems. While AI developers will likely understand how the technology works enough to be satisfactory prompt engineers, the opposite will typically not be the case. AI developers need computational science and programming skills. These individuals will enhance the performance of existing AI systems and develop new ones. Not only do individuals in this role contribute to having a vibrant AI-technology ecosystem, including firms that are developing new techniques, they are key to having a regional ability to develop or modify systems to be suitable for applications that are not well-served by general-purpose AI technologies. These positions and the educators to prepare students for them will be amongst the most expensive in the AI ecosystem.
Educators
Educators are needed to prepare workers in all AI-related categories. Obviously, these teachers, instructors and professors must have the requisite skillsets and teaching abilities. Because many of these educators could readily take jobs in the non-education workforce at much higher compensation, they may be comparatively expensive to employ compared to other faculty (even as compared to educators in other high-demand fields, such as computer science and engineering). Accordingly, they will be difficult to attract and retain. Educational institutions will need to carefully craft packages of appropriate-level wages, other benefits and intangibles (such as emphasizing the rewards of seeing students succeed) to fill these positions.
With estimates that prompt engineers may earn $200,000 to $300,000 or more a year and some AI jobs offering starting salaries of $800,000,[i] the cost of educators who can prepare people for these positions might cost three to five times (or more) traditional faculty salaries. There may be an additional cost associated with attracting these individuals to the region. For some schools, sharing educators between institutions or using remote instructors may be the only way to fill these critical roles at affordable budget levels.
Positions that combine the ability to conduct research and teaching may be more readily filled than those that are only teaching-focused, due to the flexibility that they offer. Incentives, such as the ability to share in royalties and license fees from technologies developed through research, and flexible policies that not only allow, but promote, startup formation in the region may also prove valuable in attracting talent (in addition to creating new AI business ventures in the state).
The Road Ahead
This is a key time in the development of AI in the U.S. and worldwide. It’s also a key time for North Dakota to claim its place within the AI ecosystem. With AI beginning to impact virtually every facet of society—and poised to have even greater impact in the years ahead—this is not the time to lag or get left behind. The decisions that are made today regarding participation in the burgeoning AI ecosystem will have an impact for decades to come. These decisions will determine our reliance on other regions for technologies. They will drive our industrial, agricultural, educational and other efficiency and competitiveness. They will impact the quality of medical care and just about every other service imaginable.
It is far from an exaggeration to say that AI is changing—and will further change—the world, and the decisions made right now will significantly shape our role in it.
[i] https://www.entrepreneur.com/business-news/chatgpt-experience-can-mean-a-much-higher-salary-report/454811
Jeremy Straub, PhD, is an Assistant Professor in the North Dakota State University Department of Computer Science and a NDSU Challey Institute Faculty Fellow. His research spans a continuum from autonomous technology development to technology commercialization to asking questions of technology-use ethics and national and international policy. He has published more than 60 articles in academic journals and more than 100 peer-reviewed conference papers. Straub serves on multiple editorial boards and conference committees. He is also the lead inventor on two U.S. patents and a member of multiple technical societies.
