Approaching Professional Reskilling Like We Approach Technology Transfer in Universities
I explore how universities learned to take ideas developed by their faculty and turn them into valued products and services, something often called technology transfer, and suggest that similar principles might guide entrepreneurial development of professional reskilling opportunities.[1]
The ongoing industrial revolution, driven by the rapid advancement of generative artificial intelligence, places a significant responsibility on universities to actively engage in professional reskilling. Similar to historical phases of industrial change, the middle class workforce faces displacement and potential replacement by intelligent machines. History warns us that this disruption of people accustomed to a good life and future expectations can lead to substantial social upheaval. Universities are often the breeding grounds for advances in AI, thus providing the potential to equip professional workers with skills that complement and expand upon the capabilities of intelligent machines. However, this can only be achieved if universities adapt and become more flexible in creating learning opportunities tailored to the needs of professionals facing career upheaval.
In a recent essay,[2] my colleague Michael Bridges and I explored the role universities can play in this transformation and why it is imperative for them to do so. Simply put, there are no other public educational institutions capable of fulfilling the necessary requirements. While community colleges have traditionally been the primary source for reskilling, the current pace of change demands a more dynamic response. Neither the entrenched workforce of community colleges nor experts borrowed from the business world can adequately handle the entire training load. Universities possess a wide range of faculty and advanced student expertise essential for navigating the era of intelligent information systems. Furthermore, universities must strike a balance between efficiently delivering large-scale learning opportunities and supporting advanced scholarship to remain financially viable. Given changing demographics, integrating cost-effective professional reskilling modules into their offerings greatly benefits their fiscal sustainability.
Entering the realm of professional reskilling requires universities to embrace agility and an outward focus, which can be challenging for institutions accustomed to more traditional roles. Many university schools and colleges have attempted this transformation but have often fallen short in terms of speed, focus on emergent professional needs, and efficiency. To address these challenges, universities should consider establishing separate units dedicated to translating their scholarly and instructional strengths into entrepreneurial endeavors. These units should be willing to take risks and foster aggressive partnerships with the business and industry sectors to deliver efficient professional reskilling opportunities, much like the technology transfer units that leverage intellectual property for startups and licensees. This essay explores this strategic option in depth.
Given that many universities have experience with technology transfer initiatives, we can draw on these experiences to outline key elements of a successful university tech transfer program (Table 1). These strategy elements can be adapted to create an effective university strategy for contributing to the growing demand for large-scale yet personalized professional reskilling. Below, we examine each of these elements, sometimes grouping them together, while making necessary adjustments to better align with the realm of teaching rather than research.
Specialized Units for Professional Reskilling in Universities
Just like universities have special offices to turn research into profitable ventures, there is a need for separate units focused on professional retraining. Mike Bridges and I discussed this in a previous article (see Footnote 1). Traditional university programs take years to develop, but the job market is changing rapidly. We need a way to create efficient new training programs quickly to help people stay employable.
The Challenge of agility. Universities are great at long-term education but are still figuring out how to offer quick and efficient retraining programs. To meet the fast-paced demands of the job market without losing money, universities need to be agile. This might include setting tuition fees based on market demand, offering free trial courses to attract new students, and being open to occasional failures. A separate unit within the university would be better equipped to handle these challenges.
The challenge and opportunity of cost management. Managing costs is a significant hurdle when introducing new courses in a university. Faculty members are usually fully committed and prefer to minimize new responsibilities to focus on research. Online courses, for instance, often cost more than their on-campus counterparts. This is because they require additional resources for development, and there is a lack of established best practices for automation.
In contrast, a specialized unit for professional reskilling could more freely explore automated learning solutions. These could potentially be more cost-effective, as expenses would not necessarily increase with the number of enrollees. Finding ways to control instructional costs is not a straightforward task for the academic units of a university; a freestanding unit might be better able to try more efficient approaches.
What do businesses do? Large corporations often have similar independent units to drive innovation. Some companies have committees to review innovative ideas, while others have set up their own venture capital arms to operate separately from the main organization. When it comes to research, some external funding agencies offer grants that allow faculty to act as research entrepreneurs. However, universities still rely on specialized units to turn research into commercial products. Such units also are needed for professional re-education and retraining.
The stigma of educational entrepreneurship. In research-focused universities, writing textbooks or developing new courses is often seen as less prestigious than publishing research. A dedicated professional reskilling unit could take on this work without affecting the university’s top researchers, who are more focused on publishable studies.
In summary, an independent unit for professional retraining could offer the agility and focus needed to quickly respond to the changing demands of the job market.
Incubators, Accelerators, and Accepting the Need for Some Failures
The rapid advancement of intelligent systems is unprecedented, and it is crucial for society that universities take a more proactive role in preparing the existing workforce for the disruption this will catalyze. However, the changing landscape of job distribution between humans and machines requires more adaptable strategies to harness emerging technologies effectively than are prevalent in normal university operations. While it is unlikely that a single entity can meet the immense demand for reskilling opportunities, there are compelling reasons to favor alternative approaches such as incubators, accelerators, and other schemes that encourage experimentation. The key is to respond rapidly and in tailored form to a reskilling need and to be ready, if efforts fail, to let them fail quickly without causing significant harm.
Innovative ideas require a balance of protection and encouragement. Initial endeavors are often experimental and demand frequent restarts and quick adaptations. Those responsible for developing reskilling programs need protection from the prevailing elitism in research universities. To give ideas for effective reskilling programs a genuine chance of success, they should be nurtured in an environment that embraces failure as an integral part of the learning process.
Developing new capabilities also demands resources. Since resources are usually limited, research universities and federal granting agencies tend to invest minimally in ideas until they are well-established, reducing the risk of failure. Entrepreneurial efforts to provide learning opportunities for professionals in need of new knowledge and skills require a more evolutionary approach. This approach involves quick trials of various methods, acceptance of failure, and rapid learning from those failures. This contrasts with the conventional research funding culture and the slow development of new degree programs.
While some universities, including my own, already engage in incubating new teaching methods and making small investments to drive change, these efforts fall short of the scale required for reskilling demands. Additionally, the pace of these initiatives is often insufficient. Furthermore, there is still a prevalent culture that discourages faculty from embracing failure and making significant investments in new teaching ideas. Just as our country benefits from both a conservative NIH and an entrepreneurial DARPA, universities should maintain their existing approaches to major degree and certificate programs while simultaneously establishing units dedicated to incubating reskilling initiatives and rapidly scaling those that prove effective.
Interdisciplinarity
Universities aspire to foster interdisciplinary collaboration, but often remain divided along disciplinary lines. Each field maintains its distinct research methodologies and standards for valid knowledge. This fragmentation is exacerbated by budget models that push each department to achieve financial self-sufficiency, discouraging interdepartmental collaboration. Conversely, modern professions are increasingly embracing interdisciplinary approaches. Reskilling programs now demand a fusion of knowledge from diverse domains, particularly as AI systems become deeply integrated into professional tasks.
For instance, in the field of medicine, AI is transforming diagnostics. Physicians must grasp how to use these systems effectively and when to rely on their findings. While medical schools offer comprehensive education, the rapidly evolving landscape necessitates ongoing learning, especially regarding the integration of AI systems and collaborative practice.
Similarly, educators are grappling with new challenges as AI tools gain prominence in education. Just last year, students may not have been acquainted with using AI for research or essay writing. Today, instructors are navigating the intricacies of teaching these skills effectively, ensuring students derive genuine educational value.
Furthermore, professors themselves must adapt by acquiring competencies that extend beyond their academic specialties. This includes a comprehension of psychology, sociology, marketing, and the inner workings of AI systems. They must also anticipate swift technological advancements and acknowledge that, occasionally, their students might grasp new learning-enhancement tools faster than they do.
Preparing for an unpredictable future is essential. The pace of AI system improvement is so rapid that what was ineffective just a few months ago may now prove highly valuable. Therefore, a significant challenge in creating new learning opportunities lies in preparing individuals for an ever-changing landscape. Faculty members excel when they establish partnerships with their students, enabling professors to understand students’ learning needs and guide their access to educational resources. Occasionally, students may inquire why a new tool is not employed to enhance their learning experience. Universities must help faculty to respond positively when this happens.
In summary, both academia and the professional sphere are transitioning towards interdisciplinary paradigms. This transformation necessitates novel modes of thinking and collaboration, especially given the increasing integration of AI systems across various domains.
Flexible Staffing of New Learning Opportunities
In the realm of technology transfer, it is uncommon for the original researcher who conceived a novel idea to lead all of its transformation into a product or service. One prevalent scenario involves the “inventor” assuming the role of chief technology officer, offering expertise but not spearheading the development and delivery of the product or service. In fact, many technology transfer endeavors falter when the researcher insists on retaining excessive control. Another common pattern entails entrepreneurs discovering the potential of a new product or service and subsequently collaborating with a researcher to exploit their innovation. In these cases as well, the researcher typically provides advisory support while others manage the development and marketing of the newfound discovery.
Similarly, in numerous instances where a professor’s profound knowledge is critical to shaping a new reskilling opportunity, these patterns may apply. Often, the demand for such opportunities arises first from business leaders or entrepreneurs. In these scenarios, universities can make a substantial impact by swiftly responding to these needs. To respond promptly, they must enlist instructional designers and potentially adjunct professionals from the industry to construct the learning opportunity. Simultaneously, they can harness faculty expertise, provided it can be accessed swiftly and aligns with the external learning requirements. If a business confronts the choice between an immediate reskilling opportunity for its employees and potential job terminations, universities are not helpful if their response is that the required professor is currently on sabbatical, has committed to research project completion, or is already scheduled to teach other courses.
Just as it entails expenses to staff degree-program courses with top researchers, there will also be associated costs in attracting premier instructional designers. These individuals should possess the capacity to swiftly grasp the knowledge and skills required for teaching and to design efficient and engaging learning experiences to impart new capabilities. Universities may find it advantageous to cultivate some of this needed talent internally through their own instructional design degree and certificate programs. The demand for such talent is substantial, with much of it originating from the business world, which often outcompetes university HR systems in recruitment. Consequently, universities must be open to flexibility regarding compensation levels when attracting, hiring, and retaining the best talent for their professional reskilling units, even if their core academic units must operate on more restrictive rules.
Robust Assessment
Professors in research universities wield significant control over the assessment of their courses, sometimes to the extent of blocking external access to information about the effectiveness of their teaching. In contrast, to thrive in the professional reskilling arena, universities must establish robust assessment programs for continuous improvement and often require independent data to market the real-world impact of their learning offerings effectively.
Ideally, the assessment strategy for a new educational offering should commence with the university reaching a consensus with relevant external bodies regarding the intended learning outcomes. In some instances, it is straightforward to create assessments for these outcomes. For instance, “stealth assessment” technology[3] can be integrated into simulated work environments to gauge a person’s performance within them. In other cases, alternative assessment methods may be necessary, such as performance evaluation based on predefined criteria in actual situations rather than simulations. Sometimes, the outcomes may involve measuring changes in learner-generated results, like assessing the impact of emergency medical technician training through shifts in patient survival rates or complication rates before and after training.
Given the imperative that learning should lead to quantifiable performance improvements, it is crucial to design assessments early in the process, even before designing the learning opportunity itself. This not only provides clearer objectives for the learning opportunity but also enables the creation of tailored marketing strategies concurrent with its development.
This perspective on assessment differs significantly from that of degree programs, where measures of student satisfaction and readiness for subsequent courses guide the process, as opposed to external outcomes. Nevertheless, it parallels how technology transfer efforts and innovations such as new medical treatments are assessed. It is indispensable to a targeted initiative aimed at assisting displaced workers and the enterprises in which they are or will be employed.
Intellectual Property, Licensing, and Delivery Partnerships
In the realm of professional reskilling, universities have a unique opportunity to forge impactful partnerships, much like they do in technology transfer. Consider, for instance, a university that develops a cybersecurity training course tailored for accountants adapting to roles that leverage intelligent systems. Initially, this course could blend online learning with periodic in-person weekend sessions. If successful, the course could attract significant demand from corporations seeking a comprehensive online training package for internal use. Additionally, there may be a market for a customizable version of this course to meet the specific needs of individual businesses.
However, the marketing and customization of such a course may diverge from the university’s core competencies and objectives. Sometimes, outsourcing these aspects to an external entity may be more practical. This mirrors the challenges encountered in technology transfer, particularly in the management of intellectual property. Fortunately, universities have amassed considerable expertise in navigating these complexities and can often leverage existing legal resources to manage both technology and course transfers efficiently.
When it comes to course customization, additional considerations come into play. Drawing from experience, I recall a research contract for which I was the lead researcher, with Intel Corporation. In writing the contract, we reached an impasse over intellectual property rights, with my university and the company each wanting to own everything. The deadlock was broken by delineating the ownership of distinct aspects of the project, separating teaching methods and content knowledge the university brought to the effort from proprietary and company-specific content. A similar approach could be applied to course customization, where the core content remains the property of the university’s professional reskilling unit, and any additional content requested by a specific firm belongs to that firm.
Another critical aspect to consider is faculty “ownership” of course content. While legal clarity may be lacking, academic tradition affords professors considerable rights over the courses they develop. These rights serve to uphold academic freedom and allow faculty to repurpose course content for research publications and other scholarly activities. However, there are limitations. For example, a professor cannot sell a course to another institution to be offered under that college’s name. In the context of professional reskilling units, if they operate separately from the university’s core academic divisions, it may be appropriate to designate the courses as “works for hire,” thereby making them university property. Exceptions could be made when a course incorporates existing content from a regular academic course, in which case the original professor’s rights should be preserved under a non-exclusive license agreement.
Navigating the intricacies of intellectual property will require a collaborative approach, involving substantial faculty input and aligning with established university procedures. While this process may be complex, it is certainly feasible, as evidenced by the successes in the technology transfer sector.
Collaborations
At an abstract general level, universities pay close attention to input from representatives of the business world, government, and the general public. However, the journey from external input to course development is often indirect and filled with noise. Typically, when there’s demand for a new academic program, universities tend to take existing courses that seem somewhat related and repackage them, occasionally adding a course or two. This approach can be effective for undergraduate education and professional programs in fields with various entry pathways. However, it falls short when new professional roles emerge due to changes in what intelligent machines are capable of. Professionals, particularly those displaced by emerging technology, require highly specific reskilling to fit into newly available positions. Moreover, these displaced professionals often cannot afford lengthy and costly programs; they need to acquire the skills that will help them find new employment or retain their current jobs, and they need this to happen swiftly.
For these reasons, a university’s professional reskilling unit should establish a robust system for actively listening to the needs of the business world, government, and professionals seeking new learning opportunities. This entails a mix of standard marketing practices such as surveys, focus groups, and websites where potential students can express their requirements. Additionally, it involves continuous monitoring of the impact of intelligent systems on the job market.
Companies like McKinsey[4] and organizations such as the OECD, Brookings, and others regularly publish valuable insights regarding which sectors of the economy will witness significant shifts from human labor to automation. A professional reskilling unit should stay informed about these analyses, identify the needs that it is well-positioned to address, and seek substantial input from experts in areas where displaced professionals are likely to require new skills.
Often, this listening process will extend to forming partnerships with one or more enterprises to develop and implement the training and education necessary to prepare professional workers for their evolving roles. In some cases, companies may want to create their tailored programs. This can serve as a source of revenue and also facilitate the development of reusable programs that can be adapted to serve other enterprises with ease. To make this work, universities must combine their expertise with that of potential employers of their professional learning students and strategically plan how to maximize the value of their investments in new learning opportunities.
Recently, I have been involved as a consultant in a project aimed at developing intelligent training systems for power grid operators. The increased pressures on the grid, partly due to climate change, coupled with the rapid expansion of microgrids, have created a heightened demand for skilled operators. The team I have been collaborating with includes university researchers and private companies specializing in simulations, training systems, and even eye movement tracking technology, along with experts from various power companies. Each contributor brings essential knowledge to the project, and its success hinges on the synergy of these diverse expertises. Without some of these elements, the team might still produce a training system suitable for one power company or one type of grid. However, by combining all these elements, the training can encompass not only the fundamentals of grid maintenance (which only needs to be embedded in the training system once) but also region-specific knowledge and insights into company policies governing resource allocation, which can be quickly changed to serve new utility companies desiring the training. This allows the resulting training opportunity to be both tailored and efficiently produced.
In essence, merely listening to various experts can help develop a system that breaks even in terms of costs and returns. Yet, deeper listening and a strategic approach to designing a system with a reusable core that can adapt to different enterprise scenarios can potentially yield a revenue-positive outcome. Partnerships that encompass both active listening and strategic planning are indispensable for universities to thrive in an era where significant professional reskilling is urgently required.
Effective Marketing
The marketing strategies for university-based professional reskilling programs differ from those for traditional degree programs, and these differences manifest in several key areas:
Target audience. Degree programs primarily aim to attract high school graduates or individuals seeking higher education for initial career preparation. In contrast, professional reskilling programs target working professionals, as well as those who are unemployed or seeking a career transition. The channels for reaching these distinct groups also vary. While degree programs often utilize digital platforms popular among high school graduates, career fairs, and school visits, reskilling programs are more likely to leverage platforms like LinkedIn, industry events, and partnerships with employers.
Messaging. The messaging for degree programs is most effective when it focuses on academic excellence, long-term career prospects, and campus life. Reskilling programs, however, need to focus on the immediate return on investment, the relevance of the skill set being offered, and how these new skills will enhance long-term professional value, career opportunities, and job stability.
Time frame. Degree programs typically have annual enrollment cycles and involve long-term planning both by program designers and by prospective students. Reskilling programs, on the other hand, often need to be marketed swiftly, in response to rapid changes in the job market due to technological advances. This necessitates rolling admissions, quick start dates, and shorter program durations.
Pricing. While degree programs can command higher tuition fees and offer scholarships and financial aid to promote diversity and attract top talent, reskilling programs cater to a more price-sensitive audience. This audience often has family responsibilities and is beyond the stage of living frugally. As a result, reskilling programs need to offer more flexible payment options and to encourage employer sponsorships.
Curriculum development. Traditional degree programs are developed over several years and rely on a stable identity for effective marketing. In contrast, the marketing of reskilling programs is often contingent on the speed at which they can adapt to emerging needs in the job market. While a strong reputation for delivering effective reskilling programs is beneficial, the primary focus should be on addressing current market demands rather than repurposing existing content.
In summary, the marketing of professional reskilling programs requires a distinct approach, tailored to meet the specific needs, timelines, and financial considerations of a different target audience. More broadly, Table 2 characterizes the kind of programming that is likely to be effectively marketable by a professional reskilling unit in a university.
Coda: Advice from Supermind Ideator
Beyond my own thinking in response to the suggestions from ChatGPT, I also asked MIT’s Supermind Ideator to describe the analogies between tech transfer and professional reskilling. Table 3 shows what it provided.
These analogies are also a notable set of core principles for a research university’s professional reskilling efforts.
[1] I thank Mike Bridges for the conversations that led to this piece and for helpful comments on how to improve it. Tables 1 and 2 were developed with help from ChatGPT, and Table 3 was developed with help from Supermind Ideator.
[2] Lesgold, A., and Bridges, M. (2023). Can Universities Prepare People for the Future of Work? Medium. https://medium.com/about-work/can-universities-prepare-people-for-the-future-of-work-c499547845ee
[3] Shute, V., & Ventura, M. (2015). Stealth assessment. The SAGE encyclopedia of educational technology, 675–676.
[4] See, for example, https://www.mckinsey.com/mgi/our-research/generative-ai-and-the-future-of-work-in-america
