# Innovating for the Future: AI and HRM Capabilities for Sustainability in Higher Education

Tricia Cleland Silva, Mika Hämäläinen

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Tricia Cleland Silva, Mika Hämäläinen. Innovating for the Future: AI and HRM Capabilities for Sustainability in Higher Education. Academy of Management Annual Meeting, Aug 2024, Chicago, United States. 10.5465/AMPROC.2024.19249abstract. hal-04665987

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# Innovating for the future: AI and HRM capabilities for sustainability in higher education

Tricia C. Cleland Silva and Mika Hämäläinen

## ABSTRACT

This paper investigates the intersection of sustainability strategies and artificial intelligence (AI) in Human Resource Management (HRM) with a Finnish University of Applied Sciences as its case study. Drawing from a multi-level framework, the paper explores and discusses the interplay of barriers and drivers shaping sustainability practices in teaching and the potential of leveraging AI for consistent messaging and accountability to the organizational goals. The historical evolution of AI in HRM is presented with an emphasis on the need for strategic frameworks. The research design uses a cross-disciplinary approach, focusing on case study analyses within the educational context. Preliminary findings reveal a gap in translating institutional and strategic sustainability capabilities into operational practices, prompting the introduction of AI plugins for enhanced accountability and transparency in the digital learning platform. The study concludes with recommendations for future research, emphasizing the potential of AI in the HRM system and practices to drive sustainability in higher education.

## Keywords:

changing nature of work, creativity and innovation, HR and organizational strategy
Introduction

Within the evolving landscape of Finnish higher education, the imperative for sustainability and technological innovation necessitates a paradigm shift in Human Resource Management (HRM) system design and practice. This paper aims to explore the preliminary research of sustainability strategies in practice at a Finnish University of Applied Sciences. Drawing from Broken and Gersalts's (2020) multi-level framework, the initial analysis illustrates interconnected barriers and drivers which enable or prevent sustainability in teaching and how HRM can leverage AI for consistent messaging and accountability between levels. Building on this, the paper proposes the use of AI's role for future research on how HRM in higher education can support employees with necessary skills for sustainability goals.

Historical approaches to AI and its Evolution in HRM for Sustainability in
education

Recent research has acknowledged the potential of AI in HRM, offering opportunities to enhance
sustainability strategies and foster value-based learning in higher education. However, the
research on the intersection of AI and HRM is limited, and it becomes imperative to address the
barriers and challenges that may impede the incorporation of AI practices within work
organizations. This section aims to provide an overview of the historical roots of AI from
rule-based approaches to the contemporary era of neural networks and Transformer-based
models as a way to narrow the focus to AI's impact on Human Resource Management (HRM).
Early AI solutions were rule-based, which meant that people had to write rules by hand to cover different scenarios the AI system might face. In particular, grammar rules from linguistics served as an inspiration for early computational approaches to AI, such as Context-Free Grammars (Chomsky & Schützenberger, 1959), Finite-State Automata for morphological processing (Karttunen, 1994) and Head-Driven Phrase Structure Grammars (Pollard & Sag, 1994). The problem with such approaches was that the more complex the phenomenon one tries to model is, the more difficult it is to come up with a suitable list of rules to model the phenomenon computationally.

After the rule-based era, machine learning started to emerge in the field of AI research. Suddenly, many things that required a vast amount of rules were solvable simply by coming up with a suitable algorithm and training a computational model on data. Some of the important methods of the era were Principal Component Analysis (Pearson, 1901), Support Vector Machines (Cortes & Vapnik, 1995) and Bayesian Modelling (see Mackay, 1992). While the computational methods for machine learning already existed for a long time, it was the increase in data and computational resources that made their use viable for downstream AI applications.

After computers became even faster, neural networks emerged in AI research. Researchers started truly experimenting with older neural networks such as Recurrent Neural Networks (Amari, 1972) and Convolutional Neural Networks (Fukushima, 1980) only in the past decade. This has led to the emergence of Transformer (Vaswani et al., 2017), which is an all-purpose neural network that can be trained to work with any modality such as text, audio or image. Later on, it was found that Transformers can exhibit emergent behavior and even learn things that it
has not explicitly been trained to solve (see Anil et al., 2023). Modern AI solutions such as
ChatGPT (OpenAI, 2022) and DALL-E (OpenAI, 2021) are Transformer-based.

The integration of AI into Human Resource Management signifies a transformative shift in managing people, presenting the potential to enhance sustainability policies and foster value-based learning in higher education. Recent comprehensive reviews have highlighted the interdisciplinary nature of AI research in HRM, spanning management, economics, computer science, engineering, and operations (Budhwar et al., 2022). However, the reviews have also emphasised the need for enhanced interdisciplinary collaborations, a unified definition of AI, and more robust theoretical development to fully harness the transformative potential of AI in HRM (Malik et al., 2023).

The benefits of AI for HRM have been noted and yet, there is an emphasis that AI should be viewed as a tool rather than a replacement for human judgement in HRM (Gryncewicz et al., 2023). Through the systematic reviews, the necessity for a strategic framework to guide HR managers in adopting and implementing AI-assisted HRM is underscored that critically examines organizational and employee-centric outcomes (Malik et al., 2023).

The consequences of a weak HRM system when adapting AI and applying organizational strategies for sustainability, highlights the roles of distinctiveness, consistency, and consensus, and emphasises the need for a strong HRM system to convey clear messages that derive from the organizational values and strategies (Bowen & Ostroff, 2004). In this context, it is noteworthy that different types of sustainability strategies require different capabilities such as institutional, strategic and operational (Bocken and Geradts., 2020)). Furthermore, factors in organizational design are likely to play different roles depending on the adopted strategy and the required
capabilities (Bocken et al 2020)). This insight underscores the importance of aligning AI-assisted
HRM practices with the specific sustainability goals and organizational design considerations
based on the existing capabilities.

Drawing on these insights, it becomes evident that the integration of AI into HRM systems could
enhance accountability by aligning decisions with sustainability and social responsibility goals.
The potential for AI to contribute to the creation of a strong HRM system, characterised by clear
messages, organizational goal alignment, and a work environment through consistent and visible
practices, holds promise for shaping more sustainability knowledge and practice in higher
education. However, exploring this potential requires further systematic research and case study
analyses to understand the nuanced interactions and outcomes in the integration of AI and HRM
within educational institutions that have sustainability as organisational strategies.

The case for sustainability in higher education

Sustainability has become a focal point in Finnish universities of applied sciences, driven by
governmental reforms addressing global challenges and educational institutions. The universities
have aligned their organizational strategies to contribute to governmental reforms with the
development of knowledge and innovative solutions. Originating in the late 1960s during a
period of environmental activism, the concept of sustainability was initially associated primarily
with the environment rather than business or society. Bansal and Song (2017) argue that
sustainability in businesses, for instance, only gained prominence in the late 1990s, with
increased awareness and a sense of responsibility emerging in the 2000s.

In 2015, the United Nations General Assembly drafted the Sustainable Development Goals (SDGs), succeeding the Millennium Development Goals (MDGs). Unlike the MDGs, the SDGs
encompass a comprehensive set of goals addressing environmental, societal, and economic aspects through private-public partnerships. The SDGs marked a shift in perceiving private and for-profit organizations as stakeholders, emphasizing a collective responsibility and legal accountability for addressing global challenges (United Nations N.d.)

Described as a "shared blueprint for peace and prosperity for people and the planet," the SDGs mirror sustainability's system-thinking approach, connecting to the origins of corporate social responsibility (CSR) (United Nations N.d). With 17 goals, the SDGs highlight the interconnectedness of environmental, societal, and economic dimensions in sustainable development. Sustainability is considered a "normative concept," grounded in values, feelings, and desires, according to Mebratu (1998). Harrington (2016) emphasizes the quest for sustainability as connecting scientific knowledge to applications in pursuit of desired future outcomes.

Despite these efforts, there are barriers to translating sustainability, framed as abstract concepts in broad goals, into collective convictions and subsequent actions. Many individuals do not perceive themselves as responsible or capable of contributing to global challenges in their personal and professional lives (Cleland Silva, 2023).

Finnish universities of applied sciences have embraced organizational strategies for sustainability, influenced by Finnish government policies, as Finland actively participates in the Wellbeing Economy Governments (WEGO) partnership. WEGO is a collaborative initiative which involves national and regional governments, including those of Scotland, Iceland, New Zealand, Wales, and Canada. These partner members engage in the exchange of insights and
experiences through WEGo Policy Labs, fostering a shared commitment to sustainable policy
practices (Fioramonti, Lorenzo et al 2022).

Within the Finnish context, specific instances of WEGo influence include the appointment of a steering group by the Finnish Ministry of Social Affairs and Health in 2021. This group is charged with developing a national action plan to seamlessly integrate the economy of wellbeing approach into knowledge-based decision-making (STM n.d). Additionally, Finland has established the International High-Level Group on the Economy of Wellbeing, a collaborative effort aimed at leveraging international and multi-sectoral expertise to shape the Economy of Wellbeing as a policy-making tool within the framework of global collaboration.

In this context, publicly-funded organizations (Denis et al. 2009) like our case study of Metropolia University of Applied Sciences, have redesigned organizational strategies and resource allocation towards sustainable development in reform their operations and teaching.

This strategic integration reflects a concerted effort to contribute to sustainable practices within higher education.

## Research design: From policy and knowledge to practice

Our research design came from a cross-disciplinary and interorganizational effort to explore the integration of AI in HRM systems, with a focus on enhancing accountability for sustainability goals within the organization. We propose that leveraging AI, through its development and use in teaching, can strengthen the HRM system with clear communication, organizational goal alignment, and visible practices, particularly in higher education institutions committed to sustainability and value-based learning.
To explore the potential of AI in HRM, the research design incorporates case study analyses within the educational context. This approach is for preliminarily data to provide practical insights for the effective integration of AI in HRM practices aligned with sustainability objectives.

The preliminary findings are based on the feedback and discussions of the Sustainability in Education Board in 2023 which were documented in a MS team channel, Metropolia's internal documents, three reports (two on sustainability (2021 and 2022) and an executive summary of an external audit), and preliminary observations from coding an AI plugin for sustainability in Metropolia's digital learning platform (Moodle). In short, the data has been collected by document research (Prior 2003) and participant observations (Kennedy-Lewis 2012), with a preliminary analysis that was deduced from Broken and Geradts' (2020) multi-level framework to analyses barriers to sustainable innovation in organization design capabilities. The multi levels are institutional, strategic and operational. Broken and Geradts (2020) also suggest focusing on dynamic capabilities such as sensing, seizing, and transforming which we use to recommend future research in HRM with our proposition that an AI plugin can be leveraged for communication on organization and employees' capability to sense, seize and transform sustainability in teaching across levels.

The researcher and first author of this paper was recruited and allocated hours to meet the Board monthly, to attend and organize workshops with heads of degree of the health and social services campus, and coordinate together with the Board a teacher-led workshop (September 2023) that showcased examples of integrating sustainability in teaching at Metropolia. The researcher also attended meetings with an externally hired AI company that had been working for Metropolia since 2019 on AI generated scorecards based on the content available on the organization's
website where research notes were taken. The objective of the external company was to visualise and raise awareness as to how the content correlated with the United Nation Sustainable Development goals.

With these experiences, Metropolia decided to create a role for AI expertise, which is the role filled by the second author and co-researcher who was hired in June 2023.

## Preliminary findings: Future research to leverage AI in HRM for sustainability in higher education

Similar to other professional organizations (e.g., Hart and Dowell, 2011; Inigo et al., 2017), higher education institutions often are lacking dynamic capabilities required to innovate for sustainability. Dynamic capabilities, defined as an organization's capacity to "integrate, build, and reconfigure internal and external competences to address rapidly changing environments" (Teece et al., 1997, p. 516), play a crucial role in organizational design and innovation (e.g., Teece, 2018). Ordinary capabilities, functioning as repeatable patterns of action at a fundamental level, enable large organizations to maintain their existing organizational design (Winter 2003). In contrast, dynamic capabilities encompass sensing (identifying and assessing opportunities), seizing (mobilizing resources to address opportunities and capture value), and transforming (continuously renewing the organization) (Broken and Geradts 2020). These dynamic capabilities allow organisations to adapt, recombine, and transform ordinary capabilities in their organizational design (Harreld et al., 2007; Teece, 2007).

Organizations typically undertake the reconfiguration of capabilities and invest in the development of dynamic capabilities when the perceived financial benefits of change outweigh those of maintenance (Hart and Dowell, 2011; Winter 2003). This tendency poses challenges for
sustainability because it is not always clear how organizations can generate financial value through sustainability (Epstein and Roy, 2001; Schaltegger et al., 2012) and addressing complex sustainability challenges with uncertain pay-offs may require financial trade-offs and extensive experimentation with various external stakeholders and not sole prioritization of short-term profit (Aragón-Correa and Sharma, 2003; Weissbrod and Bocken, 2017).

Focused on constructing effective organizations to help them achieve their purpose and objectives (Burton et al., 2006), organization design is conceptualized as a configuration of components such as strategy, structure, processes, incentives, and people (Burton et al., 2006; Mintzberg, 1980). Despite acknowledging that an organization's vision, culture, structure, resource allocation, incentive system, and values can either bolster or undermine its dynamic capabilities, the design aspects needed for dynamic capabilities for sustainability innovation remain inadequately explored in most professional organizations (Fjeldstad and Snow, 2018; Bocken and Geradts 2020).

In our case study, sensing and seizing opportunities for sustainability in higher education at the institutional and strategic levels were captured in the internal documents and reports. These dynamic capabilities, which will be discussed below, have been employed through an online course for all staff to acquire knowledge on sustainability and the allocation of annual budgets to the strategies of sustainability. Nonetheless, there is a clear division between policy and strategies at the institutional level being applied to practices beyond knowledge acquisition on the theory of sustainability. This is displayed in an external audit that proposed simplifying quality management systems at the operational level and in organizational design. At the
operational level, we propose leveraging AI plugin throughout the information systems at the university to ensure accountability and transparency of sustainability is applied.

## Institutional level capabilities: Sensing sustainability

In 2021, Metropolia University of Applied Sciences initiated organizational strategies focused on sustainability. Operating in diverse fields such as culture, business, technology, and health care, Metropolia emphasizes a multidisciplinary approach. With a strategic vision spanning 2021-2030, the institution prioritized societal impact and aimed to be “a bold reformer of expertise” (Kahra, 2022:6). The strategy revolved around five key themes, including continuous learning and phenomenon-based innovation hubs. Metropolia aspired to guide all operations with principles of sustainable development, targeting carbon neutrality by 2030. Success factors encompass people, culture, and digitalization, with a commitment to fostering a flexible learning culture and enhancing digital capabilities. The strategy is stated to be implemented responsibly, guided by values such as transparency, community spirit, high quality, and expertise. Below is an illustration of the aspired organizational strategies and reforms, including the establishment of two new work positions, three teams, and one network (Kahra et al., 2022: 8).
<figure><img src="image_2.png" /><figcaption>FIGURE 1: Metropolia Sustainability Highlights 2021</figcaption></figure>

In 2022, institutional reforms at Metropolia were driven by a commitment to sustainability, guided by the UN Sustainable Development Goals, the Metropolia 2021–2030 strategy, stakeholder expectations, and a sustainability roadmap (Ojala et al., 2023). This roadmap outlined specific goals and associated measures, serving as the foundation for development efforts. The key objectives included social, ecological, and economic sustainability, expertise in sustainable development, and the creation of sustainable solutions. Coordination of sustainability efforts was to be overseen by the Sustainable Development Manager, with specific responsibilities delegated to managers for each goal. Progress was to be regularly communicated through quarterly impact reports and an annual sustainability report, ensuring accountability to stakeholders and the board (Ojala et al. 2023).
In spring 2022, Metropolia also initiated a values renewal, engaging around one thousand students, staff, and stakeholders in a two-stage process, with the ultimate aim of implementing the outcomes in 2023. The institution decided to transition to the term 'value base' to encapsulate the comprehensive perspectives that emerged, serving as the foundational element for their strategy-driven operations (Metropolia N.d).

In early 2023, Metropolia passed an external audit with the following recommendations summarised below (Internal announcement):

> Metropolia uses many surveys and feedback channels. Feedback collection should not be limited to quantitative methods but comprise qualitative methods. This mix could be more favourable to concrete enhancements, which would be more transparent and visible to create an even stronger incentive for student participation.

> The growing number of focus areas increases the risk of poor consistency. Realistic resource planning is vital for ensuring sufficient resources for strategic actions.

> Metropolia should reduce the complexity of the quality management system and communicate goals, instruments, and roles distribution with the staff more intensively.

> The staff of Metropolia is motivated by phenomenon-based teaching and learning. However, new projects and activities need resources which are not necessarily sufficiently available. The audit team anticipates the possible risk of conflicts due to resources shared between RDI, especially the innovation hubs and teaching, which should be observed carefully.

Based on the report, Metropolia identified the audit's key considerations as the quality system which revolved around clarification and communication, with a particular emphasis on assessing the practical implementation of the continuous improvement principle (PDCA cycle) across various organizational levels. It was stated in the internal announcement that "the upcoming
internal audit in 2024 will further scrutinize the PDCA cycle's practical application and the
integration of the quality system into daily operations" (31.7.2023).

Strategic capabilities: Seizing opportunities for Sustainability

In all the reports and documents, there is an emphasis on community-led solutions and the language of “change agents” and “bold reformers”. Meetings were organized and led with this language throughout 2023 when the primary author and researcher was allocated work hours to participate in the sustainability in Education Board. And yet, a common feedback from participants on the board as well as the main teaching workshop in September 2023 was the lack of leaders and management (researcher notes 23.9.2023)

Operational level capabilities: Transforming through AI

To increase the operational capabilities of using AI to achieve sustainable development goals, three student programmers were required to conduct AI development. The applicants were given a task of building a small Finnish-English machine translation tool using Hugging Face Transformers (Wolf et al., 2020). The students who submitted the most advanced tools were invited for an interview, and the ones who had developed the tool even further than instructed were hired.

The students were tasked to work on two different projects that involve the use of AI in
strengthening sustainability in Metropolia. The first project is about developing a Moodle plugin
that can coach teachers in sustainability matters, the other project is about analyzing the SDGs
related to each course, module and degree program in a curriculum-level. Both projects use
PaLM 2 (Anil et al., 2023), a large language model developed by Google. The reason for going
with PaLM 2 instead of ChatGPT was that Google Cloud services are GDPR compliant<fnref n="1" /> whereas
OpenAI has had difficulties in following EU legislation².

The Moodle plugin is designed to bring LLM capabilities directly to the Moodle environment with no need for teachers to consult any external services. Currently, the plugin creates an AI button next to teaching materials that are in PDF or PowerPoint format. When a teacher clicks on the button, the LLM is prompted to identify the most relevant SDGs for the current lecture given the teaching material. After this, the teacher can choose which SDG they would like to teach about during their class, and the LLM is prompted to give talking points and an example assignment based on the teaching material and the chosen SDG.

The curriculum tool is used to identify which SDGs are covered by each course in Metropolia.
This tool provides study planners with valuable information on how sustainability is taught in
different parts of the University. The idea is to prompt an LLM with a course description to
extract the SDGs that are covered in a given course. The tool can also do this on a module or
degree level, in which case, the tool prompts every single course within the module or degree
and returns an aggregated list of SDGs that are covered in the entire module or degree.

## Discussions and recommendations for future research

Kocken and Geradts (2020) contend that sustainability drivers at each level play a crucial role in shaping how large organizations sense and seize sustainability opportunities, allowing for the

<footnote n="1">¹ https://cloud.google.com/blog/products/ai-machine-learning/enterprise-ready-generative-ai-models-go-ga-in-vertex-ai
² https://www.theverge.com/2023/5/5/23709833/openai-chatgpt-gdpr-ai-regulation-europe-eu-italy</footnote>
capabilities to innovate with these opportunities to transform existing organizational systems and structures.

Through the preliminary analysis of the data, the case study exhibits drivers for sustainability in higher education in practice through institutional and strategic capabilities. To simplify and enhance the institutional capabilities of the quality management and HR system after the external audit, Metropolia strategically restructured the organization and HRM systems through the autumn 2023 with the intention of a 2024 internal audit.

The 2021 and 2022 sustainability reports clearly communicated the values and beliefs of the university with the Sustainability Roadmap, a dedication of resources and working roles as well as defined strategic goals in relation to the United Nations Sustainability goals.

We propose that there is a research gap between institutional and strategic capabilities versus operational capacities. There is a clear value-based driven organizational design which affects the HR system and a robust climate of employee driven sustainability effort; however, the lack of accountability measurements of the efforts for sustainability in education remain elusive. This can be addressed through AI plugins.

## Conclusion

There is potential for leveraging AI in HRM for sustainability strategies in higher education, which our preliminary data in our case study suggests. Our case study's commitment to sustainability is sensed and seized in the institutional and strategic capabilities that are aligned with the UN Sustainable Development Goals. However, the preliminary findings also underscore barriers in translating high-level sustainability commitments into operational practices, revealing
a gap that necessitates further exploration. In addition, our paper proposes leveraging AI as a
supportive tool to enhance accountability and transparency of sustainability in teaching and the
overall operations of the universities.

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