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Article

Artificial Intelligence and Developments in the Electric Power Industry—A Thematic Analysis of Corporate Communications

by
Dorota Chmielewska-Muciek
1,
Patrycja Marzec-Braun
1,
Jacek Jakubczak
1 and
Barbara Futa
2,*
1
Faculty of Economics, Maria Curie-Sklodowska University of Lublin, Pl. Marii Curie-Sklodowskiej 5, 20-031 Lublin, Poland
2
Institute of Soil Science, Engineering and Environmental Management, University of Life Sciences in Lublin, Leszczynskiego 7, 20-069 Lublin, Poland
*
Author to whom correspondence should be addressed.
Sustainability 2024, 16(16), 6865; https://doi.org/10.3390/su16166865
Submission received: 5 June 2024 / Revised: 31 July 2024 / Accepted: 8 August 2024 / Published: 9 August 2024
(This article belongs to the Section Energy Sustainability)
Review Reports Versions Notes

Abstract

:
This study investigates the role and impact of artificial intelligence (AI) in the electric power industry through a thematic analysis of corporate communications. As AI technologies proliferate, industries—such as the electric power industry—are undergoing significant transformations. The research problem addressed in this study involves understanding how electric power companies perceive, adopt, and implement AI, as well as the implications of these developments. By employing a qualitative thematic analysis approach, we examined a corpus of corporate communications from innovation leaders, including annual reports and sustainability reports, in the electric power sector. The data spanned 2020 to 2023, capturing a crucial period of AI integration in the industry. Our analysis reveals several key findings. Firstly, there is a clear trend toward increased utilization of AI in various facets of the electric power sector, including grid management, predictive maintenance, and customer service. Companies actively invest in AI technologies to enhance operational efficiency, reduce costs, and improve service quality. Secondly, the corporate discourse has shifted significantly, with companies emphasizing AI’s role in sustainability efforts. Moreover, our analysis identified challenges and concerns associated with AI adoption in the electric power industry. In conclusion, the thematic analysis of corporate communications provides valuable insights into the evolving landscape of AI in the electric power industry. The findings underscore the transformative potential of AI technologies, highlighting opportunities for enhanced efficiency and sustainability. However, they also emphasize addressing challenges to ensure responsible and beneficial AI integration. This study contributes to the growing literature on AI in industries, offering practical implications for electric power companies, policymakers, and stakeholders navigating the AI-driven future of the sector.

1. Introduction

The literature provides various perspectives on the essence of artificial intelligence. Artificial intelligence (AI) is defined as the ability of computer systems to learn and, in doing so, exhibit human-like behavior. AI is associated with human intelligence in that it can perform tasks or reasoning processes through the use of a computer program [1,2]. It refers to replicating human intelligence in machines that can think like humans and imitate their actions through characteristics such as perception, learning, use of knowledge, logical reasoning, self-correction, planning, and problem-solving [3,4,5,6]. This is because artificial intelligence can correctly interpret data, learn from the data, and then use this knowledge to achieve specific goals through flexible adaptation [7].
AI is the science and engineering of creating intelligent machines, encompassing robotics and automation across various professions and industries. In particular, the growing dynamics of artificial intelligence can be seen in driving innovation in business models, products, services, and research practices [8,9]. AI supports everyday social life and business activities; nevertheless, it can pose a threat to human professions [10]. Its significant limitation is its over-reliance on large datasets and its lack of self-imagination capabilities [11].
Observing economic changes indicates a significant impact of artificial intelligence on business processes. It affects managerial work at strategic, tactical, operational, functional, and administrative levels [12]. It plays a crucial role in forming customer relationships by analyzing data on their behaviors and providing personalized recommendations. Additionally, by processing natural language, artificial intelligence contributes to more effective communication through voice recognition systems, virtual assistants, and chatbots [13]. AI assists employees in carrying out more challenging activities, enabling them to be creative and innovative in the tasks at hand. As a result, it helps improve productivity and efficiency, as well as reduce organizational costs [13,14]. Bharadiya [13] listed additional benefits of implementing artificial intelligence, including streamlining HR processes, improving supply chain and logistics processes, detecting fraud, managing risks, implementing cybersecurity, developing robotics, and automating complex tasks.
The use of artificial intelligence by companies not only leads to new opportunities for them but also numerous limitations. Because artificial intelligence is not equipped with human cognitive capabilities, it cannot be used in tasks that require intuitive intelligence [14]. Cultural inconsistencies in language technologies using artificial intelligence are also problematic and can lead to problems in the relations between representatives of different cultures and societies [15]. In order to take full advantage of the potential capabilities of artificial intelligence, researchers postulate that its implementation should be approached thoughtfully and ethically [13,16,17,18].
The ubiquitous impact of artificial intelligence is evident in various economic industries and fields of human activity. Many researchers refer to the applications of artificial intelligence in national security, the judiciary system, the healthcare industry, and the aviation industry to perform complex tasks previously performed only by humans [19,20]. Damaševičius [21] described using artificial intelligence in finance, economics, manufacturing, and mining. Balmer, Levin, and Schmidt [22] wrote about using artificial intelligence to minimize costs, improve customer service and efficiency, and develop new services in the power, gas, telecommunications, and water industries.
We also see significant use of artificial intelligence in the power industry due to radical energy transformation. Advanced communications, metering infrastructure, distributed energy sources, management algorithms, renewable energy, new digital solutions, electric vehicles, and energy efficiency programs are driving dynamic changes in the power industry. Franki, Majnarić, and Višković [23] wrote about the significant potential of artificial intelligence in analytics, e-mobility, data forecasting, cybersecurity, financial services, and customer service, as well as in solving many system-level optimization and resource optimization problems. AI is already used to connect to smart networks and Internet of Things devices [24], as well as improve the planning, operation, and supervision of power systems [25].
Technological transformation, environmental policies, economic growth, competitiveness, climate change, and market structures have also influenced the use of artificial intelligence in the electric power industry [26]. AI is driving innovation in business models by automating services, minimizing energy supply disruptions, and improving production, transmission, and consumption processes, leading to improved efficiency and profitability of business practices [27]. The electric power industry uses artificial intelligence to optimize, secure, and control the operation of smart grids and modern systems, particularly in controlling electrical automation within the electric power distribution area [28]. AI applications in the electric power industry include data acquisition for classification, optimization, mining, and regression during the design, control, and maintenance stages of remotely controlled equipment [29,30]. Hussain et al. [31] wrote about artificial intelligence’s important role in mitigating cyberattacks on smart grids. Jiao [32] and Huang [33] highlighted the use of artificial intelligence for analyzing energy user behavior and improving customer service, as well as for fault diagnosis and predictive maintenance.
With the dynamic application of artificial intelligence in the electric power industry, one exciting research aspect involves communicating this to stakeholders. However, this is a research issue rarely undertaken. The articles mainly focus on applying artificial intelligence in stakeholder communication strategies [34,35,36,37]. The adaptation of artificial intelligence in activities such as spokesperson operations, customer communication, customer research, message personalization, editing press releases, image analysis, content conversion, and targeting displayed content to individual recipients is noted [38]. There are studies on using artificial intelligence in marketing communications with stakeholders [39]; however, there is a lack of research on how companies in the electric power industry communicate about their use of artificial intelligence. Accordingly, this article identifies the communication of AI topics by selected companies in the electric power industry, based on their reports. This article identifies and analyzes patterns of meaning related to AI utilization within corporate communications in the electric power industry.

2. Methods

This section outlines the methodological approach undertaken to investigate the role and impact of artificial intelligence (AI) in the electric power industry. A thematic analysis of corporate communications will be employed to achieve this objective.
This study aims to explore the role and impact of artificial intelligence (AI) in the electric power industry through a thematic analysis of corporate communications. Three primary questions guide this research: How is AI communicated within corporate communications in the electric power industry? What are the dominant themes and narratives surrounding AI in these communications? Finally, how do these types of communication address the benefits and challenges of AI implementation? A diverse range of corporate communications will be purposefully selected to capture a holistic perspective on AI integration within the industry. This will encompass annual reports, sustainability reports, consolidated non-financial statements, corporate social responsibility (CSR) reports, environmental, social, and governance (ESG) reports, and financial and sustainable development reports. The timeframe for data collection will span the years 2020–2023, ensuring a representative sample that reflects the most recent advancements in AI. A purposive sampling strategy will be utilized to maximize the variation within the selected corporate communications. This involves selecting reports from leading companies across geographically distinct regions, technology providers specializing in AI solutions for the electric power sector, and companies of varying sizes and areas within the industry. The characteristics of the enterprises selected for the research sample are presented in Appendix A.
Following Braun and Clarke’s [40] six-phase framework, this study employs an inductive thematic analysis approach to examine corporate communications regarding AI in the electric power industry. This method was chosen for its flexibility and ability to allow themes to emerge from the data [41], which is particularly valuable when exploring a rapidly evolving topic like AI implementation. The inductive approach aligns with the exploratory nature of the research, enabling a nuanced understanding of how companies conceptualize and communicate about AI without imposing predetermined expectations [42]. Thematic coding will be conducted on the collected reports. This entails a systematic process of identifying and categorizing text segments relevant to AI. A comprehensive codebook will be developed to ensure consistent coding practices throughout the analysis. To increase the reliability of the results, discussions will be held after the initial coding of the pilot dataset to reconcile any discrepancies and refine the coding framework [43].

3. Results

An inductive thematic analysis was conducted on 61 corporate reports from the electric power industry that were identified as containing AI communication. A total of 481 AI-related statements were identified in the sample, which were context-coded using 189 unique codes. Utilizing these codes made it possible to identify 18 key themes appearing in corporate communications. Their frequencies of occurrence are shown in Table 1.

3.1. Practical Application

A thematic analysis of corporate communications within the electric power industry reveals a compelling narrative regarding the practical applications of AI. A key theme emerges, focusing on AI’s tangible implementation and anticipated benefits across the entire value chain, encompassing generation, transmission, and distribution. The frequencies of occurrence of individual codes related to the theme of practical application between 2020 and 2023 are presented in Table 2.
Thematic analysis reveals a focus on AI as a cornerstone for enhanced operational efficiency and reduced maintenance burdens. Phrases like “support in maintenance”, “instrument used at industrial plants”, and “optimized management of wind and solar plants” underscore its potential to automate tasks, implement predictive maintenance through anomaly detection capabilities, and optimize resource allocation for field service personnel.
A significant focus is on leveraging AI for smarter grid management strategies. Terms like “flexibly manage the grid systems” and “smart energy management system” suggest its application in areas like demand forecasting, real-time grid optimization, and more efficient integration of renewable energy sources. This alignment with industry priorities underscores the potential of AI to address critical challenges in grid modernization.
The analysis indicates that AI is envisioned as a tool for improved infrastructure management, encompassing construction and ongoing management aspects. Phrases like “construction assistance”, “infrastructure management assistance”, and “key technology to building intelligent hydropower plants” point toward its potential role in optimizing construction processes, automating inspections, and enhancing overall asset management strategies. This focus on infrastructure management reflects the industry’s need to optimize capital expenditure and ensure the longevity of critical assets.
Furthermore, the analysis suggests that AI can catalyze business model transformation within the electric power industry. Phrases like “monetization of assets”, “source of savings”, and “improve business development” indicate its potential to optimize energy production and consumption patterns, create novel revenue streams through innovative services, and streamline core business processes. This alignment with industry trends toward distributed energy resources and customer-centric solutions highlights the strategic importance of AI in fostering a more dynamic and competitive market landscape.
In conclusion, the identified codes paint a comprehensive picture of AI as a transformative force with the potential to significantly impact the electric power industry. Practical applications encompass core operations and maintenance, grid management, infrastructure development, and even business model innovation across the entire value chain. This highlights the strategic imperative for electric power companies to leverage AI to enhance efficiency, optimize resource utilization, and create a more sustainable future.

3.2. Business Benefits

Another prominent theme revealed by the thematic analysis of corporate communications within the electric power industry involves the anticipated business benefits associated with AI implementation. A robust cluster of interrelated codes demonstrably supports this theme. The frequencies of individual codes related to the theme of business benefits between 2020 and 2023 are presented in Table 3.
Process automation emerges as a critical driver of anticipated benefits. Terms such as “process optimization”, “operational efficiency”, and “acceleration of processes” highlight the potential for AI to streamline workflows and reduce manual labor across all organizational levels. This focus on automation demonstrably extends to both management and field operations. Codes such as “management support”, “worker assistance”, and “management in field operative processes” suggest AI can empower employees at all levels, potentially leading to improved decision-making throughout the value chain.
Furthermore, the theme underscores the potential for comprehensive efficiency improvement across various aspects of electric power operations. Codes such as “production optimization”, “energy and storage efficiency”, and “increase in operational efficiency” all point toward AI’s ability to optimize resource utilization and minimize waste. This directly translates to cost reduction, with terms like “source of savings” and “source of optimization” suggesting a positive financial impact for companies adopting AI solutions.
Beyond cost savings, AI is also identified as a source of innovation and improvement. Codes like “source of change in organization management”, “source of benefits”, and “source of improvements” indicate a broader transformation potential for the industry. AI’s ability to analyze vast datasets and identify patterns can lead to novel solutions and improved electric power value chain performance.
It is essential to acknowledge that the theme also acknowledges potential disruption alongside opportunity. The code “opportunity and disruption” suggests that the industry recognizes that AI implementation may necessitate changes in traditional workflows and organizational structures. However, the overall focus within the corporate communications analyzed remains on the significant business benefits AI can potentially deliver to the electric power industry.

3.3. HRM

This thematic analysis of corporate communications within the electric power industry reveals a critical focus on human resource management (HRM) practices in the context of AI implementation. Codes such as talent acquisition, talent management, talent development, career management, and learning management all point toward a strategically driven workforce transformation in response to AI integration. The frequencies of occurrence of individual codes related to the theme of HRM between 2020 and 2023 are presented in Table 4.
The thematic analysis underscores several critical areas of impact on HRM practices. Firstly, a shift in recruitment strategies is evident, focusing on acquiring talent possessing the requisite skillsets to collaborate with and manage AI technologies. This suggests a potential paradigm shift, with data analysis, problem-solving, and adaptability complementing traditional industry knowledge and becoming increasingly sought-after during talent acquisition.
Secondly, the theme emphasizes the evolving role of training and development. Codes such as learning digitization, personalized learning, and new skills necessary indicate a need for reskilling and upskilling the existing workforce to facilitate effective collaboration with AI. This suggests a move toward more targeted and technologically driven training programs, ensuring a future-proof workforce.
Finally, the theme highlights a proactive approach to career progression within the context of AI adoption. Codes like learning management and career progression suggest focusing on managing employee concerns and ensuring continued growth opportunities alongside AI integration. This underscores the need for transparent communication and the establishment of robust support structures to navigate potential career transitions.
In conclusion, the HRM theme demonstrates a strategic shift within the electric power industry. The identified codes suggest a multi-faceted approach encompassing talent acquisition, development, and career management, all facilitated by the strategic use of technology in training programs. This focus on HRM practices reflects the industry’s recognition that successful AI implementation hinges on a skilled, adaptable, and future-proof workforce. This proactive approach signifies a commitment to not only harnessing the power of AI but also ensuring a smooth transition for its human capital.

3.4. Customer

Another essential theme revealed through the thematic analysis of corporate communications within the electric power industry is centered on the “customer”. This theme explores AI’s perceived role and impact on customer interactions, encompassing various sub-categories that are crucial for effective customer relationship management (CRM). The frequencies of individual codes related to the “customer” theme between 2020 and 2023 are presented in Table 5.
The code “customer expectations” explicitly highlights a critical challenge—elevating customer expectations fueled by the proliferation of AI solutions across industries. Customers may now anticipate a more personalized, efficient, and data-driven experience at every touchpoint with their electricity provider. Power companies leveraging AI must demonstrate a clear understanding of these evolving expectations and develop a strategic approach to address them. This could involve employing AI-powered analytics to proactively anticipate customer needs, offer real-time usage insights for cost optimization, or even implement AI-powered chatbots equipped to handle complex inquiries with a human-like touch.
The remaining sub-categories—“customer benefit”, “customer service”, “customer communication automatization”, “customer communication”, “fundament of good service”, and “product improvement”—all contribute to the strategic utilization of AI in meeting these rising expectations and fostering a superior customer experience (CX). By harnessing AI to gain deeper insights into customer needs, automate routine tasks, personalize communication, and analyze customer feedback for product innovation, power companies can leverage AI to create a future where customer interactions are efficient, personalized, and driven by data-driven insights.
In conclusion, the “customer” theme within the electric power industry’s communication regarding AI reflects a strategic focus on comprehending and exceeding evolving customer expectations in the face of AI’s growing presence. This analysis suggests a future where AI plays a significant role in fostering stronger, more positive, and data-driven customer relationships within the industry. However, the success of this future hinges on the ability of AI-powered solutions to deliver on the promise of a truly enhanced customer experience.

3.5. Important Business Area

Our thematic analysis of corporate communications reveals a pivotal theme: the strategic integration of AI as a core facet of the company’s operational landscape. This theme is further nuanced by several sub-categories that illuminate AI’s multifaceted significance. Terms such as “area of investment” and “strategic business area” posit AI as a primary target for resource allocation, suggesting a pronounced emphasis on financial commitment toward its development and implementation. Furthermore, codes like “area of operation” and “one of the key areas of activity” imply a move beyond peripheral utilization, signifying the active integration of AI into the fundamental business functions of the company. Notably, the presence of terms like “area of cooperation for innovation”, “company’s area of innovation”, and “area of research” underscores AI’s role as a catalyst for novel technological advancements and process improvements within the organization. In essence, this theme transcends the mere perception of AI as technology. It portrays AI as a strategic focus area actively shaping the company’s future operational trajectory. This necessitates ongoing investment, fosters a culture of innovation, and ultimately positions AI as a foundational pillar of the company’s core business activities. The frequencies of occurrence of individual codes related to the theme of important business areas between 2020 and 2023 are presented in Table 6.

3.6. Global Trends

Corporate communication within the electric power industry reveals a thematic emphasis on AI as a key driver of global trends (e.g., “megatrend” or “megatrend shaping the world”). Textual analysis using codes associated with this theme positions AI as a transformative force with the potential to be the primary engine of novel value creation within the global economy (e.g., “the main source of new value creation in the economy” or “technology changing the global economy”). This transformation is envisioned as a source of dynamic, significant changes (“source of dynamic, significant changes”), impacting domains such as global economic development (“source of global economic development”) and supply chain innovation (“innovation enabling global supply chain transformation”). The frequencies of occurrence of individual codes related to the theme of global trends between 2020 and 2023 are presented in Table 7.
Furthermore, the analysis suggests that AI is positioned as a critical actor in energy transition, acting as a key technology in the energy transition and potentially even the definitive solution (“answer to the energy transition”) to this pressing global challenge. The integration of AI with the energy sector is believed to be a significant factor accelerating the growth of the energy market (“a factor accelerating the growth of the energy market”), with the potential to create new job opportunities (“new types of jobs”) and provide companies with openings for market expansion (“opportunity for companies to expand their markets”).
In essence, the industry portrays AI as a powerful force for positive change, with the potential to address demographic pressures (“answer to the demographic challenge”) and ultimately improve the quality of life on a global scale (“life improvement”, “key driver of product demand growth”). Analyzing the specific codes used (“megatrend”, “source of global economic development”, “answer to the energy transition”) suggests a strongly optimistic view of AI’s transformative potential within the electric power industry and its role in shaping a more prosperous and sustainable future.

3.7. Legal Framework

Thematic analysis of corporate communications within the electric power industry reveals a focus on the legal framework governing AI integration. This theme unpacks various sub-categories, illuminating the intricate considerations surrounding AI adoption in this critical sector. The frequencies of occurrence of individual codes related to the legal framework theme from 2020 to 2023 are presented in Table 8.
Navigating the existing “area of legal regulation” and potential adaptations within the “EU regulation” framework is paramount. The thematic analysis highlights the need for international standards (“The need for regulation at the international level”) to ensure consistency and address potential cross-border issues.
Consumer protection emerges as a cornerstone principle within this theme. The focus on “consumer protection” indicates a commitment to safeguarding consumer rights and privacy in the face of AI applications within the electric power industry. The potential for algorithmic bias and the need for transparent decision-making processes are likely prominent concerns.
The theme incorporates the complexities of “legal challenges” and ethical considerations. Codes like “human rights” and “human rights in cyberspace” highlight potential legal issues surrounding accountability, liability, and potential human rights infringements, particularly in the context of cybersecurity and data privacy. These considerations necessitate a sophisticated approach that balances innovation with robust legal and ethical frameworks.
Finally, the theme explores intellectual property considerations. “Patent protection” and “patented solutions” suggest a focus on ownership, licensing, and potential conflicts arising from AI development within the electric power industry.
In conclusion, as evident in corporate communications, the “Legal Framework” theme underscores the electric power industry’s recognition of the multifaceted legal landscape surrounding AI. It highlights the need for well-defined regulations, unwavering consumer safeguards, and a focus on ethical considerations to ensure responsible and secure integration of AI technologies. This, in turn, fosters a future-proof electric power grid.

3.8. Data and Digitalization

A conducted study of corporate communications within the electric power industry reveals another vital theme: data and digitalization. This theme sits at the heart of the industry’s strategic discourse and encompasses several interrelated concepts with significant operational and commercial implications. Woven into this narrative is AI’s transformative potential. The frequencies of occurrence of individual codes related to the theme of data and digitalization between 2020 and 2023 are presented in Table 9.
Data are the bedrock of digital transformation, acting as the cornerstone of the industry’s transition to a more digital future. Companies are leveraging data to drive digitalization efforts (digitalization drive), which necessitates the transformation of core business processes (digitalization of business processes). Data are critical for streamlining operations and optimizing efficiency across the entire value chain. However, the sheer volume and complexity of data necessitate advanced analytical techniques. Here, AI presents itself as a powerful tool, enabling companies to extract valuable insights from data that would be difficult or impossible to glean through traditional methods.
The theme further highlights the crucial role of big data management tools alongside AI. The exponential growth of data generated by modern, interconnected power grids necessitates sophisticated tools for collection, storage, and analysis (big data management tools). Effective data management (data management requirements) becomes indispensable to unlocking the full potential of digitalization efforts, particularly when coupled with AI’s processing power.
As reliance on data increases, companies acknowledge the heightened responsibility to ensure its security and privacy (safe data use). This necessitates a focus on developing robust data governance frameworks, fostering trust with consumers, and complying with evolving regulatory landscapes.
The theme delves even more profoundly, exploring the potential for monetization of data-driven services. Digitalization, powered by AI, paves the way for innovative business models (new business models in a digitalizing world, monetization of digital services). Companies can leverage data-driven insights obtained through AI analysis to create and deliver novel customer services, potentially unlocking new revenue streams and fostering competitive advantage. For instance, AI-powered customer segmentation can lead to personalized energy plans or dynamic pricing models.
In conclusion, the data and digitalization theme paints a compelling picture of the electric power industry actively embracing digital transformation, with AI acting as a critical driver. Companies recognize data as a core strategic asset, investing in tools and strategies to effectively manage, analyze, and leverage it. This focus on data and digitalization, powered by AI, reflects the industry’s commitment to a future that is not only more efficient, secure, and reliable but also potentially more profitable. This strategic shift positions the industry to navigate the evolving energy landscape and deliver enhanced value to stakeholders.

3.9. Health and Safety

Thematic analysis of corporate communications regarding AI integration within the electric power industry reveals a theme of health and safety. This theme, encompassing various sub-categories evident in codes like “asset and plant safety”, “asset safety”, “health and safety”, “risk detection”, “safety”, and “work safety”, illuminates the multifaceted role AI plays in this critical domain. The frequencies of occurrence of individual codes related to the theme of health and safety between 2020 and 2023 are presented in Table 10.
Firstly, the theme underscores the potential for AI to augment asset and plant safety (e.g., “asset and plant safety”, “asset safety”). This translates to enhanced security for physical infrastructure. AI-powered predictive maintenance techniques can be utilized to identify potential equipment failures before they occur. This proactive approach mitigates the risk of accidents and safeguards plant integrity.
Secondly, AI’s prowess in analyzing vast, intricate datasets is pivotal in risk detection (e.g., “risk detection”). This sub-category suggests the strategic employment of AI for proactive threat detection—identifying safety hazards and predicting potential incidents before they escalate (e.g., “safety”). This enables the timely implementation of preventative measures, fostering a safer work environment.
Finally, the theme emphasizes AI’s capacity to significantly contribute to work safety (e.g., “work safety”). This could involve implementing AI-powered monitoring systems to detect unsafe work practices in real-time. Developing AI-driven training programs could also equip employees with the necessary safety knowledge and best practices.
In conclusion, the emphasis on health and safety within communication surrounding AI integration underscores a robust commitment by the electric power industry. This commitment prioritizes harnessing the capabilities of AI to drive positive change. By employing AI for proactive threat detection, enhanced asset and plant safety management, and the fortification of work safety practices, the industry strives to create a more secure and reliable work environment for its employees. Ultimately, this ensures continued safe and efficient power generation.

3.10. Risk

Thematic analysis of corporate communications in the electric power industry reveals a multifaceted view of the risk associated with AI implementation. While some communications highlight AI’s potential for risk reduction (e.g., corruption risk reduction, risk management), others acknowledge the introduction of new risk areas (e.g., security risk area, source of legal risk). This duality underscores the need for a comprehensive understanding of both opportunities and challenges presented by AI. The frequencies of occurrence of individual codes related to the theme of risk between 2020 and 2023 are presented in Table 11.
On the positive side, AI is seen as a tool to optimize risk exposure and transaction costs, potentially leading to a more efficient and secure industry. Furthermore, AI can contribute to overall risk reduction by identifying and mitigating existing vulnerabilities.
However, the communications also unveil concerns surrounding potential sources of risk introduced by AI. These include legal liabilities, strategic risks impacting market position, and the possibility of increased competition due to the proliferation of AI-powered solutions.
The most concerning risk area appears to be cybersecurity. The term “security risk area” emphasizes the potential for AI systems to be exploited for malicious purposes, disrupting critical infrastructure or manipulating data.
The theme of risk within the electric power industry’s AI communication portrays a technology with the potential to be both a risk mitigator and a risk introducer. Further research is necessary to develop robust risk management frameworks that capitalize on AI’s benefits while effectively mitigating its potential downsides.

3.11. Ecology

This investigation explores the thematic landscape surrounding AI within the electric power industry and reveals a focus on the “ecology” theme. A nuanced understanding of how corporate communications frame AI’s potential role in environmental considerations is developed by examining a range of codes identified during the thematic analysis. The frequencies of occurrence of individual codes related to the theme of ecology between 2020 and 2023 are presented in Table 12.
Central to this theme are concerns regarding CO2 reduction and decarbonization (“CO2 reduction” and “decarbonization”). These terms highlight the power industry’s critical challenge: mitigating its contribution to greenhouse gas emissions. Corporate communications position AI as a tool for optimizing energy production and distribution, potentially leading to a decreased reliance on fossil fuels and a subsequent reduction in greenhouse gas output.
However, the thematic analysis reveals a broader concern for the industry’s overall ecological impact. Codes such as animal protection, biodiversity protection, and influence on environment (“animal protection”, “biodiversity protection”, “influence on the environment”) suggest an awareness of the potential negative effects of power generation on ecosystems. AI is presented as a potential solution, with capabilities for minimizing such impacts, perhaps through optimizing land use for energy infrastructure or fostering the development of more sustainable energy sources.
Furthermore, the concept of sustainability emerges within this theme. Codes indicative of sustainability and sustainability assistance (“sustainability” and “sustainability assistance”) demonstrate a recognition of the need for a balanced approach that prioritizes both energy production and environmental responsibility. AI is portrayed as a tool for achieving this balance, enabling resource optimization and promoting environmentally sound practices throughout the industry.
Notably, the theme acknowledges the potential for unintended ecological consequences arising from AI. The code “increases energy consumption and CO2 emissions” suggests a concern that some AI applications might lead to inefficiencies or increased energy demand. This underscores the critical need to consider the environmental implications throughout the entire lifecycle of AI development and implementation within the electric power industry (“increases energy consumption and CO2 emissions”).
In conclusion, the “ecology” theme in corporate communications regarding AI in the electric power industry underscores a growing focus on environmental responsibility. AI is positioned as a potential solution for reducing greenhouse gas emissions (CO2 reduction), minimizing ecological damage (animal protection and biodiversity protection), and promoting sustainable practices (sustainability and sustainability assistance). However, a commitment to carefully considering AI’s potential environmental drawbacks (e.g., increases in energy consumption and CO2 emissions) remains equally emphasized. This holistic perspective on AI’s role in the industry paves the way for responsible development and implementation that prioritizes both economic and environmental objectives.

3.12. Policy

The thematic analysis of corporate communications within the electric power industry reveals a distinct focus on policy considerations surrounding AI implementation. This theme encompasses several interconnected aspects. The frequencies of individual codes related to the policy theme between 2020 and 2023 are presented in Table 13.
Firstly, it highlights the emerging area of corporate responsibility in digital trust and security. This suggests that electric power companies recognize the importance of responsible AI development and deployment, acknowledging the potential impact on customer privacy and data security.
Secondly, the theme incorporates the broader concept of an “area of responsibility”, implying that companies view AI governance as an integral part of their overall corporate responsibility landscape. This aligns with the notion of “business policy”, where AI implementation requires policy frameworks to guide ethical and responsible use within the organization.
Furthermore, the theme underscores the strategic importance of AI within the electric power sector. Terms like “Enterprise readiness for the AI world” and “management priority” suggest that companies perceive AI as a strategic lever for optimizing operations and achieving business goals. This strategic focus inevitably leads to considering the “need for regulation”. Companies acknowledge the potential for external regulations to shape the landscape of AI adoption within the industry.
In conclusion, the policy theme in electric power industry communications regarding AI reflects a multi-faceted approach. It acknowledges the need for responsible development, positions AI governance as a corporate responsibility, recognizes its strategic significance, and anticipates the influence of regulatory frameworks. This focus on policy highlights the industry’s proactive stance in navigating the complex landscape of AI integration.

3.13. Cybersecurity

The conducted research reveals a notable focus on cybersecurity, particularly emphasizing the integration of AI for enhanced security. This focus stems from a heightened awareness of “cybersecurity risks” and the “high probability of an increase in cyber threats”. The increasing digitization of power grids, the growing sophistication of cybercriminals, and the potential for AI-powered attacks exploiting these vulnerabilities all contribute to this concern. The frequencies of occurrence of individual codes related to the theme of cybersecurity between 2020 and 2023 are presented in Table 14.
To address these evolving threats, the industry is adopting a proactive approach. Companies are actively exploring AI-powered solutions for “cyber threat detection” and identifying “potential areas of cyberattack”. AI’s ability to analyze vast amounts of data in real-time makes it a valuable tool for identifying anomalous behavior and potential cyberattacks before they can disrupt critical infrastructure. This shift extends beyond traditional security measures, as evidenced by the development of “new cybersecurity models” incorporating AI. These models, potentially developed through collaboration within the industry or with external security firms specializing in AI, can learn and adapt to the evolving threat landscape, further strengthening defenses.
In conclusion, the thematic analysis underscores cybersecurity as a top priority for the electric power industry, with AI playing a central role. The industry’s acute awareness of increasing cyber threats, particularly those potentially powered by AI, is driving the development and adoption of AI-powered solutions. This focus on leveraging AI for proactive measures like “cybersecurity assistance” will be crucial in ensuring the continued reliability and security of the power grid. By integrating AI, the industry positions itself at the forefront of cyber defense strategies, promoting stability and resilience within the critical infrastructure landscape.

3.14. Strategic Advantage

Another prominent theme revealed by thematic analysis of corporate communications within the electric power industry is the strategic application of AI to achieve a competitive edge. This theme is constructed through a network of interconnected codes. The frequencies of occurrence of individual codes related to the theme of strategic advantage between 2020 and 2023 are presented in Table 15.
Firstly, the emphasis on AI as a source of organizational pride (e.g., highlighting advancements in AI development) and a core area of expertise (e.g., emphasizing in-house AI capabilities) positions AI as a critical differentiator for the company. This focus suggests that AI is not merely a technological adoption but a strategic investment to achieve a competitive advantage.
Secondly, using codes related to organizational capabilities (e.g., discussing how AI optimizes internal processes) implies that AI is viewed as a tool for enhancing internal functionalities. This signifies a focus on utilizing AI not just for external market gains but also for internal process improvement and efficiency.
Most importantly, the codes of the source of competitive advantage and leadership in the industry (e.g., statements about gaining market share or superior efficiency through AI) directly link AI to improved market positioning and potential industry dominance. By framing AI through this combination of codes, these communications establish AI as a strategic lever for achieving a sustainable competitive edge and ultimately, leadership within the electric power sector.

3.15. Business Functions

Leveraging thematic analysis of corporate communications within the electric power industry, this study also explores the role and impact of AI on core business functions. The findings reveal a strategic focus on AI applications demonstrably enhancing these functions. The frequencies of occurrence of individual codes related to the theme of business functions between 2020 and 2023 are presented in Table 16.
AI is revolutionizing quality management by enabling real-time, predictive maintenance. AI algorithms proactively identify potential issues before they escalate into outages by analyzing vast sensor and equipment datasets. This minimizes downtime, optimizes equipment performance, and fosters a more proactive approach to asset management.
Furthermore, AI empowers data-driven decision-making across all organizational levels. By analyzing complex information from diverse sources like historical data, weather patterns, and market trends, AI algorithms generate actionable insights for grid management, resource allocation, and power generation optimization. This empowers leadership to make informed decisions that enhance overall operational efficiency.
AI also acts as a powerful tool for knowledge management within the electric power industry. It can process and organize vast amounts of technical data and industry knowledge, creating intelligent knowledge bases. These knowledge bases serve as a critical resource for human experts, facilitating troubleshooting, identifying best practices, and fostering knowledge transfer across the organization. This ensures the preservation and dissemination of critical expertise.
Finally, AI enables a more granular understanding of the customer base. AI algorithms can create highly targeted customer segments by analyzing customer consumption patterns and preferences. This empowers the development of personalized energy plans and pricing structures, leading to improved customer satisfaction, loyalty, and potentially increased revenue streams.
AI empowers electric power companies to achieve significant operational advancements by focusing on these core business functions. Integration of AI fosters increased efficiency, optimizes operations, and enhances customer service. This ultimately translates into a more robust, competitive, and customer-centric market for electricity.

3.16. Ethical Aspect

Another theme revealed revolves around the ethical ramifications of AI integration. Codes like “ethical aspect”, “ethical issues of digitizing”, “ethical risk”, and simply “ethics” dominate this theme, underscoring industry-wide recognition of the inherent threats and opportunities accompanying AI adoption. The frequencies of occurrence of individual codes related to the theme of ethical aspects between 2020 and 2023 are presented in Table 17.
Corporations acknowledge the existence of ethical risks, encompassing concerns around data privacy and security breaches. Another prominent consideration is algorithmic bias, leading to discriminatory energy access and pricing practices. Furthermore, the “black box” nature of certain AI algorithms, where decision-making processes lack transparency, exacerbates ethical anxieties regarding accountability for AI-driven outcomes.
However, the discourse also highlights the potential for AI to advance ethical principles within the industry. AI-powered systems can identify and mitigate potential biases in existing practices, thereby promoting fairness and inclusivity. Additionally, AI can contribute to environmental sustainability by optimizing energy distribution and facilitating the integration of renewable energy sources.
The emphasis on ethical considerations in corporate communications signifies a maturing understanding of AI’s potential impact on the electric power industry. This awareness positions the sector to navigate AI development and deployment responsibly, ensuring the technology is a catalyst for progress rather than a source of unforeseen social or environmental repercussions.

3.17. Commitment of the Organization’s Authorities

Thematic analysis of the identified codes unveils another important theme—the commitment of the organization’s authorities, specifically the board of directors, to fostering an environment conducive to successful AI implementation within the electric power industry. This commitment manifests through a multi-pronged approach. The frequencies of occurrence of individual codes related to the commitment of the organization’s authorities between 2020 and 2023 are presented in Table 18.
Firstly, the codes highlight an emphasis on developing the requisite skillsets at the board level. Phrases such as “management and board member training” and “the need for skills at the board level” suggest recognition that effective AI integration necessitates a board equipped to comprehend and oversee its strategic application.
Secondly, codes like “important experience of the board member” and “Board member’s crucial background” point toward a preference for board members with relevant expertise or a demonstrably strong track record in areas that complement AI adoption. This focus on experience can be interpreted as a strategic measure to bridge potential knowledge gaps and ensure well-informed decision-making regarding AI investments.
Finally, including the “area of interest of the company’s authorities” suggests that a genuine interest in AI at the leadership level is viewed as a critical driver for its successful implementation. This facet of the theme underscores the organization’s commitment to building a foundation for successful AI adoption by ensuring its leadership possesses a confluence of essential skills, relevant experience, and a demonstrably strong interest in this transformative technology. In conclusion, this thematic analysis reveals a deliberate effort by the organization’s authorities to cultivate an “AI-ready” board, a crucial step in navigating the complexities of AI integration within the electric power industry.

3.18. Other

The category “other” captured occasional references to other themes, which, beyond the purely technical considerations, offers valuable insights into the strategic nuances influencing successful AI implementation. The frequencies of occurrence of individual codes related to the category of others between 2020 and 2023 are presented in Table 19.
Analysis reveals a primary emphasis on human–AI interaction, signifying a strategic focus on fostering effective collaboration models within the workforce. Corporate communications likely address potential anxieties surrounding human roles in an AI-powered future, promoting a complementary rather than a replacement dynamic.
Furthermore, the theme highlights the importance of a staged development approach coupled with accelerated technology adoption. This suggests a well-defined strategy that acknowledges AI’s evolving nature. Communications may manage expectations by emphasizing a phased implementation process, ensuring a smooth transition.
Additionally, the inclusion of terms like “glossary” points toward efforts to bridge the knowledge gap. This underscores the need for clear communication and educational initiatives to equip the broader industry workforce with the necessary understanding for seamless AI adoption.
The theme extends to acknowledging the infrastructure prerequisites for AI-powered solutions. Including the “need for sensors” suggests that successful AI integration hinges on the technology and robust infrastructure development.
Strategic considerations are further revealed by the inclusion of promoting AI and public–private partnerships (PPPs) for AI adaptation. This signifies a proactive approach to garnering industry-wide support and exploring collaborative models to overcome potential hurdles. Such partnerships could facilitate knowledge sharing, resource allocation, and risk mitigation during AI implementation.
Finally, the theme underscores the imperative for seamless AI integration. This signals a recognition that successful adoption requires careful consideration of user experience and smooth interaction within existing workflows. Communication efforts likely address potential concerns regarding data security and algorithm transparency, promoting user trust and facilitating efficient integration.
In conclusion, far from extraneous, the “other” theme unveils a nuanced understanding of the critical factors influencing AI integration within the electric power industry. It highlights the importance of human-machine collaboration, staged development, clear communication, infrastructure considerations, strategic partnerships, and a focus on user experience. By acknowledging and addressing these elements alongside the technical aspects of AI, the industry can navigate a more effective and comprehensive path toward successful AI adoption.

4. Discussion

The thematic analysis of corporate communications within the electric power industry reveals a comprehensive thematic landscape surrounding AI. “Practical application” (n = 92) emerges as the most dominant theme, signifying a pronounced industry-wide focus on leveraging AI for tangible solutions. This centrality is closely followed by “business benefits” (n = 52), highlighting a strong emphasis on the economic advantages garnered through AI implementation. Other prominent themes include “human resource management (HRM)” (n = 46), reflecting considerations regarding potential workforce transformations, and “customer” (n = 31), suggesting a strategic intent to utilize AI for enhancing customer experience.
The observed frequency distribution of themes underscores the electric power industry’s pragmatic approach toward AI integration. The dominance of “practical application” signifies prioritizing real-world solutions that can effectively address current challenges and optimize operational efficiency, as other studies also indicate [44,45,46,47]. The emphasis on “business benefits” further aligns with this focus, suggesting a solid commercial rationale driving the adoption of AI within the sector. The dominance of these themes aligns with existing research highlighting the economic motivations for AI adoption across various industries (e.g., [8,9]). This focus on tangible solutions suggests that the electric power industry views AI as a tool to address pressing needs for grid modernization, optimize operations, and potentially achieve cost reductions. Other studies also indicate this [48]. The prominence of “customer” (n = 31) as a theme aligns with literature discussing AI’s role in customer relationship management (e.g., [13]). However, further investigation is needed to understand whether the industry primarily utilizes AI for personalized experiences or enhances service reliability (e.g., through predictive maintenance, as mentioned in the existing literature [32,33]).
Intriguingly, “HRM” emerges as a significant theme, reflecting a proactive acknowledgment of potential workforce transformations due to AI [49,50,51,52]. This suggests a cautious yet thoughtful approach where potential drawbacks are not elided but addressed preemptively. The presence of “customer” as a theme highlights the industry’s recognition of AI as a tool to improve customer service and satisfaction, thus emphasizing a customer-centric perspective, as other publications also point out [53,54].
These findings offer valuable insights into the current discourse surrounding AI within the electric power industry. They portray an industry actively seeking to harness the potential of AI for practical applications, with a keen eye on both economic benefits and potential social considerations associated with its implementation. This focus on tangible solutions, alongside a measured consideration of potential social impacts, suggests a strategic and thoughtful approach to AI adoption within the electric power sector.
Thematic analysis reveals the key themes surrounding AI in corporate communications and the language used to frame those themes. This analysis provides valuable insights into the industry’s overall perception and approach to AI adoption. The language used to discuss “practical application” and “business benefits” often exhibits a positive and tech-forward framing. Terms like “innovative solutions”, “cutting-edge technology”, and “optimized operations” aim to convey the industry’s enthusiasm for AI’s transformative potential. Themes like “data and digitalization” (n = 24) and “business functions” (n = 12) suggest a focus on the functional aspects of AI. The language used emphasizes how AI can automate tasks, improve data analysis, and streamline business processes. These topics are leading in the research of other authors [23,55].
However, the narrative extends beyond pure optimism. Themes like “HRM” (n = 46), “cybersecurity” (n = 16), and “risk” (n = 20) indicate an awareness of potential challenges associated with AI implementation. The language used here explores potential job displacement due to automation, the need for robust cybersecurity measures, and the importance of risk mitigation strategies. Other authors also write in the same context [56].
While the “ethical aspect” (n = 11) emerges as a theme, its relatively low frequency suggests a limited focus on the broader ethical implications of AI. The language used in this context has been more reactive, addressing general concerns rather than proactively considering ethical frameworks for AI deployment. While existing literature emphasizes the need for ethical considerations during AI adoption (e.g., [13,16,17]), the limited focus on corporate communications might indicate a potential blind spot. This could be due to a lack of industry-wide ethical AI deployment frameworks or hesitation to address potential concerns publicly. Further research exploring internal discussions or employee perspectives on AI ethics within the industry might be fruitful [57].
Such ethical concerns as data privacy, algorithmic bias, and the potential displacement of workers require urgent attention. For instance, the use of AI in predictive maintenance and grid management relies heavily on data collection, raising data privacy and security issues. Companies must adopt robust data governance frameworks to safeguard customer information and ensure transparency in data usage. Moreover, addressing algorithmic bias is crucial to prevent discriminatory practices in AI applications. For example, AI systems used for energy consumption forecasting must be designed to avoid biases that could lead to unequal energy distribution or pricing.
Companies can look to established ethical AI frameworks to guide ethical AI practices, such as the IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems [58], which provides guidelines on transparency, accountability, and human-centric values. Additionally, the Asilomar AI Principles [59], which emphasize safety, transparency, and the common good, offer valuable guidelines for ethical AI deployment. By integrating these principles into their AI strategies, companies in the electric power industry can enhance operational efficiency and innovation and build trust with stakeholders by demonstrating a commitment to ethical AI practices.
Overall, the language used in corporate communications seems to balance optimism about AI’s potential and a cautious awareness of potential drawbacks. The industry appears to be framing AI as a powerful tool for optimization and growth while acknowledging the need for thoughtful implementation and mitigation strategies.
The limited discussion on ethics highlights the need for industry-wide conversations on establishing ethical frameworks for AI development and deployment. Future research could explore how existing ethical frameworks from other sectors can be adapted to the electric power industry’s specific context.

5. Conclusions

In conclusion, this study explores how AI is communicated within corporate communications in the electric power industry, the dominant themes and narratives surrounding AI, and how these communications address the benefits and challenges of its implementation. The thematic analysis reveals a multifaceted narrative where the industry prioritizes practical applications and business benefits of AI (e.g., grid optimization, cost reduction), aligning with existing research on economic motivations for AI adoption.
The focus on customer themes suggests potential applications in personalized experiences or service reliability improvements. Interestingly, the industry acknowledges potential workforce transformations through the HRM theme, reflecting a proactive stance on potential social impacts alongside economic gains.
However, the limited discussion on ethical aspects raises concerns about potential blind spots in addressing broader societal implications of AI. This, coupled with the reliance on corporate communications, highlights the need for further research incorporating employee and stakeholder perspectives.
The broader implications of these findings suggest that while the electric power industry is proactive in leveraging AI for operational and environmental benefits, it needs to develop a more balanced narrative that also considers the ethical dimensions of AI integration. This gap highlights the importance of incorporating ethical considerations into AI strategies to ensure responsible and sustainable AI adoption. Future research should focus on exploring internal discussions and employee perspectives on AI ethics to provide a more holistic understanding of AI’s role in the industry. By addressing these ethical concerns, the industry can enhance its AI communication strategies, fostering greater transparency and trust among stakeholders.

Author Contributions

Conceptualization, J.J., P.M.-B., D.C.-M. and B.F.; methodology, J.J., P.M.-B., D.C.-M. and B.F.; validation, J.J., P.M.-B. and D.C.-M.; formal analysis, J.J., P.M.-B. and D.C.-M.; investigation, J.J., P.M.-B. and D.C.-M.; resources, J.J., P.M.-B. and D.C.-M.; data curation, J.J.; writing—original draft preparation, J.J., P.M.-B., D.C.-M. and B.F.; writing—review and editing, J.J., P.M.-B., D.C.-M. and B.F.; visualization, P.M.-B.; supervision, J.J., P.M.-B., D.C.-M. and B.F.; project administration, J.J., P.M.-B. and D.C.-M.; funding acquisition, D.C.-M. and B.F. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors upon request.

Conflicts of Interest

The authors declare no conflicts of interest.

Appendix A

Table A1. Characteristics of the research sample.
Table A1. Characteristics of the research sample.
CodeCountryYear of FoundationOperating RangeForm of the PropertyRevenue (2023)Energy TypeSpecialization
General ElectricUnited States1982InternationalStateUSD 67.95 bn Conventional, nuclear, wind, water, solarEnergy, measuring equipment, the arms industry, aerospace industry, space industry, household appliances industry, plastic and chemical industry, medical equipment, banking, film, rail transport
IberdrolaSpain1992InternationalPrivateUSD 53.17 bn WindEnergy distribution and storage, building, operations, maintaining various electrical infrastructures, supervising huge electricity distribution systems
Vestas Wind SystemsDenmark1898InternationalPrivateUSD 16.58 bn WindManufacturing, selling, installing, and wind turbine maintenance
Schneider Electric SEFrance1836InternationalPrivateUSD 38.7 bn Solar, wind, waterConstruction, metallurgy, electricity, industrial automation, sustainable energy, switchboards, equipment, and energy management systems
China Yangtze Power Co., Ltd.China2002NationalMixedUSD 10.82 bn WaterProducing and selling energy
Enel SpAItaly1962InternationalStateUSD 153.52 bn Geothermal, solar, wind, hydro, thermal, nuclearProducing and distributing electricity and gas
Acwa Power Co.Saudi Arabia2004InternationalPrivateUSD 1.63 bn Solar, wind, waterA combined cycle power plant, solar power, concentrated solar and wind power, desalination plants, green hydrogen projects
Siemens GamesaGermany1976InternationalPrivateUSD 9.81 bn WindManufactures wind turbines, wind energy on land and at sea; services related to operating and maintaining wind turbines

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Table 1. Frequency of each key theme from 2020 to 2023.
Table 1. Frequency of each key theme from 2020 to 2023.
Key Theme2020202120222023SUM
n%n%n%n%n%
Business benefits810.51211.71915.3147.85311.0
Business functions11.343.932.442.2122.5
Commitment of the organization’s authorities00.011.043.252.8102.1
Customers45.354.986.5147.8316.4
Cybersecurity22.632.964.852.8163.3
Data and digitalization56.665.864.873.9245.0
Ecology22.643.943.273.9173.5
Ethical aspects11.321.932.452.8112.3
Global trends22.632.910.82413.4306.2
Health and safety22.698,754.052.8214.4
HRM67.987.81411.31810.1469.5
Important business areas810.565.897.373.9306.2
Legal framework56.654.986.5105.6285.8
Other11.332.954.042.2132.7
Policies22.600.021.6126.7163.3
Practical applications2532.93029.12016.1168.99118.9
Risks22.621.932.4137.3204.1
Strategic advantages00.000.043.295.0132.7
SUM76100.0103100.0124100.0179100.0482100.0
Table 2. Frequency of each code for practical application between 2020 and 2023.
Table 2. Frequency of each code for practical application between 2020 and 2023.
Code2020202120222023
Active search for potential application0010
Automated plants0010
Construction assistance1000
Element of the product offered1100
Energy management1001
Healthcare support111720
Implementation success0020
Improve business development, engineering, construction, operation, and maintenance0010
Improved resource allocation0100
Infrastructure management assistance1000
The instrument used at industrial plants0100
Key technology1100
Key to building intelligent hydropower plants0100
Manage the grid systems flexibly0010
Monetization of assets0001
Optimized management of wind and solar plants throughout their entire life cycle0010
Possible future use cases0020
Radiation prognosis0010
Smart energy management system0010
Storage management0001
Support in maintenance98711
Support operations and reduce risks to people0001
Support the generation, distribution, and retail businesses0001
SUM25302016
Table 3. Frequency of each code for business benefits from 2020 to 2023.
Table 3. Frequency of each code for business benefits from 2020 to 2023.
Code2020202120222023
Acceleration of processes0010
Efficiency improvement2300
Employee assistance0010
Employee benefit0001
Energy and storage efficiency0200
Energy optimization0010
Improve performance0010
Increase in operational efficiency0010
Management in field operative processes0010
Management support0010
Operational efficiency0100
Operations optimization0011
Opportunity0101
Opportunity and disruption0001
Optimization1011
Process optimization0110
Process automatization1100
Production optimization1221
Productivity1116
Source of benefits0012
Source of change in organization management0010
Source of improvements0010
Source of innovation1000
Source of optimization0010
Source of savings0020
Workers assistance1000
SUM8121914
Table 4. Frequency of each code for HRM from 2020 to 2023.
Table 4. Frequency of each code for HRM from 2020 to 2023.
Code2020202120222023
Career management1000
Employee selection0100
Employee training0102
HRM0010
Learning digitization1000
Learning management and career progression0010
New skills necessary2228
Personalized learning0001
Talent acquisition1000
Talent development0010
Talent management1496
Training area0001
SUM681418
Table 5. Frequency of each code for customers from 2020 to 2023.
Table 5. Frequency of each code for customers from 2020 to 2023.
Code2020202120222023
Customer benefit23512
Customer communication0000
Customer communication automatization0110
Customer service0001
Customer expectations1111
The fundament of good service1000
Product improvement0010
SUM45814
Table 6. Frequency of each code for important business areas from 2020 to 2023.
Table 6. Frequency of each code for important business areas from 2020 to 2023.
Code2020202120222023
Area of cooperation for innovation1000
Area of investment2241
Area of operation of the company1000
Area of research0010
Company’s area of innovation3442
Important business area0001
One of the business lines1000
One of the key areas of activity0002
Strategic business area0001
SUM8697
Table 7. Frequency of each code for global trends from 2020 to 2023.
Table 7. Frequency of each code for global trends from 2020 to 2023.
Code2020202120222023
A factor accelerating the growth of the energy market0006
A key technology in the energy transition0001
Answer to the energy transition1000
Answer to the demographic challenge0001
Innovation enabling global supply chain transformation0100
Key driver of product demand growth0002
Life improvement1000
Megatrend0004
Megatrend—a source of opportunities0002
Megatrend shaping the world0003
New types of jobs0100
Opportunity for companies to expand their markets0001
Source of dynamic, significant changes0001
Source of global economic development0001
Technology changing the global economy0001
The main source of new value creation in the economy0111
SUM23124
Table 8. Frequency of each code for the legal framework theme from 2020 to 2023.
Table 8. Frequency of each code for the legal framework theme from 2020 to 2023.
Code2020202120222023
Area of legal regulation0001
Consumer protection1000
EU regulation4323
Human rights0242
Human rights in cyberspace0001
Legal aspect0001
Legal challenges0010
Patent protection0001
Patented solutions0010
The need for regulation at the international level0001
SUM55810
Table 9. Frequency of each code for data and digitalization from 2020 to 2023.
Table 9. Frequency of each code for data and digitalization from 2020 to 2023.
Code2020202120222023
Big data management tool0202
Data management requirements0001
Digitalization of business processes0100
Digitalization drive0010
Element of digitalization1110
Instrument of digital transformation2122
Monetization of digital services1110
New business models in a digitalizing world1000
Safe data use0002
The goal of digital transformation0010
SUM5667
Table 10. Frequency of each code for health and safety from 2020 to 2023.
Table 10. Frequency of each code for health and safety from 2020 to 2023.
Code2020202120222023
Asset and plant safety0100
Asset safety0002
H&S0300
Risk detection0110
Safety0110
Work safety2333
SUM2955
Table 11. Frequency of each code related to the theme of risk from 2020 to 2023.
Table 11. Frequency of each code related to the theme of risk from 2020 to 2023.
Code2020202120222023
Corruption risk reduction1000
Lack of risk0001
Optimizes risk exposure and transaction costs0001
Risk area1100
Risk management0100
Risk of competition0001
Risk reduction0010
Security risk area0020
Source of legal risk0002
Source of risk0006
Source of risk and opportunities0001
Strategic risk regarding market position0001
SUM22313
Table 12. Frequency of each code related to the theme of ecology from 2020 to 2023.
Table 12. Frequency of each code related to the theme of ecology from 2020 to 2023.
Code2020202120222023
Animal protection0010
Biodiversity protection0010
CO2 reduction0012
Decarbonization0100
Ecology0001
Ecological policy instrument0001
Greenhouse gas emissions management1100
Increases energy consumption and CO2 emissions0001
Influence on environment0001
Sustainability0211
Sustainability assistance1000
SUM2447
Table 13. Frequency of each code related to the policy theme from 2020 to 2023.
Table 13. Frequency of each code related to the policy theme from 2020 to 2023.
Code2020202120222023
Area of corporate responsibility in the field of digital trust and security1000
Area of responsibility1000
Business policy0027
Enterprise readiness for the AI world0001
Management priority0001
Need for regulation0001
Strategic priority0002
SUM20212
Table 14. Frequency of each code for cybersecurity from 2020 to 2023.
Table 14. Frequency of each code for cybersecurity from 2020 to 2023.
Code2020202120222023
Cybersecurity assistance2151
Cyber threat detection010
Cybersecurity risk0001
High probability of an increase in cyber threats0001
New cybersecurity model0111
The potential area of cyberattack0001
SUM2365
Table 15. Frequency of each code for strategic advantage from 2020 to 2023.
Table 15. Frequency of each code for strategic advantage from 2020 to 2023.
Code2020202120222023
Organizational capabilities0010
Source of competitive advantage0023
Source of leadership in the industry0012
Source of pride for the company0001
The company’s area of expertise0003
SUM0049
Table 16. Frequency of each code for business functions from 2020 to 2023.
Table 16. Frequency of each code for business functions from 2020 to 2023.
Code2020202120222023
Customer segmentation0001
Decision process support0112
Knowledge management assistance1100
Quality management0221
SUM1434
Table 17. Frequency of each code for ethical aspects from 2020 to 2023.
Table 17. Frequency of each code for ethical aspects from 2020 to 2023.
Code2020202120222023
Ethical aspects00 1
Ethical issues of digitizing—threats and opportunities from AI1222
Ethical risk0011
Ethics00 1
SUM1235
Table 18. Frequency of each code for the commitment of the organization’s authorities from 2020 to 2023.
Table 18. Frequency of each code for the commitment of the organization’s authorities from 2020 to 2023.
Code2020202120222023
Area of interest of the company’s authorities0100
Board member’s crucial background0010
Important experience of the board member0012
Key position related to AI0001
Management and board member training0012
The need for skills at the board level0010
SUM0145
Table 19. Frequency of each code related to the category of others from 2020 to 2023.
Table 19. Frequency of each code related to the category of others from 2020 to 2023.
Code2020202120222023
AI–human interaction0001
Developmental step0100
Glossary0041
Need for sensors0010
New technology0100
PPP for AI adaptation1000
Promoting AI0001
Technology adaptation acceleration0001
The need for seamlessness of AI0100
SUM1354
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MDPI and ACS Style

Chmielewska-Muciek, D.; Marzec-Braun, P.; Jakubczak, J.; Futa, B. Artificial Intelligence and Developments in the Electric Power Industry—A Thematic Analysis of Corporate Communications. Sustainability 2024, 16, 6865. https://doi.org/10.3390/su16166865

AMA Style

Chmielewska-Muciek D, Marzec-Braun P, Jakubczak J, Futa B. Artificial Intelligence and Developments in the Electric Power Industry—A Thematic Analysis of Corporate Communications. Sustainability. 2024; 16(16):6865. https://doi.org/10.3390/su16166865

Chicago/Turabian Style

Chmielewska-Muciek, Dorota, Patrycja Marzec-Braun, Jacek Jakubczak, and Barbara Futa. 2024. "Artificial Intelligence and Developments in the Electric Power Industry—A Thematic Analysis of Corporate Communications" Sustainability 16, no. 16: 6865. https://doi.org/10.3390/su16166865

APA Style

Chmielewska-Muciek, D., Marzec-Braun, P., Jakubczak, J., & Futa, B. (2024). Artificial Intelligence and Developments in the Electric Power Industry—A Thematic Analysis of Corporate Communications. Sustainability, 16(16), 6865. https://doi.org/10.3390/su16166865

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