Journalists’ Perspectives on the Role of Artificial Intelligence in Enhancing Quality Journalism in Greek Local Media

Abstract

The transformative influence of digitalization on journalism is evident across multiple dimensions of the industry. Artificial Intelligence (AI) is reshaping how news is produced, distributed, and consumed, from small local newsrooms to global media organizations, offering benefits such as increased speed, efficiency, and personalization. However, the most critical role AI can play lies in upholding the high standards of accuracy, credibility, and depth that define quality journalism. The ongoing digital transformation prompts a re-evaluation of journalistic norms and practices, positioning quality at the forefront of discussions. This paper focuses on Greece’s media market that encountered a severe economic crisis and, more specifically, to the Greek local media landscape to investigate the complex relationship between AI and journalism in regional media organizations. More specific, the study explores how Greek local journalists believe AI can contribute to quality journalism, while upholding the core principles of ethics and integrity. It highlights their perspectives on AI, exploring both their hopes for its potential to improve journalistic practices and their concerns about its impact on journalistic values. Through semi-structured interviews with local media industry stakeholders in Greece—including editors, editors-in-chief, and journalists—this study assesses AI’s influence on journalistic quality in local newsrooms. The findings underscore the necessity of employing AI to elevate content standards rather than compromise them. Our research contributes to the discourse on AI in journalism and offers valuable insights for journalists, local news organizations, and policymakers navigating the ethical implications of AI adoption in the pursuit of high-quality journalism in Greek local media.

1. Introduction

1.1. Background on AI in Journalism

In recent decades, Artificial Intelligence has been widely applied and developed in a variety of research domains, including multidisciplinary approaches that concentrate on media and communications, thanks to advancements in algorithms, data processing capabilities, and Machine Learning (ML) architectures [1]. From automating video/Web-TV streaming procedures to providing advanced content management, AI can be utilized in journalism to carry out a range of tasks that are positioned in every stage of the reporting process [2]. As noted in Arguedas et al. [3], Generative AI, like Large Language Models (LLMs), can personalize news delivery, but may also strengthen existing biases, posing risks to democratic processes. Furthermore, talks about AI’s role in journalism show a mixed outcome, where automation could help with routine tasks, but also weaken human oversight and ethical norms in reporting, as shown by the research in Cools et al. [4]. So, this study aims to examine if journalists themselves consider that AI can be a tool for trustworthy journalism.

The core of good journalism is its focus on accuracy, fairness, and accountability, which is important for building public trust. An important part of this is carefully checking information before it is shared, seen in tools like the Truthmeter, which helps assess the trustworthiness of social media users to make journalist verification easier [5]. Additionally, quality journalism needs to be aware of ethical issues brought on by new technologies; for example, biases in algorithms can affect objectivity and create misleading stories that focus more on sensationalism than on facts. As the media world changes, knowing the difference between trustworthy journalism and less reliable content is more important, especially concerning the spread of misinformation [6]. Therefore, a continuous commitment to ethical practices, clear source transparency, and a focus on detailed storytelling are important for journalism that is both informative and reliable.

Artificial Intelligence consists of many technologies that imitate human thinking, such as learning, reasoning, and problem solving. Its importance in journalism has been shown through both the benefits and difficulties it provides. AI can improve productivity by performing repetitive tasks, which lets journalists work more on investigation and in-depth analysis. However, it also raises concerns about the honesty and transparency of how information is gathered [7]. Journalists are concerned about these issues; so, it is important to find a way to ensure that AI tools help rather than harm the ethical guidelines of the field. Moreover, as noted in the News Futures 2035 initiative, keeping trustworthy news that serves the public requires teamwork among people in the industry to use AI technologies properly [8]. By managing these challenges, AI could be crucial in promoting quality journalism that serves the public good.

The current state of journalism is marked by a complicated mix of new technology and ethical issues. The way news is created and disseminated has changed significantly with the advent of digital platforms and AI technologies. For instance, newsrooms are using Generative AI to automate content creation and customize information for specific audiences, thus altering conventional journalism processes.

However, these changes have raised serious concerns about misinformation and reporting authenticity. According to Sultan et al. [9], large digital companies have a strong influence on news visibility, indirectly influencing public opinion, while making it more difficult for smaller news outlets and potentially endangering media diversity. As journalists deal with this changing landscape, the need for ethical rules and a dedication to unbiased reporting is becoming more important. The current situation in journalism shows a critical need for a balanced strategy that uses technology to build trust while maintaining journalistic integrity [9].

In the rapidly changing world of journalism, trust and quality are essential. Both characteristics affect the way audiences see and engage with the news, influencing what information they accept and trust. Additionally, in places like Uganda, the use of AI has been limited, mostly led by individual journalists and not by broader organizational systems, which reduces the chances for good reporting [10]. Trust in journalism ultimately depends on ethical and consistently high-quality practices; so, we must talk about how technology could support these ideals. The human aspect, which is essential for high-quality journalism and public trust, should be strengthened by AI rather than replaced.

1.2. Purpose and Contribution of the Study

As journalism becomes more involved with Artificial Intelligence, the effects on ethics and public trust are significant. The use of AI tools, like automated news writing and content sorting, has changed how content is created and how audiences engage [11]. To manage this changing environment, media groups need to think about working together on verifying information and applying ethical AI practices, ensuring that progress does not harm the integrity and trustworthiness of journalism [5]. Moving ahead will require a united effort to combine new technology with classic journalism standards, creating an environment where AI enhances, not harms, quality journalism.

There are several advantages and opportunities for improving quality journalism with the use of AI. By automating repetitive tasks, like content creation, information gathering, and fact-checking, tools like Reuters’ News Tracer provide journalists early access to breaking news. By automating the creation of structured content, tools such as robot journalism relieve journalists while preserving factual precision. Additionally, as AI examines feedback and trends to customize stories that appeal to varied demographics, audience engagement is improved [12].

According to Opdahl et al. [12], AI’s potential extends to trustworthy content creation by making it possible to compose stories from validated and reusable content pieces, by ensuring integrity and coherence through metadata generation and context representation. It promotes diversity in reporting by recognizing different perspectives on events and using sentiment and stance analysis to expose biases and provide balanced narratives. Also, by enabling the production of tamper-proof certificates for news articles, proactive verification approaches like blockchain and hashing improve legitimacy and audience confidence. AI’s integration of real-time data streams transforms real-time reporting by providing precise and timely updates, which are essential in situations that change quickly. Furthermore, AI can adapt stories across platforms while preserving quality and engagement thanks to contextual and multimodal storytelling. Lastly, by detecting and reducing biases and protecting privacy with features like automated face-blurring for delicate images, AI helps ethical journalism [12].

Understanding the implications of AI in journalism is crucial for journalists, media organizations, and policymakers. This study will contribute to ongoing debates by providing insights that balance the opportunities AI offers with the ethical and professional standards needed for trustworthy journalism. It aims to guide local news organizations in adopting AI technologies in a manner that supports the public’s need for accurate and unbiased information, bolstering the credibility of the media in a rapidly changing information ecosystem.

This research will focus on journalists’ perspectives regarding the applications of AI in news production and editorial decision-making within established local media organizations. While it will touch on the broader use of AI for content distribution and audience engagement, the primary emphasis is on how journalists believe AI can contribute to and support quality journalism. The study’s scope is limited to qualitative analyses based on interviews and the literature review, and it does not include quantitative data or experimental results.

2. Literature Review

The adoption of Artificial Intelligence in journalism has evolved significantly in recent decades. Initially, AI was used for basic tasks such as automated data sorting and fact-checking, which paved the way for more advanced applications, including Natural Language Processing (NLP) and Machine Learning (ML) [13]. By the 2010s, most media organizations had started using AI tools not only to support data analysis but also to create news summaries and reports with minimal human intervention [14].

Early implementations, such as Quakebot by the Los Angeles Times, showed how automation can be used for generating news updates on events like natural disasters [15]. This success led to further exploration into how AI could complement journalistic capabilities, enhancing speed and efficiency while maintaining reporting accuracy. However, these advancements also brought up some concerns regarding the extent to which AI could be trusted to uphold journalistic integrity [16].

It has been argued that quality journalism can be identified by its commitment to certain principles, including the truth, fairness, and the production of in-depth news stories [17]. These values ensure that the public receives reliable and unbiased information. As AI becomes more prevalent, maintaining these standards presents new challenges. For example, while AI can aid in generating content and managing large datasets to support in-depth investigative reporting, there is a concern that dependence on such techniques may lead to neglect of the essential human elements that define quality journalism [18].

One of the main ethical challenges related to AI in journalism is algorithmic bias. Algorithms are trained on data that may inherently carry societal biases, which can result in distorted reporting or unintentional support of stereotypes [19]. Additionally, the use of AI in newsrooms raises concerns about transparency, as the decision-making processes behind automated content generation often lack clarity. Ensuring ethical AI practices requires that media organizations remain vigilant in evaluating and monitoring AI systems [20].

Misinformation and disinformation raise additional ethical dilemmas. While AI can be used to combat fake news through enhanced fact-checking systems [21], it can also be used to spread disinformation on the inside [22]. This dual-use nature of AI technologies requires careful regulation and supervision to prevent their misuse.

The integration of AI into newsrooms has changed the role and responsibilities of journalism. Journalists need to adapt to an increasingly technologically improved work environment, developing skills that blend traditional reporting with data analysis and AI literacy [14]. This shift has resulted in the creation of new professional roles, such as impact editors and platform editors, tasked with overseeing AI-driven processes. According to Jamil [23], it is really important for journalists to realize that newsroom duties are changing as certain digital skills are inserted in the newsrooms, and they should seek this new knowledge in order to be more qualified and more competitive in the job market.

However, the reliance on automated tools can also reduce human oversight, especially in content creation, where AI might prioritize speed over depth and nuance. The presence of synthetic media—news content produced without any direct human involvement—further complicates the relationship between AI and journalism, raising questions about authenticity and trustworthiness [24].

Despite the growing body of literature on AI in journalism, gaps remain, especially in understanding how different cultural and organizational contexts affect AI adoption and ethical standards. Studies that focus on how smaller, non-Western newsrooms navigate the integration of AI, as well as continued analyses on AI’s long-term impacts on news quality, are still underrepresented [25].

2.1. The Role of AI in Enhancing Quality Journalism

2.1.1. Defining “Quality Journalism”

If one agrees with the concept that quality represents the ability of journalism to perform its duties, then, improving the quality of journalism will improve people’s ability to understand the chaotic world around us. Quality journalism interprets, analyzes, and strives to provide meaning to all the babbling that is taking place [26]. “Quality journalism” measurements are crucial, but defining and measuring “quality journalism” makes them more difficult. There are no universal standards established, and often, the meaning of the term “quality journalism” varies from individual to individual based on their cultural, social, economic, or educational backgrounds [27]. “Quality journalism” follows fundamental principles such as accuracy, objectivity, and ethical reporting. It serves as a watchdog, by offering contextual information and in-depth analysis [28]. However, maintaining “quality journalism” in a digital world that is changing rapidly, is extremely difficult. A number of recent theoretical contributions, including those by Bogart [29], Picard [30], McQuail [31], and Ramirez de la Piscina et al. (2015), are noteworthy for their attempts to define “quality journalism”. After three years of research and study, Bill Kovach and Tom Rosenstiel listed nine principals that are essential to the journalism profession in their book The Elements of Journalism [32]. This list of nine principles is currently accepted as the industry standard in Western countries. Therefore, a journalist must deliver the following in order to provide people with the information they need: (1) the truth is journalism’s first responsibility, (2) its citizens are its first priority, (3) its discipline in verification is essential, (4) its practitioners need to remain apart from the subjects they are covering, (5) it needs to function as a stand-alone power meter, (6) it needs to provide a forum for citizen compromise and criticism, and (7) it should aim to make the noteworthy engaging and pertinent, (8) keep the news balanced and complete, and (9) allow its practitioners to follow their own conscience. Because of the authors’ beliefs, terms like objectivity, fairness, and balance are not on this list. The fundamental principles of accuracy, independence, fairness, public interest, transparency, and accountability are essential to maintaining an informed and engaged citizenry. However, the challenges journalism faces in the digital age threaten its sustainability.

2.1.2. AI and Quality Journalism

In recent years, the use of Artificial Ιntelligence has revolutionized the way news is gathered, bringing benefits and issues for journalism. AI tools can help in the analysis of large datasets and in data mining to identify trends and key information faster than previous methods. Still, there are worries about accountability and the risk of false information. For example, research shows that audiences often find AI-generated news less reliable, even if it is just as accurate or more accurate than news created by humans [33]. This doubt emphasizes the importance of being open about using AI in journalism. Sharing details about the sources and ways AI creates content can help alleviate trust concerns. Finally, while AI has the potential to enhance the newsgathering and quality of journalism, it should be employed with considerable caution and regard to the ethical and professional standards of journalism, presenting it as an area that requires further examination [9].

Journalism has changed considerably with the adoption of automated reporting, which enables quick and accurate content creation in an efficient way. This technology uses algorithms and AI to create articles based on inputs such as sports scores and financial documents, so that journalists can focus on deeper investigative reporting. Recent studies show that, while Generative AI improves personalized content, it raises concerns about accuracy and the risk of misinformation [34]. As these automated systems become an essential part of media operations, it is important to balance technological advancements with responsible journalism by creating a media landscape that meets audience needs while maintaining the core values of trust and quality in the field.

Using AI tools for data analysis and fact-checking is becoming increasingly important in journalism, especially as the rise in misinformation creates considerable challenges. These tools help journalists by making the boring job of sorting through data easier, letting them focus on creating stories that are both informative and interesting. However, the use of AI in journalism raises concerns about values like truth and objectivity. Research has looked into how journalists view this issue, highlighting the need for AI systems to meet professional standards to help maintain the integrity of news reporting [35]. By integrating ethical standards into the development of AI, we can ensure these tools help fact-checking and keep the vital examination of information needed for quality journalism [36]. Therefore, AI tools can improve journalistic work while still respecting the values of reliable reporting.

Artificial Ιntelligence is transforming investigative journalism by making workflows easier and improving the ability to research deeply. By using algorithms to analyze complex data, reporters can find patterns and links that may not be seen otherwise. For example, Journalistic Knowledge Platforms (JKPs) use AI and knowledge graphs to automate boring tasks like metadata tagging, greatly cutting down the time needed for background checks and content verification [37]. This technology not only leads to better insights but also meets the changing needs of audiences for quick and reliable news. Therefore, as AI helps investigative work, it marks a new period where innovative tools improve journalism instead of hurting it.

2.2. Challenges and Ethical Concerns

Using Artificial Intelligence in collecting news brings many challenges that can reduce its benefits. A major problem is the possibility of misinformation: although AI tools can quickly analyze large data, they often do not have the understanding that human reporters do. This lack can result in spreading false stories or unverified information, worsening the issue of fake news in the media. Additionally, ethical issues arise, as AI systems can carry biases from their training data, which might distort news coverage and limit diverse viewpoints. Recent research shows that keeping good journalism requires clear and responsible AI practices while working on fixing existing biases [9]. In the end, addressing these challenges is essential to make sure that using AI does not harm the quality of news, as traditional journalistic standards are crucial for building public trust [12]. So, the real issue is not the technology itself but how it is designed and used. By including journalistic values in AI systems, it is possible to maintain quality in content creation while still using the advantages that these technologies provide.

AI algorithms in news delivery systems change how audiences interact with information, but they create difficult issues for keeping editorial integrity. Algorithms customize news by looking at personal likes and showing relevant content. However, this could lead to filter bubbles that limit users’ views. Research shows that the editorial choices found in traditional media are now replaced by algorithm-driven suggestions from software engineers and product managers, making accountability harder [38]. This shift highlights a key conflict between user engagement and the risk of greater polarization in the information ecosystem. McLuhan’s concept of Technological Determinism provides a useful framework for understanding this transformation better. According to McLuhan, media technologies do not only assist journalistic work but actively reshape the structure and nature of news production. As AI becomes increasingly integrated into journalism, it influences not only content creation but also public perceptions of credibility, audience engagement and ethical concerns regarding news automation [39]. Additionally, while AI can make reporting more efficient, it also leads to dependence on tech companies, forcing media leaders to carefully balance using AI’s strengths with maintaining journalistic values. In the end, successfully using AI for news personalization must focus on transparency and responsibility to support a reliable and high-quality journalism environment [40].

The growth of Generative AI has raised worries about fake news, which threatens the main ideas of journalism [41]. As AI-made content becomes better, it becomes tricky to distinguish what is created by people and what is produced by machines. This makes strong media literacy education important so that people can think critically and handle this new reality. Looking at how AI and journalism interact shows that raising ethical awareness is key to reducing the dangers of AI-driven fake news campaigns [42]. Also, rules for transparency, like those suggested in Article 52 of the draft EU AI Act, are important for making AI developers accountable and ensuring that content creators clearly explain where their information comes from [38].

In the current digital environment, engaging audiences and building trust are essential for journalism’s survival, and AI provides new ways to reach these objectives. By using AI tools, news organizations can look at audience likes and actions, which helps in delivering content that fits individual tastes. A study on local print media shows that only 25 percent of journalists in Uganda are using AI, showing a clear need for training and support to improve AI use in journalism [10]. Additionally, the economic challenges that traditional news outlets like the Chicago Tribune and Chicago Sun-Times face highlight the need for digital advancements to boost audience engagement [43]. As newsrooms start using AI techniques, they can create stronger links with their audiences, leading to more trust and a stronger media environment focused on quality and integrity. A study on how deepfake technology affects public views shows that keeping information honest is very important, especially in serious situations with famous people like Taylor Swift [44].

Additionally, it is important to take a balanced approach that includes ethical and legal views for the successful use of AI in this area. With its ability to not just find but also explain disinformation, AI is a key partner in supporting trustworthy journalism and safeguarding democratic discussion in our digital world [45].

The use of Artificial Intelligence in journalism opens new ways to build trust through better communication methods. By using AI-driven algorithms, news companies can provide greater openness in their reporting, which can boost audience confidence. For example, research from the University of Barcelona shows that, when AI works with 5G and IoT devices, it can change how news content is made and shared, leading to more accurate and timely reports [46].

2.3. AI in the Greek Local Newsrooms

One of the paradoxes of the Greek media ecosystem is the excess of supply over demand [47], which has led to the development of the Greek media within a clientelist structures [48].

While “regional media” was introduced by Demertzis and Skamnakis in 1998, the term “local media” has been used frequently in the Greek context to describe media outlets that operate inside the borders of the former regions, an administrative division. Since they interpreted “local” and “regional” as referring to a dynamic relationship rather than a fixed geographic location, they used the terms equally in their work [49]. Regional/local media frequently displayed traits related to language or minority distinctions, as the same study noted. These media outlets have historically served as channels of communication for particular social groupings, emphasizing the proximity factor and concentrating on topics that were especially pertinent to the local community. The Digital News Report 2024 [50] states that Greece has the lowest levels of trust in news across 47 markets. However, the proximity factor is responsible for the higher degree of trust in Greek local and regional news compared to other specialized brands assessed.

Studies reveal a disparity in AI usage and competence between big and small businesses. In particular, The Associated Press survey on the AI willingness of US local newsrooms found that a lack of technological, financial, and human resources prevent the widespread adoption of such technologies [51]. Another way to understand better this variation is through Rogers’ Diffusion of Innovations Theory, which explains how new technologies spread within the communities [52]. According to this theory, technical adoption happens in stages, moving from early adopters to the majority and finally to the laggards. Local newsrooms, especially in financially constrained environments like Greece, may face challenges in adopting AI, due to limited sources, resistance to change, or lack of institutional support. A comprehensive understanding of where Greek local journalists fall withing this adoption curve will help to contextualize their attitudes toward AI integration in their journalistic workflows.

Although the existing research has explored AI’s role in journalism broadly, there is limited literature on how local journalists perceive and adopt AI in resource- constrained environments, especially in Greece. Studies on AI in newsrooms have largely focused on major international media organizations, leaving a gap in understanding the specific barriers, ethical concerns, and professional attitudes of journalists in smaller, local outlets.

Therefore, to identify the various issues that local newsrooms face, it is important to examine if and to what extent AI can support local news providers in enhancing their journalism and maintaining their companies. Considering the impact of emerging technologies on journalism, this study aims to provide a better understanding of how Generative AI is used in local newsrooms and to map out how journalists are using generative AI in their everyday workflows.

Thus, this paper seeks to explore the following primary research question (RQ):

RQ1: How do local media journalists think AI can be used to uphold and even improve the standards of quality journalism?

3. Materials and Methods

The choice of Greece was based on a number of specific characteristics mentioned above, which make it suitable for this study. Greece is not a country that directly adopts new technologies or trends. This makes it an ideal testing ground for tools designed to help businesses that are not technologically advanced. Also, Greece’s media market has unique characteristics, such as strong fragmentation, traditional practices combined with a gradual adoption of digital solutions, and often greater influence of the traditional press than in other countries. Greece’s local media are small-scale and financially constrained and lack the resources necessary for investigative reporting. These difficulties underscore the necessity of regenerating local journalism, an endeavor in which AI might be extremely helpful.

So, in order to address our research question, semi-structured interviews were conducted with journalists working in Greek local media, mainly newspapers. Semi-structured interviews were chosen for their flexibility, allowing for both consistency in dealing with key points and adaptability to follow up on topics of interest during the interviews.

3.1. Participant Selection

Participants were selected using purpose sampling to ensure that the study obtained insights from individuals with direct experience in local journalism.

A total number of 8 journalists participated in the study, representing a range of roles within their organizations, including editors, managers, and publishers. Among them, 5 were men and 3 were women. The average age of participants was 44 years and their educational backgrounds included degrees in journalism and/or in related fields, while their professional experience ranged from 15 to 29 years, providing insights from both early-career and seasoned journalists. The journalists represented a variety of local media outlets, as presented in

Table 1. Greek local media.

Greek Local Media	Website	Region
Haniotika Nea	https://www.haniotika-nea.gr/ (accessed on 5 December 2024)	Crete
Trikala Voice	https://www.trikalavoice.gr/ (accessed on 16 December 2024)	Thessaly
Xanthi Nea	https://www.xanthinea.gr/ (accessed on 19 December 2024)	Eastern Macedonia and Thrace
Empros Xanthi	https://empros.gr/ (accessed on 20 December 2024)	Eastern Macedonia and Thrace
Thraki Nea	https://www.thrakinea.gr/ (accessed on 20 December 2024)	Eastern Macedonia and Thrace
Pame Evro	https://pameevro.gr/ (accessed on 21 December 2024)	Eastern Macedonia and Thrace
Xronos Kozanis	https://xronos-kozanis.gr/ (accessed on 23 December 2024)	Western Macedonia
Makedonia	https://www.makthes.gr/ (accessed on 23 December 2024)	Central Macedonia

. Efforts were made to achieve gender and geographic diversity within the sample, reflecting the landscape of local journalism in Greece.

3.2. Data Collection

The interviews were conducted in December 2024 via Zoom, each interview lasted approximately 20 min, and all interviews were in Greek to ensure participants could express themselves fully and comfortably. With the participants’ consent, each interview was recorded, transcribed, and subjected to a thematic content analysis.

The interview guide designed ad hoc for this research was customized to address specific aspects of journalists’ experience and expertise. The guide consisted of the following sections:

• Participants’ perceptions of AI and its applications in journalism.
• Current use of AI tools or technologies in their daily work.
• Potential benefits and challenges of integrating AI in local journalism.
• Ethical considerations and implications for journalistic integrity and trust.

In order to conduct a thematic analysis to identify and interpret patterns within the interview data, the first step was to become familiar with the empirical data by reading all the transcribed interviews [53]. NVivo was used to systematically code various features across all the dataset. While most of the initial codes were mainly descriptive/organizational [54], the rest of the analysis process consisted of collating these codes into potential themes with the help of the theoretical framework of the study. Therefore, the analysis process can be described as abductive, which is defined as a combination of induction and deduction [55].

The study followed ethical guidelines to ensure the integrity of the research process and to protect the participants based on the Research Ethics Committee of the Aristotle University of Thessaloniki1. Before participating, all journalists received an email detailing the purpose of the research, their rights, and how their data would be used. Informed consent was obtained from all participants. To ensure confidentiality, respondent names were anonymized and assigned identifiers that are linked to the respective news outlets.

Although qualitative methods provide rich insights, further testing is needed to prove if the findings can be generalized beyond the Greek local news media context. Furthermore, the participants’ familiarity with AI technology varied, and this may affect more detailed discussions on some topics. These limitations are acknowledged and were considered when interpreting the results.

3.3. Results

The findings of this study highlight the early adoption and experimentation with AI tools among journalists in Greek local media. Most interviewees described themselves as early adopters, saying that both they and their media organizations are in the early stages of experimentation with Generative AI tools.

3.3.1. Improving Quality with AI Tools

The participants mentioned that AI tools can significantly improve the quality of journalism. By providing access to large amounts of data and information, these tools can help journalists to achieve better accuracy and depth in their reporting, as Participant 3 highlighted: “Because I’ve saved a significant amount of time from tasks that within quotes are “a waste of time”, like the ones I described earlier and that enables me to focus more on reporting”. The interviewees noted that AI aids the processing of large datasets, allowing for a faster and more efficient analysis. More specifically, Participant 7 said: “You can process a large amount of data with Artificial Intelligence and let’s say, come to a conclusion to get a news story that you wouldn’t get it otherwise”. This ability helps journalists to present complex information in a more understandable and accessible way for their audiences.

Additionally, the speed and ease of data processing with AI tools were seen as a major advantage, enabling journalists to meet tight deadlines while maintaining the quality of their work. These benefits highlight the role of AI as an important tool in elevating journalistic standards, particularly in investigative and data-driven reporting. As Participant 8 referred: “AI tools have significantly changed the way we work, particularly for investigative articles. They enable us to swiftly process vast volumes of data, which is quite beneficial when we have short deadlines”. Also, with the help of AI tools, journalists can maintain greater standards of credibility and trustworthiness without sacrificing speed, as Participant 1 mentioned: “It (AI) can help let’s say, to cross-check a piece of information to see if it’s valid. So yes, that, that could be very helpful to us because it’s a time-consuming thing to do and the way journalism is practiced now, everything is done very quickly, and that is undermining the quality of our work”.

In addition, several participants pointed out that the use of Artificial Intelligence tools had contributed significantly to improving the quality of the content they produced. On the one hand, it saved them valuable time during time-consuming processes, such as transcribing interviews and transcribing information, while, on the other hand, it facilitated processes such as spell-checking and language editing of texts. As Participant 3 said: “I’ll tell you first what happens in my own case I feel that AI has helped me to provide better content to my readers. Why? Because I can do more quality reporting or be able to offer more and more substantive news, as with AI tools I save time, in tasks related to organizing the material that I receive in editing press releases and reading material, which would otherwise take me a lot of time”. The participants stressed that these tools allow journalists to focus more on the creative and analytical aspects of their work, enhancing the quality and validity of the content. However, they emphasized strongly that the final checker remains the human, as AI, although useful, is not infallible and can lead to errors that require human intervention for correction and final evaluation. More specifically, Participant 4 said: “We use the ChatGPT every day for editorial spell checking. This doesn’t mean that the position of editor has been eliminated, the final filter is always the person”.

3.3.2. AI Adoption in News Reporting

When the participants were asked about using AI tools in the news reporting process, the majority of them pointed to practical and immediate uses. ChatGPT was the most frequently mentioned tool, used mainly for drafting content and brainstorming ideas. AI-powered transcription services were also noted as popular and useful application, making the process of converting recorded interviews into written text— typically a time-consuming task in traditional workflows. More specifically, Participant 7 said: “The only tool I use in the process of writing a news article and so on is a tool that helps me in transcription”.

Additionally, two respondents mentioned that they have used or are using AI tools for editing or creating images, as Participant 6 highlighted: “I’m working on quite a few AI tools that are related to the photos that we use in the newspaper, not to create them, but to make them a little bit better, so that I don’t go through the process of opening up Lightroom”. This suggests a growing trend in using AI for visual storytelling and multimedia production, although such uses are much less common than text-related applications.

Interestingly, two participants had not yet used AI tools, mentioning either a lack of familiarity or uncertainty about their actual benefits. This indicates different adoption levels, even among journalists who identify themselves as early adopters. More specifically, Participant 1 said: “I don’t use (AI tools) to tell you the truth yet; I mean, I’m skeptical about that”, while Participant 5 mentioned that “I barely use Artificial Intelligence tools”.

A common theme was the use of AI tools for data collection and initial fact-checking. As Participant 2 stated: “It (AI) can help us initially in gathering information…in terms of our website and personally I use it (AI) mainly in collecting data”. While the participants recognized the efficiency that these tools can bring to gathering information, they expressed doubts about trusting AI for verification. Several interviewees emphasized that AI tools often lack the nuanced judgment required for thorough fact-checking, especially when dealing with context-specific information. Participant 6 highlighted: “So, my reporter will find out an information, will cross check it with an AI tool and once he ties it up, he will pass it to me and I will look for the sources and my sources to see that it is indeed true, and then a third person, who is not from the newspaper, and that’s important, because he/she has a different perspective, he/she will confirm it. We always follow the principle of the triple check”. This skepticism highlights the current limitations of AI compared to the critical skills that are essential in journalism.

Of particular interest is the fact that Greek local media organizations, as a whole, either use very few AI tools or are still in the experimental stage. Typically, in all cases, efforts to integrate AI tools were initiated purely out of the personal interest and curiosity of the individuals involved, rather than by organized strategic initiatives, as Participant 4 noted: “From pure personal interest and exploration to see what it is and how exactly we can use it”. Also, Participant 3 subserved this mentality: “The truth is, because I’m very involved in technology and I generally follow the technological trends, so when the discussion about ChatGPT, I tried it out of curiosity and then of course, when I settled on what I think is right for me I watched some YouTube videos with tutorials that help me understand a little bit better what this platform does”. Only Participant 5 clarified that “Obviously we don’t use them and as far as I know and the colleagues that I work with don’t use them as well”.

Therefore, as the use of AI tools is at an early stage by local media, as the interviewees themselves told us, no formal protocol has yet been established for the proper setting and use of AI within organizations. Only informal guidelines for some very basic tasks have been established, as Participant 4 highlighted: “No, what has been done is that general instructions have been given. Clear instructions are given in discussions and meetings, firstly that we never take content pieces as they produced from the tools, and we make sure that we don’t copy content that we don’t know the source of for both copyright reasons and also for cross-referencing information”. Only one of the Greek local media has provided clear guidelines as to the use of AI and the creation of content and are planning to formalize it in 2025. Participant 6 mentioned: “It has it been created, but currently is in place informally, but from 2025 it will be in place formally as we get into Reporters Without Borders. So, we are required to follow those procedures”.

3.3.3. Ethical Concerns

All participants rejected the idea of AI as a direct threat to their profession. Instead, they considered AI as a complementary tool that could improve productivity and creativity when used wisely, as Participant 2 also highlighted: “We can use Artificial Ιntelligence as a very important, a valuable auxiliary tool”. However, this optimism was accompanied by significant concerns. These concerns reflect caution in adopting AI, even among journalists who are otherwise optimistic about its potential.

Overall, the participants emphasized the need to establish a balance between using AI for efficiency and maintaining the journalistic standards of trust and quality, as Participant 1 highlighted: “We’re going into uncharted waters that undermine our work, our credibility. So, I think it raises a lot of ethical dilemmas over there and in terms of the work that we do. We’re giving up a little bit of the freedom that journalism has to defend and accountability. You have to look at it as an asset, not a replacement”.

The participants also brought up broader ethical concerns about AI integration. These included worries about AI’s role in spreading false information, unclear algorithms, and the effects on journalistic integrity. Participant 7 said: “First and foremost, I am concerned about the profession itself. But mostly about the content and how easy it is for readers to understand who produces the content, and if they’re not concerned, whether it’s going to be the machine or not”. Participant 3 added: “So what I’m concerned about is whether journalists or at least those who are engaged and using AI are able to manage what they get from AI so that they deliver a product that is both journalistically high quality and right for the reader”. Despite these issues, the participants expressed a desire to explore AI’s potential in ways that focus on ethics and accountability.

While the participants are interested in experimenting with AI tools and see their potential benefits, they also remain cautious about their limitations and the broader implications for the profession. Participant 1 mentioned: “I mean, what’s going to happen? Let’s say we’re going to have robots telling us the news, producing the news, and we’re going to sit back, we’re going to have the role of the consumer. It also raises the question of who controls these robots and all these platforms and how these things work, there are some big multinational companies that control these things”. Participant 6 added: “I have the fear, I think we all have, that eventually we won’t be needed. Our text will be written by Artificial Intelligence. The photo will be uploaded by Artificial Intelligence. AI will do everything for us. I’m not afraid of losing my job. I’m afraid that we won’t be useful as human beings because our brains and our abilities will be dulled, that’s my concern”.

4. Discussion

The findings of this study show a new landscape in the use and integration of AI tools in Greek local journalism. Journalists are aware of the transformative potential of AI to improve productivity, efficiency, and reporting quality. However, they remain cautious about the ethical and practical issues these technologies raise.

One of the main topics from the interviews is concerns regarding the reliability and integrity of AI results, which are aligned with those mentioned by Olsen [56]. According to Olsen’s study [56], journalists are skeptical of AI’s ability to produce high-quality content without human intervention. This opinion was stated also by our Greek participants, who emphasized that the journalist must always have the last say on content verification. Their emphasis on “the human touch” reflects a shared global concern about relying too much on AI in journalistic processes, especially when it comes to tasks that require detailed understanding and ethical judgment.

Also, another topic was the ability of AI tools to improve journalistic efficiency and free up time for more creative and in-depth reporting. This is in line with the research by Cools and Diakopoulos [4], who highlighted that Generative AI is widely seen by journalists as a way to reduce routine workload, so that they can focus on more complex tasks like critical analysis and investigative journalism. Greek journalists also note advantages like saving time from transcription and fact-checking tasks, as well as improved accuracy in spell-checking and language editing. These similarities highlight AI’s potential as a supplement tool rather than a replacement for human judgment.

Greek journalists expressed serious concerns about the ethical implications of AI in journalism, especially regarding biases embedded in AI systems, the potential loss of journalistic accountability, and the possibility of spreading false information. Similarly, Noain Sánchez [57] noted that journalists and media experts expressed concerns about the lack of transparency in AI algorithms and the possibility that these systems could spread biases or inaccuracies. Greek journalists shared these fears, raising questions about who controls the technology and whether it is consistent with the journalistic values.

Additionally, the participants expressed worries about AI’s role in reducing journalists’ critical engagement, a topic that Cools and Diakopoulos [4] also observed. According to their study, some journalists worry about the “dulling” of critical thinking abilities and the possibility of decreased participation in the narrative process. Greek journalists shared similar concerns, especially the worry that AI could eventually undermine the unique cognitive and analytical abilities of human journalists.

The results from Greek local media show that AI adoption is still in its early stages, characterized by experimentation driven by individual initiative rather than organizational policy. This contrasts with findings from Noain Sánchez [57], who reported more structured integration efforts in larger, better-resourced newsrooms. Financial limitations and lack of technology infrastructure characterize the Greek context, which is similar to challenges identified by Olsen [56], who pointed out that smaller newsrooms often lack the resources required to fully use AI tools.

It is interesting to note that Greek journalists’ cautious optimism represents a balanced viewpoint, highlighting AI’s potential to improve quality while emphasizing the need for ethical regulation. This balanced perspective is consistent with the “perils and possibilities” framework outlined by Cools and Diakopoulos [4], where journalists recognize both the revolutionary potentials, and the major risks associated with AI technologies.

The results of the study also highlight the need for strong ethical frameworks to guide AI integration in journalism. According to Noain Sánchez [57], industry-wide collaboration is necessary to create standards that guarantee AI supports rather than compromises journalistic values. Greek journalists’ reliance on unofficial guidelines for AI use highlights a gap that could be addressed through formalized policies and training programs, allowing local media to take advantage of AI’s strengths while maintaining ethical integrity. The most recent initiative within the Greek media landscape to address this need is the creation of a Code of Ethics for AI by the Panhellenic Federation of Journalists’ Associations (https://www.poesy.gr/deontologia/, accessed on 1 March 2025). Currently under development, this framework aims to provide general guidelines for the use of AI in Greek newsrooms, ensuring responsible and ethical integration of these technologies. Furthermore, Trattner et al. [58] emphasized that responsible media technology requires a shared commitment to addressing the ethical and societal implications of AI. Their study highlighted the need for clear regulations and investigation into the unexpected consequences of AI adoption in journalism, ensuring that AI technologies align with the values of trust, accountability, and fairness. At this point, it is worth mentioning that several international organizations have established ethical guidelines to ensure the responsible development and application of AI in journalism. These frameworks focus on transparency, human oversight, the protection of human rights, and journalistic integrity. UNESCO’s Recommendation at the Ethics of Artificial Intelligence (2021), the first globally preferred setting tool on AI ethics, highlights the safety of human rights, transparency, and the need of human oversight, ensuring the human duty on AI-generated content [59]. Similarly, the OECD AI Principles (2019) propose truthful and obvious AI systems, emphasizing human-centered governance that prioritizes democratic values and press freedom [60]. Complementing these frameworks, the Council of Europe’s Guidelines on AI and Human Rights (2023) is conscious of the accountable implementation of AI in journalism, outlining editorial oversight measures, regulatory obligations, and the need to evaluate the risks of incorrect information in AI-generated content [61]. Given that Greece is a member of both the European Union and the Council of Europe, these international guidelines could serve as essential references for shaping AI policies in Greek journalism.

Limitations

A key limitation of this study is its sample size, consisting of eight journalists from Greek local media organizations. However, as a qualitative and exploratory research, the aim was to gain in-depth insights rather than achieve statistical representativeness. The Greek local media landscape is highly fragmented, with many outlets operating as one-person entities due to long-standing financial constraints. In this context, the pool of professionals actively engaging with AI in journalism is limited. Therefore, our sample focused deliberately on journalists who have already experimented with AI tools, following a similar approach seen in prior studies [4]. While this limits the generalizability of our findings, it offers valuable early insights into AI adoption in resource-constrained, local media environments. Future studies with broader and more diverse samples could further enrich this understanding.

5. Conclusions

This study aimed to answer one key research question: How do local media journalists think AI can be used to uphold and even improve the standards of quality journalism?

To address this research question, the results show that AI can play a significant role in enhancing the efficiency and quality of journalism by automating repetitive routine tasks, supporting investigative reporting, and improving the accuracy of content creation processes. Based on the interviews, AI tools like transcription services and generative platforms optimize workflows and help journalists to focus on the creative and analytical elements of their work. However, these tools are most effective when used as complements to, rather than replacements of, human expertise. The study emphasizes how crucial it is to incorporate AI into journalistic practices in ways that respect ethical standards and maintain the human oversight required to ensure trustworthiness and accountability.

Furthermore, the study found that Greek local media stakeholders have a cautiously optimistic view of AI. While they recognize its potential to enhance journalistic quality and efficiency, they are also careful of ethical risks, such as biases in AI systems and the diminution of critical journalistic skills. The adoption of AI in Greek local media is still in an experimental stage, driven mostly by individual initiatives rather than organizational strategies. This reflects broader global trends in smaller newsrooms, where resource limitations often prevent the full-scale integration of AI technologies. The study emphasizes the need for structured approaches, including formal guidelines and training programs, to ensure that AI adoption supports journalistic integrity and trust.

In conclusion, the findings of this research contribute to the ongoing discourse on AI in journalism by providing useful insights into its potential and challenges within the context of Greek local media. By addressing both the opportunities and ethical implications of AI, this study offers valuable insights for journalists, media organizations, and policymakers navigating the rapidly evolving media landscape. It will be essential to create a balanced approach that prioritizes ethical guidelines, human oversight, and collaboration among stakeholders in order to leverage AI’s strengths while safeguarding the core principles of quality journalism. Furthermore, drawing from Rogers’ theory [56], our findings suggest that the journalists interviewed align with the profile of early adopters—those who recognize the necessity of adapting to technological advancements to ensure their professional survival. In an industry undergoing rapid transformation, it is often these early adopters who lead the way in integrating new tools, setting the stage for broader adoption within their field. Their experimentation with AI reflects a broader trend in which innovation is first embraced by those who face the most pressing challenges, ultimately shaping the future of journalism.