Strategies Used by Public Relations and Communications Executives to Implement Ethical Use Standards for AI ()
1. Introduction
Artificial intelligence (AI) tools have transformed the public relations and communications (PR&C) industry, improving speed and efficiency through data-driven generative capabilities (Anani-Bossman et al., 2024; Biswal & Gouda, 2019). AI adoption among companies more than doubled since 2017, with private funding reaching $91.9 billion in 2022, insinuating a profound shift in global investment patterns (McKinsey & Company, 2022; Stanford Institute for Human-Centered AI, 2023). These tools help PR&C professionals streamline critical processes like content creation, sentiment analysis, and customer engagement, enabling more efficient and data-driven operations (Nikolova, 2024).
However, the rapid integration of AI into business has outpaced the development of corporate ethical policies. The gap in usage versus governing policy has created significant risks for PR&C professionals in modern practice. AI-generated content and automated stakeholder interactions can propagate misinformation, bias, and data privacy breaches. PR&C directly impacts society and its associated roles because they directly impact what is being seen by the public. Therefore, not having proper ethical guardrails can harm customer experience and brand reputation. PR&C executives currently operate without effective methods for creating ethical guardrails for AI deployment which leads to regulatory and reputational voids that endanger financial health and organizational integrity.
This study examines how PR&C executives address these challenges by identifying and exploring the effective strategies they use to develop and apply ethical frameworks for AI implementation. Grounded in the AI4People framework (Floridi et al., 2018) and stakeholder theory (Freeman, 1984), this qualitative pragmatic inquiry was designed to uncover how leaders navigate the complex intersection of technological innovation and ethical responsibility to maintain their organization’s brand reputation.
The following section reviews the relevant literature and conceptual framework, after which the paper presents the study’s findings. These findings detail five key themes: Strategic and Ethical AI Integration, Human-Centric Integration, and Protecting Brand Integrity, that outline actionable approaches for PR&C leaders. The paper concludes by discussing the implications of these findings for professional practice and future research in the evolving landscape of AI and communications.
2. Literature Review
The professional and academic literature review served as a foundational component of this project, addressing the overarching research question: What effective strategies did PR&C executives use to develop and apply an ethical framework for AI implementation to maintain their organization’s brand reputation? The purpose of this review was to identify, explore, and synthesize scholarly and professional insights that contributed to understanding the complexities and opportunities related to ethical AI integration in the PR&C field (Pantic & Hamilton, 2024).
Through a critical analysis of existing research, this review supported the application of relevant theories, concepts, and a conceptual framework that shaped the project’s trajectory. This methodical process highlighted knowledge gaps, identified commonalities and differences in studies, and uncovered emerging trends within AI usage while providing a framework for current and future research (Pantic & Hamilton, 2024). Searches focused on sources published within the past five years to maintain recency and relevance, with exceptions for seminal works essential to the conceptual framework.
To conduct a comprehensive search, the following keywords were used: “AI ethics”, “PR ethics”, “ethics in communications”, “brand reputation and AI”, “AI transparency”, “AI in business”, “AI in marketing”, and “stakeholder alignment in AI adoption”. Primary resources were accessed through databases such as ProQuest Central, EBSCOhost, Sage Journals, and Emerald Insight via the Walden University Library, supplemented by Google Scholar. This literature review referenced a total of 75 sources, of which 65 (87%) were peer-reviewed journal articles; 65 were published within the last five years, ensuring recency and relevance.
This project examined the ethical concerns related to the use of AI integrations by PR&C professionals. As AI technologies became increasingly ubiquitous, organizations faced challenges related to transparency, accountability, and trustworthiness. Addressing these challenges required ethical frameworks that aligned AI use with organizational goals and societal values. Strategic communication ethics depended on maintaining transparency and promoting accountability while keeping public trust a priority. Establishing ethical guidelines for AI systems was essential to maintaining transparency, accountability, and fairness while reducing potential dangers and promoting responsible AI usage.
This review explored perspectives from AI4People and stakeholder theory, which collectively encompassed the conceptual framework that served as a foundation for the project. A systematic approach analyzed the conceptual framework; synthesized research related to themes and phenomena; and compared and contrasted perspectives from recent and historical literature to evaluate how evolving practices influenced the project’s focus.
2.1. Conceptual Framework
The purpose of this qualitative pragmatic inquiry project was to identify and explore the effective AI strategies global PR&C executives used to develop and apply an ethical framework for AI implementation to maintain brand reputation. The conceptual framework leveraged AI4People (Floridi et al., 2018) and stakeholder theory (Freeman, 1984), providing a comprehensive basis for directing ethical AI practices in PR&C.
AI4People outlines five key principles: beneficence, non-maleficence, autonomy, justice, and explicability, that establish ethical guidelines for AI applications. Beneficence focuses on AI doing good for others; non-maleficence requires prevention of harm; autonomy stresses maintaining human oversight; justice calls for fairness and inclusiveness; explicability covers transparency and accountability to build trust among stakeholders (Floridi et al., 2018). Stakeholder theory emphasizes considering the interests of employees, consumers, shareholders, regulators, and the extended community; it guides AI adoption that addresses ethical, social, and reputational concerns; encourages engagement; and focuses on longer-term relationships that establish trust and loyalty (Freeman, 1984). When used separately, the AI4People theory is great for considerations for aligning AI system goals with human values, and stakeholder Integrating AI4People and stakeholder theory is great for considerations for a holistic and strategic framework for decision-making for ethical conduct and long-term business success. The combination of both theories as a lens bridges technical guidelines and a human-centric approach to ensure alignment with organizational goals and values, transparency, and stakeholder engagement (Mökander & Floridi, 2021).
2.2. Applications and Strategic Implications of AI in PR
AI reshaped PR&C by changing how professionals handle communications, decision-making, and operational efficiency. AI-powered tools automate routine tasks, enhance data-driven decisions, and enable more personalized communications, while also improving campaign strategy through analysis of large cross-channel datasets. These capabilities support trend detection, faster data-driven campaigns, audience segmentation, influencer identification, and crisis monitoring through real-time sentiment analysis (Nikolova, 2024; McKinsey & Company, 2025). The inclusion of AI in modern business environments helped researchers and practitioners move from rigid, rules-based systems toward dynamic human-AI collaboration informed by machine learning and big data (Lai et al., 2021; Almanasra, 2024).
2.3. AI Governance and Ethical Considerations
Responsible deployment of AI demands strong governance and ethical practices aligned with organizational values and stakeholder expectations to maintain trustworthiness. Without comprehensive frameworks, misuse can create societal ripple effects (e.g., misleading synthetic media and rapid information cascades), underscoring the need for verification protocols, auditability, and unified standards (Morandín-Ahuerma, 2023; Lahusen et al., 2024). UNESCO’s ethical AI recommendations and the EU’s emerging regulatory posture highlight transparency, responsibility, testing, and accountability (Morandín-Ahuerma, 2023). For PR&C leaders, embedding privacy legislation, data governance, and workforce training into AI strategies protects consumer trust and brand integrity, while ethics-based auditing strengthens governance (Mökander & Floridi, 2021; Nair et al., 2025).
2.4. Transparency and Trust in AI Usage
Transparency is essential in generative-AI-supported PR. Professionals face disclosure challenges around AI tool usage; inconsistent transparency erodes trust. Research shows AI-generated news and narratives tend to be viewed as less trustworthy and less emotionally resonant than human-created content, particularly on sensitive topics (Lahusen et al., 2024; Lai et al., 2021). During crises, opaque AI use undermines credibility; clear disclosures, content verification, and watermarking reinforce trust (Cheong, 2024; Morandín-Ahuerma, 2023).
2.5. Custom Frameworks for Ethical AI Implementation
The increased prominence of AI in PR&C required organizations to implement tailored ethical frameworks that reflect regional, cultural, and legislative variability. Localized approaches address data privacy, consumer trust, and human-machine interaction issues (“glocalization”) while embedding principles of transparency, accountability, and fairness to mitigate data misuse and algorithmic bias (Kopalle et al., 2022; Siricharoen, 2024). Customized ethical frameworks should actively anticipate new problems, reduce resistance, align global standards with local requirements, and incorporate ethics-based auditing for continuous assurance (Mökander & Floridi, 2021). By implementing these measures, organizations maintain public trust and compliance with ethical standards while satisfying organizational and societal concerns (Nwodo, 2024).
2.6. Balancing Innovation with Ethical Safeguards
The increased and rapid adoption of AI offers competitive advantage but also introduces risks such as over-reliance, generic messaging, or amplification of bias—making strategic oversight essential (Kirk & Givi, 2024; Kar et al., 2021). Understanding human decision-making tendencies helps anticipate how predictive models might drift from stakeholder expectations and societal standards (Wang & Wu, 2024). Responsible AI practices are therefore vital for reducing risks, including bias, privacy breaches, and reputational harm, and require comprehensive governance frameworks (Siricharoen, 2024). The integration of blockchain or distributed ledger techniques into AI workflows can enhance transparency, traceability, and data integrity—mitigating brand and financial exposure where auditability is critical (Lüthi et al., 2020). Practical transparency measures such as policies for distinguishing authentic from synthetic assets, editorial oversight, and controls to prevent over-personalization, help keep AI-enabled communications aligned with organizational values and stakeholder expectations (Dixon, 2024; Dezao, 2024; Informatica, 2024).
2.7. Relationship to Previous Research
This project investigated various perspectives on AI spanning historical expert systems to contemporary human-AI collaboration. Early AI was dominated by rule-based expert systems that lacked adaptability beyond narrow domains. Modern AI systems leverage data-driven learning and adaptive algorithms to overcome those limitations, supporting real-time insights and flexible decision support (Lai et al., 2021; Almanasra, 2024). In PR&C—where creativity intersects with data-driven strategy—scholarship and practice now converge on the need to pair AI-enabled efficiency with safeguards that prevent bias and protect reputation (Nikolova, 2024; Cheong, 2024).
3. Methodology
This study employed a qualitative pragmatic inquiry approach to explore the strategies PR&C executives use to develop ethical AI frameworks. Semi-structured interviews were conducted with six PR&C executives selected through purposive sampling of PR&C leaders, with at least 5 years’ experience in the position, who had successfully developed and applied ethical frameworks for AI implementation while maintaining their organizations’ brand reputations. Data saturation was reached at the fifth interview; one more was conducted to ensure data saturation. Participants were recruited through professional networks and industry associations, all of which had direct experience with AI implementation in their organizations.
Data collection involved virtual interviews conducted via Microsoft Teams or Zoom, which were audio-recorded and subsequently transcribed. Thematic analysis was used to identify patterns and themes across the interview data, following the process outlined by Braun and Clarke (2006). The study involved familiarization with the data, generating initial codes, searching for themes, reviewing the themes, defining the themes, and producing the report. Ethical approval was obtained from the institutional review board, and all participants provided informed consent. Trustworthiness was enhanced through member checking to verify interpretations, triangulation of interview data with industry reports, and detailed documentation (research log and reflexivity journal), which served as an audit trail to support dependability, credibility, transferability, and confirmability.
4. Findings
4.1. Introduction
The purpose of this qualitative pragmatic inquiry was to identify and explore the effective strategies PR&C executives use to develop and apply an ethical framework for AI implementation to maintain their organization’s brand reputation. Data analysis from semi-structured interviews with six PR&C executives revealed five primary themes, which are summarized in Table 1. The participant demographics are provided in Table 2.
Table 1. Summary of key themes.
Theme |
Description |
1. Strategic and Ethical AI Integration |
Selection and use of AI tools governed by ethical guidelines and aligned with organizational values. |
2. Human-Centric Integration of AI |
Maintain human oversight, creativity, and ethical judgment as key components in AI-outputs. |
3. Protecting Brand Integrity Through Responsible AI Use |
Implementing safeguards to mitigate risks including lack of originality, false or misinformation, and emotional disconnect. |
4. Framework, Privacy,
and Risk Mitigation |
Establishing governance structures to address data privacy, security, and ethical oversight from the outset. |
5. Transparency and Stakeholder Communication |
Championing clear disclosure about AI’s role in content creation both internally and with clients. |
Table 2. Participant demographics.
Pseudonym |
Gender |
Industry |
Years Experience |
Role |
PRC1 |
Male |
Manufacturing |
30 |
Head of Global PR |
PRC2 |
Male |
Cyber-Security |
10 |
Managing Director, Communications |
PRC3 |
Female |
Cyber-Security |
11 |
Co-CEO |
PRC4 |
Female |
Technology |
8 |
Founder |
PRC6 |
Female |
Lifestyle/Authors |
15 |
Founder |
PRC7 |
Female |
Technology |
20 |
Head of PR |
4.2. Themes
Theme 1: Strategic and Ethical AI Integration
The first central theme suggests that PR&C executives consider the strategic use of AI to be essential. Still, it must be grounded by strong ethical standards to support innovation without compromising brand values. The AI4People framework, highlighted “beneficence” and non-maleficence” as essential principles and demonstrated that tool choice and settings influence both fairness and transparency in results
Sub-theme 1.1: Tool Selection and Vetting. Participants stressed the value of a thoughtful process for vetting AI tools, in particular, attention to maintaining content quality and brand integrity. Five of the six participants stated they used enterprise platforms such as ChatGPT Enterprise and Jasper.AI. As PRC1 explained, the focus is on guiding the AI ethically: “The importance is teaching AI what to include and not include...recommending the creation of agents to guide ethical outputs.” PRC6 noted the use of internal libraries to ensure consistency and originality.
Sub-theme 1.2: Brand Integrity and Risk Management. AI content that was unoriginal or presented as something it was not, was considered a reputational risk by leaders. Participants reported that over-reliance was a significant risk. PRC1 warned of the danger, stating, “the temptation has overrun us”, while PRC3 described leveraging a “team-centric content vetting process” to prevent sharing compromised messaging. PRC6 identified misinformation as a primary concern, reinforcing the need for internal guidelines.
Sub-theme 1.3: Alignment with Organizational Values. Respondents unanimously agreed that organizational values were the top priority. As a focal point, it was critical that AI outputs aligned with both organizational ethical standards and brand persona (voice). Usage guidelines and output reviews helped maintain these standards. PRC4 stated they maintained this “through usage guidelines and output reviews which maintained tone, inclusivity and factual accuracy.” PRC2 expressed a more cautious approach, limiting the use of AI predominantly to research functions to safeguard the originality of thought leadership.
Theme 2: Human-Centric Integration of AI
Participants consistently emphasized that successful AI adoption hinges on keeping human creativity, oversight, and ethical judgment at the core of all communication workflows. AI was viewed as an augmentation tool, not a replacement. This directly ties back to both the stakeholder theory in that it manages risk while treating stakeholders as valued partners, and the AI4People theory so far as integrating its core ethical principles.
Sub-theme 2.1: Preserving Creativity and Original Thought. A primary concern was that over-reliance on AI could stifle the human creativity essential to public relations. PRC3 described how AI could sometimes “create some kind of a writer’s block...it stops spontaneous brainstorming and creativity.” PRC4 shared a similar early challenge in “balancing efficiency with authenticity.”
Sub-theme 2.2: Human-Led Strategy and Editorial Oversight. To mitigate this, participants developed workflows that prioritized human decision-making. PRC2 was explicit: “We don’t lead with AI. Instead of leading with it, we use it as a supporting tool.” PRC6 highlighted the critical importance of “an editorial process” for reviewing AI outputs for tone, factuality, and relevance.
Sub-theme 2.3: Including Ethical Judgment in Team Practices. Ethical reasoning was embedded into daily practices through internal checklists and team dialogues. PRC7 highlighted the importance of human origin in communication, stating, “I feel more comfortable putting my own words into ChatGPT... at least it’s using my original thoughts and my original point.”
Theme 3: Protecting Brand Integrity Through Responsible AI Use
The third theme helps identify the positive steps they are taking to ensure their brand reputation and consumer trust will be protected from some of the negative downsides to AI, including inauthenticity and misinformation. It aligns with the AI4People concepts of “explicability” and “non-maleficence” as they focus on transparency and avoiding unintended harm.
Sub-theme 3.1: Risk of Overreliance and Generic Messaging. Participants described how excessive dependence (hyper-automation) on AI could lead to generic, machine-generated language that could damage personal and brand credibility. The consensus was that human-led review processes were non-negotiable for ensuring messaging remained distinct and intentional.
Sub-theme 3.2: Message Accuracy and Relevance. The accuracy of AI-generated content was a significant concern. PRC6 stated that misinformation “creates a huge reputational risk” and that “verification and editorial standards must be set to establish confidence in the content being shared with the public.”
Sub-theme 3.3: Maintaining the emotional depth and storytelling capability of human communication was deemed irreplaceable. AI’s ability to create text was noted, but this was not necessarily thought to be as personally or authentically connected to writing by a human. This was exemplified by PRC6, who described using AI only for “structural support and brainstorming, not as a replacement for original content creation,” underscoring the continued primacy of the human voice in building genuine connections. The consensus was that authentic emotion and tone are foundational to brand trust and cannot be outsourced to AI.
Theme 4: Framework, Privacy, and Risk Mitigation
This theme highlights the critical need for proactive governance structures to manage the practical and ethical risks of AI, particularly concerning data and accountability. As with stakeholder theory, this promotes ethical management to build a more resilient and successful business. This theme also ties back to AI4People theory in its approach to mitigate and prevent unacceptable actions and potentially identify socially preferable opportunities
Sub-theme 4.1: Early Adoption Frameworks. Participants agreed on the importance of implementing structural frameworks from the start. PRC6 highlighted how such frameworks direct teams and leaders in their AI application. PRC2 suggested that future contracts would include precise terms regarding AI use to ensure legal protection.
Sub-theme 4.2: Data Privacy and Security Concerns. Participants expressed overwhelming concern about safeguarding sensitive information. PRC7 explained they were extra cautious: “I ensure absolute caution when selecting information to reveal,” demonstrating measures to protect client information from unauthorized access.
Sub-theme 4.3: Ethical Oversight Process. Organizations used formal and informal strategies to ensure ethical AI performance. PRC4 described using a vetting checklist to assess vendors’ data practices for alignment with organizational values, indicating that ethics monitoring is an ongoing responsibility.
Theme 5: Transparency and Stakeholder Communication
The final theme emphasizes that the implementation of ethical AI requires clear communication about its use to both internal teams and external clients. The fifth theme supports the part of the AI4People theory that fosters public trust and inclusivity by focusing on explicability, accountability, and multi-stakeholder engagement as critical to that end. Further, it supports stakeholder theory through enhanced reputation via a commitment to a broader range of stakeholders.
Sub-theme 5.1: Client-Facing Disclosure. Being upfront with clients about the use of AI was considered essential for maintaining trust. PRC4 stated, “It is important to maintain that transparency and honesty, that credibility...This is how we use AI...and we are not relying on it to get things done.”
Sub-theme 5.2: Internal Transparency Practices. Participants emphasized the need for explicit internal communication regarding the use of AI. PRC7 reflected on the ethical dilemma with the question, “Am I not admitting that I’m using it?” PRC6 shared, “I find that it is the most effective to tackle it head on and be very transparent,” highlighting the value of open dialogue to maintain accountability and integrity.
5. Limitations and Future Research
This study has some limitations. The sample size of six executives, while sufficient for a qualitative study, may not represent the experiences of all PR&C professionals. Future studies might include a larger sample and a quantitative approach in order to generalize the results. Further, since AI technology is constantly changing, additional research is needed to overcome upcoming ethical dilemmas.
6. Conclusion
This study aimed to identify and explore the practical strategies that public relations and communications (PR&C) executives employ to develop and apply an ethical framework for AI implementation, while maintaining their organization’s brand reputation. Ethical challenges such as AI-driven misinformation campaigns and biased algorithms in data processing have emerged with the fast-paced adoption of AI in public relations and communications while potential data privacy breaches threaten brand reputation unless these issues are addressed. This article, reporting on a qualitative pragmatic inquiry drawing on AI4People and stakeholder theory, reveals how PR&C leaders respond to such challenges.
Five themes emerged from the analysis and outline the approach of PR&C executives to these strategies: (1) Strategic and Ethical AI Integration which focused on key considerations in tool vetting, risk assessment, and upholding the organization’s values; (2) Human-Centric Integration of AI which involved the human considerations of AI adoption such as retaining human creativity, oversight and ethical decision-making; (3) Protecting Brand Integrity Through Responsible AI Use which was centered on responsible adoption of tools to mitigate the risks of inauthenticity and misinformation; (4) Framework, Privacy and Risk Mitigation which included the need for being proactive and creating the right governance structures; and (5) Transparency and Stakeholder Communication which focused on disclosure to stakeholders and communication internally about use of AI.
These findings demonstrate that the implementation of ethical AI in PR&C is not merely a technical issue, but a complex organizational endeavor that requires a balance between innovation and ethical safeguards. The themes align with the principles of AI4People (Floridi et al., 2018) and stakeholder theory (Freeman, 1984), emphasizing beneficence, non-maleficence, autonomy, justice, explicability, and the consideration of diverse stakeholder interests. For instance, the emphasis on human oversight and transparency aligns with the principles of autonomy and explicability. At the same time, the focus on brand integrity and risk management reflects the principles of non-maleficence and justice.
The implications for practice are significant. PR&C executives should establish clear ethical guidelines and governance frameworks for AI use, ensure human involvement in AI-augmented workflows, and maintain transparency with stakeholders. Managers and their organizations should invest in training and tools that support ethical AI practices, which include creating checklists and editorial process overview.
In conclusion, this study provides a foundational understanding of the strategies employed by PR&C executives to implement ethical AI frameworks. By integrating ethical principles with practical strategies, organizations can leverage the benefits of AI while preserving their brand reputation and fostering stakeholder trust. The findings could potentially refine and extend the understanding and application of the stakeholder and AI4People theories particularly in the realm of AI-driven corporate communications.