AI and Strategic Communication
Description
Provides an essential guide to AI's impact on PR practices, ethics, and societal implications
As AI technologies continue to evolve, communication professionals must understand their profound effects on media relations, activism, and digital engagement. AI and Strategic Communication: Navigating the Future offers a comprehensive exploration of AI's role in reshaping public relations, bringing together contributions from leading scholars and practitioners from 9 countries across 5 continents, with representation from Europe, North America, Oceania, and Asia, this comprehensive volume addresses the ethical implications, challenges, and opportunities AI presents for individuals, organizations, and society.
Covering topics such as AI-driven crisis communication, algorithmic bias, and human-robot interactions, the authors provide both theoretical frameworks and actionable strategies to help readers navigate the AI-driven landscape. The book is structured into three distinct sections, each addressing AI's impact at different levels of communication, including individual, professional and organizational, and society levels. The opening section explores personal experiences with AI, followed by an examination of AI's transformative role in public relations and strategic communication, including crisis management, employee communication, and AI-augmented content creation. The concluding section delves into the broader implications of AI on democracy, media ethics, and cultural biases.
Offering expert guidance for integrating AI tools responsibly while addressing privacy concerns and ethical dilemmas, AI and Strategic Communication:
- Presents cutting-edge research from experts in AI, PR, and media ethics
- Discusses emerging AI-driven technologies and their implications for PR professionals
- Discusses AI's impact on democracy, misinformation, and truth in public discourse
- Includes a forward-looking analysis of AI's evolving role in communication
- Offers recommendations for future research and professional adaptation
- Features research-backed insights, practical strategies, and real-world case studies
With a multidisciplinary approach to communication in the digital age, AI and Strategic Communication: Navigating the Future is essential reading for students, educators, and industry professionals looking to stay ahead in the evolving field of strategic communication. It is an ideal textbook for undergraduate and postgraduate courses on digital communication and social media, communication ethics and technology, advanced public relations, and strategic communication.
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Persons
YANG CHENG is an Associate Professor at North Carolina State University One of Stanford University's top 2% most-cited scholars, she specializes in AI, crisis communication, and relationship management. Her work has earned numerous awards, and she has lectured at top institutions worldwide.
DEJAN VERCIC is Professor and Head of the Centre for Marketing and Public Relations at the University of Ljubljana. A Fulbright scholar and PhD graduate of the London School of Economics, he specializes in globalization, internal communication, and strategic PR.
Content
Notes on Editors xvii
List of Contributors xix
Foreword xxiii
Preface xxv
Acknowledgements xxvii
Decoding Complexity: The Role of AI in Modern Public Relations 1
Marko Grobelnik
Setting the Stage: An Analogy 1
Introduction 1
PR through the Lens of AI Definition 3
AI System Definition 4
PR Systems in Relation to AI System Definition 6
Demystification of AI Modeling 8
An Exercise How to Construct AI-Based PR Systems 12
Reputation Management Scenario 12
Social Media Performance Scenario 13
Crisis Response Effectiveness Scenario 14
Ethics, Risks, and Bias of AI 15
Future AI Technologies and PR Applications 17
Five AI Technologies of the Future 17
Four Future PR Application Scenarios 19
Scenario 1: The Corporate Sentinel 19
Scenario 2: Disaster Relief in the Digital Age 20
Scenario 3: Vaccination: A Public Health Imperative 21
Scenario 4: The Political Arena 21
Summary 22
References 22
Introduction: AI and Strategic Communication 24
Yang Cheng and Dejan Vercic
1 Staying Human in a Smart Machine World 33
Anne Gregory and Swati Virmani
Staying Human in a Smart Machine World 33
AI and Technological Advancement 34
AI and Government 35
AI and the Corporate Sphere 36
AI and Civic Society 37
AI and Its Use in Strategic Communication 38
Ethics and the Human 45
Ethics by Design 47
Conclusion 52
References 52
2 AI and Privacy: Privacy Concerns in the Public Sphere 55
Tugce Ertem- Eray and Eyun- Jung Ki
Information Privacy 57
AI and Privacy in Strategic Communications 58
Using AI in Strategic Communication to Shape the Public Sphere 60
Moving Forward 62
References 65
3 AI, Activism, and Strategic Communication: Grappling with Evolving Power Dynamics 71
Dean Kruckeberg, Marina Vujnovic, Lukasz Swiatek, and Chris Galloway
Introduction 71
There is no Return 74
AI Opens a Whole New Frontier and at a Whole New Level 75
AI Will Alter Requisite KSAs of Public Relations Practitioners 76
What is AI? 76
Power, Opacity, and AI 77
Conclusion 79
References 80
4 Anxiety and Education: How Not To Become Obsolete 83
Cheng Chen and Qian Xu
Anxiety and Education: How Not To Become Obsolete 83
AI and Generative AI 84
AI Anxiety 84
AI Anxiety Typology 85
AI Anxiety among Educators 86
Solutions to Mitigate AI Anxiety 87
Method 88
Sampling and Participants 88
Procedure 89
Focus Group Protocol 89
Data Transcription and Coding 90
Results 90
Primary Types of Perceived AI Anxieties 90
Job Replacement Anxiety 90
Anxiety about Integrating AI into Teaching 91
Anxiety Surrounding Student Use and Perceptions of AI 92
Potential Solutions to Alleviate AI Anxieties 92
Solutions to Job Replacement Anxiety 92
Solutions to AI Integration Anxiety 93
Solutions to Anxiety about Student Use and Perceptions of Generative AI 94
Discussion 95
Job Replacement Anxiety and Its Solutions 96
AI Integration Anxiety and Its Solutions 97
Anxiety about Students' Use and Perceptions of Generative AI and Its Solutions 98
Theoretical Implications 98
Limitations and Future Studies 99
Conclusion 99
References 100
5 AI Strategies and Tools for Public Relations Practitioners 105
Stephen Waddington
Theoretical Perspectives of AI 106
AI in a Practical Context 108
The Strategic Case for AI 109
Practitioner Adoption 109
Organizational Adoption 110
Strategies for Practitioner Adoption of AI in Practice 111
Strategies for Organizational Adoption of AI in a Public Relations Setting 112
Governance and Regulation of Systems 117
Data Management 118
Copyright and Disintermediation 118
Hallucination: Tools Make Stuff Up 120
Transparency and Detection 120
Ethical Decision- making 121
AI and Future Skills in Public Relations 121
References 122
6 Linking AI with Internal Communication: A Systematic Review 125
Yi Luo, Dongdong Yang, and Hua Jiang
Introduction 125
Theoretical Framework 126
Defining Artificial Intelligence 126
Linking Artificial Intelligence with Internal Communication 127
Focus of this Study 128
Method 128
Literature Search 128
Analysis 133
Results 133
Findings from Literature Review 134
RQ1: What is the Current Status of AI Adoption for Internal Communication? 134
AI Adoption for Internal Communication 134
Transformative Potential of AI Use for Internal Communication 135
Employee Attitudes toward AI Communication Tools 135
Organizational Readiness 136
RQ2: What is the Impact of AI Use on Internal Communication? 137
Operational Efficiency and Employee Development 137
Organizational Listening and Employee Voice 138
Value of Internal Communication 139
Employee Well- being and Professional Role Identity 139
RQ3: What are the Barriers and Risks of AI Use for Internal Communication? 140
Barriers to Adoption 140
Ethical Considerations 140
Discussion 141
Future Research Directions 142
References 144
7 Does AI Democratize Commercial Content Creation? Changes to the Strategic Communication Profession 149
Jukka Niittymaa, Joel Mero, and Vilma Luoma- aho
Introduction 149
AI in Strategic Communication 151
Data and Methodology 153
Analysis 156
Conclusions 158
Implications for Strategic Communication 160
Limitations 162
Future Research Opportunities 162
Acknowledgements of Funding and AI Use 163
References 163
8 Collaborating with AI: The Next Frontier of Crisis Communication 167
Elise Karinshak, Wenqing Zhao, Philippe Borremans, and Yan Jin
Introduction 167
AI Tools 170
Relevant Technological Developments 170
Practitioner Tools 172
Human- AI Collaboration in Crisis Communication 173
The Need for Collaboration with AI 173
Using AI in Crisis Management across Sectors 176
Practitioner Responses to AI Adoption 177
Ethical and Societal Considerations 178
Conclusion 182
References 182
9 Human- Robot Communication and Organization- Public Relationships 187
Jeyoung Oh and Eyun- Jung Ki
Introduction 187
Robot and Human- Robot Communication 189
AI- Powered Robots in Public Relations 190
Organization- Public Relationship (OPR) Framework 191
Theoretical Frameworks for Human- Robot Communication 193
Computers are Social Actors (CASA) Theoretical Framework 193
Social Presence Theory 194
Uncanny Valley Effect 195
Building Relationships through Robots 195
Future Direction 197
References 198
10 Democracy and Public Deliberations in an AI- Mediated World 207
Anca Anton
Introduction 207
Theoretical Framework 208
AI's Utopian Possibilities 209
Enhanced Inclusion 209
Transparency and Accountability 212
Heterotopic Tensions in AI- Mediated Public Deliberations 214
Algorithmic Manipulation 215
AI- Driven Echo Chambers 216
Human Agency versus Technological Influence 216
Case Studies 217
Reframing the Role of the Communicator 220
From Organizational to Societal Logic 220
Combating Societal Myopia 221
Responsible AI Implementation in Relation to Democracy and Public Deliberation 222
Regulatory Frameworks 222
Balancing Benefits and Risks 223
Strengthening Democratic Values 224
Conclusions 224
References 226
11 Deepfakes in Subversive Strategic Communication: Challenges and Responses 231
Sergei A Samoilenko and Inna Suvorova
Subversive Strategic Communication 232
Deepfakes in Subversive Strategic Communication Campaigns 234
Deepfakes in Political Contexts and Warfare Scenarios 236
Deepfakes in Political Contexts 236
Deepfakes in Warfare Scenarios 238
Threats, Challenges, and Responses to Deepfakes 239
Conclusions 241
References 242
12 AI, Biases and Cultures: Values in a Machine World 251
Shannon A Bowen and Evgeny N Pashentsev
Values and Ethical Use of AI Across Cultures 251
The Malicious Use of AI 255
Malicious Use of AI as Intentionally Antisocial Action: Roots of the Problem 255
Malicious Actors, Cyber Attacks, and AI Ownership 256
Twin- Use Technologies (Deepfakes, Chatbots, Emotional AI, Prognostic Weapons, etc) in the Hands of Bad Actors 260
Conclusion: The Role of Strategic Communication and Acting as Values Managers 263
References 265
13 Strategic Communication for AI: How Strategic Communication Makes AI Socially Accepted 271
Yangzhi (Nicole) Jiang, Yang Cheng, and Yuan Wang
Introduction 271
AI- Powered Chatbots in CSR Communication 273
AI- Powered Chatbots and Their Attributes Enabling CSR Communication 273
Humanlike Conversational Cues 274
Social- Oriented Communication 274
Intelligence 275
Animacy 275
Understanding Stakeholder Acceptance of Humanlike Chatbots 276
Trendiness 276
Social Presence 277
Trust 278
Impacts of Humanlike Chatbots on CSR Dialogue and Stakeholder Behavior 279
Organizational Listening 279
Shared Meaning Creation 280
Supportive Intent 281
Recommendations for Practices 282
Advancing Humanlike Conversational Abilities and Trendiness 282
Emphasizing Chatbots as Listening and Shared Meaning Creation Tools 283
Conclusion and Future Research Directions 284
References 285
Embracing the Future of AI in Strategic Communication: Impacts at the Individual, Professional, Organizational, and Societal Levels 293
Yang Cheng, Wanjun He, Jinzhe Qiao, and Dejan Vercic
Introduction 294
AI's Origin in Strategic Communication 295
AI's Application across Strategic Communication Domains 296
AI's Multi-level Impact across Strategic Communication 298
AI's Impact on the Individual Level 299
AI's Influence on the Organization and Professional Level 300
AI's Impact on the Society Level 302
The Future of AI in Strategic Communication 303
Organizational Level: Ethics, Privacy, and Fairness in AI Integration 303
Privacy Concerns 304
Fairness in AI Design 304
Individual Level: Trust and Public Behavior 305
Trust Dynamics and Psychological Impact 305
Regulatory Challenges 305
Society Level: Inclusivity, Global Impact, and Emerging Technologies 306
Inclusivity and Cultural Sensitivity 306
Emerging Technologies and Synergies 306
Conclusion: Balancing Innovation with Responsibility 306
References 307
Index 313
Decoding Complexity: The Role of AI in Modern Public Relations
Marko Grobelnik
Department for Artificial Intelligence, Co-founder of UNESCO International Research Center on AI (IRCAI), SI, Jozef Stefan Institute, Ljubljana, Slovenia
Setting the Stage: An Analogy
Google Maps and AI-enhanced public relations are modern navigational systems for different terrains. In Google Maps, a user inputs a destination, and the system analyzes countless routes, traffic conditions, and obstacles to recommend the best path. Similarly, in AI-driven public relations, the "destination" is a desired public perception or campaign objective. The AI acts as the navigator, analyzing audience sentiment, media trends, and communication channels, then suggesting strategies-be it press releases, social media posts, or influencer collaborations. Just as Google Maps adapts to real-time traffic updates, AI in PR dynamically adjusts strategies based on live feedback, ensuring the journey from A to B is as effective and efficient as possible.
Introduction
In this paper, we present the relationship between two interdisciplinary fields-artificial intelligence (AI) and public relations (PR)-both of which intersect science, technology, and practice. While AI is a relatively young discipline, emerging in the early 1950s alongside the advent of modern computing, PR has roots that extend far deeper, arguably as old as organized human society itself. Despite their differences in age and focus, the two fields complement each other in various ways, with a significant point of intersection being their shared emphasis on managing social complexity.
AI provides advanced tools and methodologies to address complex tasks, many of which were traditionally within the exclusive domain of human cognition and labor. Throughout AI's short but dynamic history, researchers and engineers have continuously pushed the boundaries of task complexity. Although early ambitions aimed at achieving human-level intelligence were largely unmet during AI's formative years, significant progress was realized after 2015 with the rapid advancements in "Generative AI" (GenAI, 2024), a transformative subfield of AI. The pivotal moment for public awareness occurred in November 2022, marked by the release of the groundbreaking chatbot system, "ChatGPT" (OpenAI, 2024). This system demonstrated unprecedented proficiency in text understanding and interaction, catalyzing a surge in the development of GenAI technologies across domains such as text, speech, image, and video processing. By 2025, the pace of GenAI innovation remains relentless, continuously advancing the complexity of tasks machines can perform.
The underlying reasons for this exponential progress post-2020 are not entirely understood, but they likely reflect the convergence of three critical factors: (1) the unprecedented scale of computational power, (2) the availability of vast quantities of high-quality data, and (3) algorithmic breakthroughs in machine learning, particularly in representation learning. Together, these factors have enabled AI systems to achieve and surpass human-level performance in several domains, redefining the boundaries of what is computationally possible.
The development of PR has been deeply intertwined with advances in communication technologies such as the printing press, radio, television, and the internet. Each new medium introduced unique capabilities and necessitated the acquisition of new skills, offering practitioners enhanced tools to amplify their messages and achieve strategic objectives. However, these technologies served solely as aids, with the management and execution of PR strategies remaining firmly within human control.
The advent of AI marks a transformative shift in the field. For the first time in history, PR tasks can be partially or fully outsourced to machines. AI systems, equipped with advanced algorithms and infrastructure, can uncover previously unknown communication patterns, manage unprecedented levels of complexity, process vast quantities of information at high speed, and operate at significantly reduced costs. Moreover, AI-driven systems can act autonomously, further extending the capabilities of PR by executing strategies and adapting dynamically to achieve desired outcomes. This evolution redefines the role of technology in PR, transforming it from a supporting tool to an active participant in shaping communication strategies.
In the following sections, we will present a detailed analysis of the intersection between AI and PR. We begin by examining how the definition of AI aligns with PR processes, offering a structured perspective on the integration of AI system components into PR workflows. This includes an analysis of the roles played by human intervention and AI automation, along with the ethical considerations that may arise from their interaction. Subsequently, we will explore currently relevant real-world applications and use cases of AI technologies in PR, emphasizing current capabilities and practical implementations. Finally, we will project potential future scenarios, both realistic and speculative, to illustrate how AI may further shape the field of PR. These scenarios will address emerging opportunities, associated risks, and strategies to prevent manipulation and misuse, providing a likely perspective on the evolution of PR in light of AI advancements.
PR through the Lens of AI Definition
In this section, we will systematically decompose the typical processes occurring within the fields of AI and PR into a defined set of characteristic components. We will then present a structured analysis to illustrate the key points of operational interaction between these two fields.
Two important differences between both fields require attention. The first difference lies in the scope of their techniques and approaches. AI is a generic, domain-agnostic technology, capable of application across diverse fields, whereas PR is domain specific, almost exclusively centered on social processes and communication between social entities. The second key distinction is in the observability and measurability of their respective processes. AI systems typically require nearly complete observability and measurability to function effectively, whereas PR tasks often deal with variables that are not easily observable or quantifiable.
It is important to note, however, that advancements in AI (particularly in GenAI) and the increasing availability of data have significantly enhanced the observability and measurability of social processes, leading to significantly greater overlap between the two fields.
AI System Definition
Defining a field as dynamic and expansive as AI, with its ongoing evolution, poses significant challenges. Nonetheless, recent developments in AI regulation at various levels-spanning international organizations, individual nations, and private companies-have necessitated a common, actionable definition to underpin legal frameworks and associated processes. The first politically agreed definition of an "AI System" was established by the OECD in 2019 and subsequently updated in 2023 (OECD, 2023). This definition achieved an initial consensus among over 40 countries (OECD member states) and was later adopted by key entities including the Council of Europe, the EU (to support the EU AI Act) (European Commission, 2024), the US National Institute of Standards and Technology (NIST), the G7, the G20, and numerous national governments. Notably, this effort focused on defining "AI System" as a tangible and actionable concept, rather than attempting to comprehensively define the broader field of AI.
The OECD definition of an "AI System" comprises three parts (Grobelnik et al., 2024): a concise two-sentence narrative, a corresponding "Explanatory Memorandum" providing detailed context, and a graphical illustration to visually support and enhance understanding. The two-sentence narrative outlines the essential components and properties of an "AI System," emphasizing their integration within a feedback loop:
"An AI system is a machine-based system that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments. Different AI systems vary in their levels of autonomy and adaptiveness after deployment."
The graphical depiction in Figure 1 illustrates a typical architecture of an "AI System," comprising components aligned with the narrative definition provided above. These components are interconnected in various configurations to represent the standard flows of information throughout the system, encompassing multiple modes of use, such as pre-deployment training or post-deployment operation. The caption of Figure 1 provides detailed descriptions of the key elements and their specific roles within the overall architecture, offering better clarity on their interdependencies and functions.
Figure 1: The graphical depiction of an "AI System" illustrates its interaction with an observed and influenced "Environment." On the left side of the image, the "AI System"...
