Enterprise AI Analysis
The agenda game: rethinking the basis of agenda-setting and related research in the age of Al
The mass adoption of artificial intelligence (AI) systems, from simple bots to complex large language models (LLMs), presents profound challenges to the foundational concepts of agenda setting and agenda building. AI blurs the lines of what constitutes an 'actor,' requiring researchers to rethink traditional frameworks. This conceptual work introduces a typology for AI systems based on autonomy and identification, offering guidance for agenda-setting research in the AI era. We propose viewing AI systems as entities combined with human actors in various contexts, effectively capturing how human actors leverage AI for communication goals. Furthermore, we advocate for a significant extension of agenda-setting scholarship that prioritizes communication environments as the object of study, a concept we term 'agenda gaming.' This new approach accounts for AI's role in shaping and challenging communication dynamics, moving beyond individual actors to encompass the structural influences of AI in the media ecosystem.
Executive Impact & Key Findings
This analysis highlights the critical need for new theoretical frameworks to address the pervasive influence of AI in communication environments, offering a path forward for strategic understanding and application.
0%
Conceptual Framework Overhaul
0
New Theoretical Propositions
0
Core Typology Dimensions
0
New Framework: Agenda Gaming
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
Agenda Setting & Building Theory
AI Typology & Implications
Agenda Gaming Framework
Understanding Traditional Agenda Frameworks
Originating with McCombs and Shaw (1972), agenda-setting theory explains the media's influence on public issue salience. Over time, as communication technologies diversified, agenda-building theory emerged, focusing on the 'multiplicity of voices' (Cobb et al., 1976; Zhang, 2024) that shape agendas. This evolution was driven by the liberalization of communicative power, allowing actors beyond traditional news media to influence public discourse (Perloff, 2022). Agenda building operates on three levels: object salience, attribute transfer, and network formation. The advent of AI systems presents a new grand challenge, troubling the core concept of the 'actor' and demanding a reconceptualization of how agendas are set and built in increasingly complex communication environments.
AI's Autonomy & Identification in Communication
Our central contribution is a two-dimensional typology for AI systems in agenda-setting and related research, based on 'autonomy' and 'identification.' Autonomy refers to an AI system's functional ability to engage in communicative actions independent of direct human authority, distinguishing between highly independent LLMs like Grok and low-autonomy propaganda bots. Identification refers to the authentic presentation of an AI system as an individual entity, addressing the 'invisibility' problem where AI systems (like curation algorithms or uncredited generative AI) influence communication without being recognized as distinct actors. This typology helps categorize AI's diverse roles, from explicit communicators to invisible structural forces, clarifying their impact on agenda dynamics.
Introducing the Agenda Gaming Paradigm
The introduction of AI systems necessitates a significant extension of agenda-setting and agenda-building scholarship, shifting the primary research object to communication environments themselves. We term this new approach 'agenda gaming.' This framework focuses on how communicators 'game the system' by leveraging the particular structural elements of communication environments, including AI algorithms and evolving bot policies. Instead of solely asking 'who sets the agenda,' agenda gaming investigates how the overarching characteristics of the communication environment structure the processes of agenda setting and agenda building. This provides a lens to study invisible AI influences and the formation of 'chimeric entities' (AI-human collaborations), offering deeper insights into the strategic manipulation and emergent dynamics of contemporary media ecologies.
Agenda Building: From Salience to Networks
Agenda building involves multiple stakeholders vying for influence, structured across distinct levels of communication and interaction.
Correlation of Object Salience Communicators
→
Transfer of Object Attributes or Frames
→
Networks Formed by Co-occurrence of Issues
| Dimension | Definition | Relevance to Agenda Research |
|---|---|---|
| Autonomy | Functional ability of an AI system to engage in communicative actions independent of direct human authority, with a broader purpose allowing greater latitude. | Helps differentiate AI as a tool vs. a distinct communicative actor; high autonomy AI may diverge from human messaging. |
| Identification | Authentic presentation of an AI system as an individual entity in a communication environment; degree to which it is clearly demarcated. | Determines visibility of AI as an actor; low identification AI (e.g., algorithms) contribute to the 'invisibility problem' and structural influence. |
Resolving AI's 'Who' & 'Invisibility' Challenge
AI systems create challenges in defining actors ('who' problem) and identifying their influence ('invisibility problem'). We propose the concept of 'chimeric entities' and studying communication environments as the object of 'agenda gaming' to address these.
AI's Blurring Boundaries in Communication
Traditional agenda-setting struggles with AI's dual nature: acting as a tool for humans and as an independent, often invisible, influencing force. This impacts how communicative entities are defined and how influence is tracked.
Solution Approach: Chimeric Entities & Agenda Gaming
The typology suggests that low-autonomy AI used for strategic communication should be considered part of 'chimeric entities' with human managers. Invisible AI (like curation algorithms) are seen as structural components of the communication environment, shifting focus to how these environments are 'gamed.'
- Low-autonomy AI often forms 'chimeric entities' with human managers, requiring holistic analysis.
- The 'invisibility problem' of algorithms necessitates studying communication environments as structural influences.
- Agenda Gaming focuses on strategic adaptation to environmental demands and AI structures.
- High-autonomy, identified AI (like Grok) can be treated as distinct communicative actors.
The Rise of Agenda Gaming
Our analysis introduces 'Agenda Gaming' as a critical new framework for understanding communication influence in the AI era.
0 New Theoretical Framework ProposedEstimate Your AI Transformation ROI
Quantify the potential impact of integrating advanced AI strategies into your enterprise operations based on your specific context.
Estimated Annual Savings
$0
Annual Hours Reclaimed
0
Your AI Implementation Roadmap
A structured approach ensures successful integration and maximum impact of AI within your organization, adapting to the dynamic landscape of "agenda gaming."
Phase 1: Strategic Assessment & Typology Mapping
Conduct a deep dive into your current communication landscape and identify existing AI touchpoints. Utilize the Autonomy and Identification typology to classify AI systems relevant to your enterprise, understanding their current and potential roles in agenda setting and building. This includes assessing low-autonomy tools for chimeric entity potential and invisible algorithms for structural influence.
Phase 2: Chimeric Entity & Environment Analysis
Identify opportunities to leverage AI for strategic communication goals, focusing on creating efficient "chimeric entities" where AI augments human efforts. Analyze your target communication environments to understand their unique structural elements and demands, informing how your enterprise can strategically 'game' these systems for optimal agenda influence.
Phase 3: Pilot Implementation & Proposition Testing
Deploy AI systems in pilot programs, specifically designing tests around the new theoretical propositions. Observe how autonomous AI systems diverge in messaging, how identified AI impacts perception, and how chimeric entities perform. Gather empirical data to refine AI integration strategies and validate theoretical insights.
Phase 4: Scaled Integration & Continuous Optimization
Scale successful pilot programs across the organization. Establish continuous monitoring systems to track AI performance, message alignment, and environmental changes. Regularly review and adapt AI strategies based on evolving communication environments and new insights from the "agenda gaming" framework to maintain competitive advantage.
Ready to Rethink Your AI Strategy?
The age of AI demands a new understanding of communication. Let's build a future-proof strategy for your enterprise.
Ready to Get Started?
Book Your Free Consultation.
Let's Discuss Your AI Strategy!
Lets Discuss Your Needs
Select a Date
Sun
Mon
Tue
Wed
Thu
Fri
Sat