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The Future of Business Communication in the Age of Artificial Intelligence and Multimedia Design

Monira Yesmin Tuli ORCID: https://orcid.org/0009-0002-8373-1126 Md Mahmudul Hasan Raju ORCID: https://orcid.org/0009-0006-9385-927X Tofayal Ahmed Chowdhury ORCID: https://orcid.org/0009-0008-8598-6046 Wahidur Rahman ORCID: Tashbihun Noor Tulona ORCID: https://orcid.org/0009-0001-8140-7763 Department of Graphic Design & Multimedia Faculty of Design & Technology Shanto-Mariam University of Creative Technology Dhaka, Bangladesh

Prof. Dr Kazi Abdul Mannan Department of Business Administration Faculty of Business Shanto-Mariam University of Creative Technology Dhaka, Bangladesh Email: drkaziabdulmannan@gmail.com ORCID: https://orcid.org/0000-0002-7123-132X   Corresponding author: Monira Yesmin Tuli: monira.yesmin025@gmail.com

Theor. appl. technol. sci. rev.  2026, 4(1); https://doi.org/10.64907/xkmf.v4i1.tatscr.4

Submission received: 1 October 2025 / Revised: 9 November 2025 / Accepted: 1 December 2025 / Published: 5 January 2026

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Abstract

The convergence of artificial intelligence (AI) and multimedia design is reshaping business communication—transforming how organisations create messages, engage stakeholders, and measure outcomes. This paper reviews current trends, synthesises interdisciplinary literatures (communication studies, human–computer interaction, organisational studies, and design), proposes a theoretical framework integrating sociotechnical systems theory and multimodal communication theory, and presents a qualitative research methodology suitable for exploring emergent practices. Drawing on recent industry and academic reports, it identifies key trajectories: AI-enabled personalisation and automation, multimodal content as default (video/audio/interactive), ethical and governance pressures, and the reconfiguration of human roles in communicative labour. The paper presents emergent themes from secondary qualitative syntheses and proposes directions for managers, designers, and researchers to build ethical, inclusive, and human-centred communication ecosystems. Recommendations include governance frameworks, design-literate AI literacy programs, multimodal communication standards, and research agendas to monitor long-term social and organisational impacts.

Keywords: artificial intelligence, multimedia design, business communication, multimodal communication, qualitative methodology

1. Introduction

Business communication has historically evolved alongside technological shifts, from handwritten correspondence to the telegraph, the typewriter, electronic mail, and the digital platforms of the early 21st century. Each innovation redefined not only the speed and reach of communication but also its form, tone, and organisational significance (Tourish, 2020). Today, a new paradigm is emerging at the intersection of artificial intelligence (AI) and multimedia design, where machine-driven content generation and multimodal engagement strategies are reshaping the communicative landscape. This transformation is not incremental but systemic, altering how organisations create, distribute, and interpret messages in an increasingly interconnected global economy.

Artificial intelligence now operates at the heart of corporate communication ecosystems. Generative AI models, natural language processing (NLP) engines, and machine-learning algorithms are being deployed to draft emails, summarise reports, produce multimedia campaigns, and even conduct sentiment analysis across platforms (McKinsey & Company, 2025). These tools promise unprecedented efficiency, scalability, and personalisation. According to the Stanford AI Index Report (2025), more than 60% of surveyed organisations in North America and Europe report experimenting with generative AI in communication workflows, with early adopters claiming measurable productivity improvements. However, these developments are not without risks: scholars warn of challenges around authenticity, bias, and overreliance on algorithmic mediation (Dwivedi et al., 2023).

Parallel to AI’s rise, multimedia design has become the default communicative mode in digital spaces. Organisations increasingly rely on video, animation, interactive infographics, and immersive technologies such as augmented reality (AR) to capture audience attention and communicate complex ideas (Deloitte, 2025). Platforms like TikTok, YouTube Shorts, and LinkedIn’s rich media tools demonstrate that video-first strategies dominate digital engagement (Leonardi & Vaast, 2021). Yet the demand for inclusivity and accessibility—captions, transcripts, adaptive interfaces—remains a pressing concern, especially as organisations navigate diverse global audiences (UX Design Institute, 2025).

The convergence of AI and multimedia design represents more than a technological advancement; it signals a fundamental reconfiguration of communicative labour and meaning-making. Human communicators increasingly act less as authors and more as curators and editors of AI-generated content (Huang & Rust, 2021). Trust, once grounded in identifiable authorship, is now mediated through governance practices such as disclosure of AI involvement, algorithmic transparency, and brand accountability (UNESCO, 2023). In this environment, business communication is no longer confined to human-to-human interaction but includes human–AI–audience triads.

Furthermore, the global context underscores the urgency of scholarly investigation. International bodies such as the OECD and UNESCO have stressed the risks of ethical lapses and inequalities in AI adoption, warning that the benefits of AI-enabled communication could exacerbate divides between technologically advanced firms and smaller enterprises in developing economies (OECD, 2024; UNESCO, 2023). Questions of governance, fairness, and digital inclusion are therefore central to understanding the future of business communication.

This paper pursues four objectives:

• To synthesise interdisciplinary insights on the integration of AI and multimedia design in business communication.
• To propose a theoretical framework rooted in sociotechnical systems theory and multimodal communication theory.
• To outline a qualitative research methodology capable of capturing lived organisational practices.
• To identify emergent themes, risks, and recommendations for organisations, educators, and policymakers.

By situating AI and multimedia design as interdependent forces, this study underscores that the future of business communication is not simply about adopting new tools but about reimagining communicative ecosystems. As organisations confront these shifts, scholarly contributions can guide responsible design, equitable adoption, and ethical governance.

2. Literature Review

2.1 AI in Organisational Communication

The role of artificial intelligence in organisational communication has expanded rapidly over the past decade. Early uses focused on automating routine tasks such as meeting scheduling or customer service chatbots, but the advent of generative AI has expanded applications into drafting, summarising, and even synthesising multimedia content (Dwivedi et al., 2023). McKinsey & Company (2025) report that generative AI adoption is most prevalent in knowledge work, customer engagement, and internal communications. Organisations deploy AI to create memos, marketing copy, and multilingual translations, often reducing turnaround times by more than 30%.

From a theoretical perspective, AI adoption redistributes communicative labour. Research suggests that human roles are shifting from message creation to editorial oversight and contextualization (Huang & Rust, 2021). This has implications for skill development: employees must now excel at “prompt engineering,” critical evaluation, and ethical judgment. However, reliance on AI raises concerns over message authenticity, as audiences may question whether organisational voices are human-authored or machine-generated (Tourish, 2020). Gartner (2025) warns that more than 40% of experimental “agentic AI” projects will fail due to poor integration and lack of governance, highlighting the risks of premature adoption.

2.2 Multimedia Design in Business Communication

Alongside AI, multimedia design has become central to corporate communication strategies. Rich media—video, interactive graphics, and AR/VR experiences—are increasingly employed to foster engagement and enhance message retention (Deloitte, 2025). According to Leonardi and Vaast (2021), digital platforms have accelerated a “video-first culture,” where visual storytelling often outperforms text-based messages in terms of reach and resonance. Multimedia design also supports cross-cultural communication by enabling visual narratives that transcend linguistic barriers (UX Design Institute, 2025).

Scholarly work on multimodal communication theory underscores that meaning emerges from the interplay of text, image, sound, and gesture (Kress & van Leeuwen, 2021). In practice, this means that multimedia business communication must be designed holistically, considering not just content but semiotic orchestration. AI adds a new layer by automating the conversion of modalities—transforming text into video, voice, or interactive simulations. While this enhances efficiency, it risks standardising aesthetics, reducing originality, and privileging machine-optimised formats over human creativity (Flew, Martin, & Suzor, 2019).

Accessibility is another crucial issue. Multimedia can empower inclusive communication through features like captions and transcripts, but accessibility is often neglected in fast-paced corporate environments. Research suggests that marginalised audiences, such as individuals with disabilities or those in low-bandwidth regions, are most likely to be excluded when multimedia strategies ignore accessibility (Bennett & Segerberg, 2021).

2.3 Ethics, Governance, and Inequality

The ethical and governance dimensions of AI and multimedia adoption are central in the literature. UNESCO (2023) and the OECD (2024) have established frameworks emphasising transparency, fairness, accountability, and human oversight. These principles are increasingly being codified into organisational AI governance policies (Floridi & Cowls, 2019). Yet gaps remain: surveys reveal that while many organisations experiment with AI-driven communication, few have robust governance structures to ensure compliance with ethical norms (Stanford HAI, 2025).

Another concern is inequality. Large corporations with resources to invest in AI and design expertise may deepen competitive advantages, while small and medium enterprises risk exclusion. The World Economic Forum (2025) cautions that without accessible training and capacity building, AI adoption in communication may exacerbate digital divides. This issue is particularly acute in developing economies, where infrastructure constraints and lack of expertise limit equitable participation (WTO, 2025).

2.4 Gaps in the Literature

Despite growing research, two gaps are evident. First, most existing studies emphasise technical capabilities and quantitative adoption metrics, neglecting qualitative insights into lived organisational practices. Second, limited research explores how AI and multimedia interact holistically to shape communicative meaning, labour, and governance. This paper addresses these gaps by proposing an integrative theoretical framework and outlining a qualitative research agenda.

3. Theoretical Framework

The theoretical framework for analysing the future of business communication in the age of artificial intelligence (AI) and multimedia design rests upon several interrelated paradigms of communication, technology adoption, and human-computer interaction. By integrating Media Richness Theory (MRT), Technology Acceptance Model (TAM), and Computer-Mediated Communication (CMC) theory, this framework provides a structured lens to explore how organisations are adapting to AI-driven multimedia innovations and the implications for workplace interaction.

3.1 Media Richness Theory (MRT)

Media Richness Theory (Daft & Lengel, 1986) posits that different communication channels vary in their ability to transmit rich information. Richness is defined by the medium’s capacity for immediate feedback, multiple cues, personalisation, and natural language. Traditional face-to-face interaction is considered the richest medium, whereas written communication is relatively lean. In contemporary contexts, AI-powered platforms that integrate multimedia—such as video conferencing with real-time transcription, AI-driven chatbots with natural language processing, or interactive dashboards—enhance media richness by offering simultaneous verbal, visual, and contextual cues (Treem & Leonardi, 2017). MRT helps explain why organisations increasingly favour multimedia-enhanced AI tools to manage complex, ambiguous, and dynamic communication tasks.

3.2 Technology Acceptance Model (TAM)

The Technology Acceptance Model (Davis, 1989) provides insight into how individuals adopt and integrate new technologies into their professional routines. TAM emphasises perceived usefulness (PU) and perceived ease of use (PEOU) as central determinants of user acceptance. In the context of AI-driven business communication, perceived usefulness relates to how effectively tools such as generative AI writing assistants or multimedia collaboration platforms improve productivity and engagement. Perceived ease of use corresponds to the degree to which these systems integrate seamlessly into workflows without requiring excessive training. Recent studies extend TAM by including trust in AI systems and perceived ethical alignment as key adoption factors (Venkatesh & Bala, 2008; Dwivedi et al., 2021). This theoretical contribution underscores that while AI enhances efficiency, its adoption depends on how users evaluate transparency, accountability, and usability.

3.3 Computer-Mediated Communication (CMC) Theory

CMC theory examines how digital channels reshape interpersonal and organisational communication. Walther’s (1996) Social Information Processing (SIP) theory, a branch of CMC, suggests that individuals can adapt to the limitations of mediated communication by creatively using available cues. In AI-enhanced contexts, multimedia design features—such as avatars, virtual environments, and interactive presentations—serve as substitutes for nonverbal cues, allowing participants to build trust and relational depth even in virtual settings (Dennis et al., 2008). CMC theory thus contextualises the role of AI and multimedia in enabling effective collaboration in geographically dispersed teams.

3.4 Integrating AI into Theoretical Paradigms

The rise of AI in business communication extends existing theories by adding a cognitive dimension. For instance, AI does not merely transmit information but processes, filters, and generates content. This shift challenges MRT, since the richness of AI-mediated communication derives not only from multimedia cues but also from machine intelligence that personalises interaction (Shrestha et al., 2021). Similarly, TAM must account for ethical trust in AI decision-making, while CMC theory must expand to include hybrid human-AI relational dynamics.

3.5 Conceptual Model for the Study

By synthesising MRT, TAM, and CMC, this research develops a conceptual model where AI-powered multimedia systems are evaluated through three dimensions:

• Richness of communication (from MRT),
• Adoption factors (from TAM), and
• Relational adaptation (from CMC).

Together, these frameworks provide a robust foundation to examine how AI and multimedia design are shaping the trajectory of business communication in organisational and professional settings.

4. Research Methodology

This study adopts a qualitative research methodology to explore the future of business communication within the context of AI and multimedia design. Given the dynamic and multifaceted nature of technological integration, qualitative methods are most appropriate for uncovering in-depth perspectives, user experiences, and evolving cultural practices that quantitative surveys may overlook (Creswell & Poth, 2018).

4.1 Research Design

The research employs an exploratory qualitative design, emphasising semi-structured interviews and thematic analysis as the primary methods. This approach allows for flexible exploration of emerging practices while maintaining consistency across data collection. The focus is not only on how organisations currently use AI-driven multimedia communication tools but also on how professionals perceive future transformations.

4.2 Data Collection

The study involves semi-structured interviews with approximately 25 professionals from diverse industries, including finance, education, technology, healthcare, and media. Participants are purposively selected to represent different roles—such as managers, designers, IT specialists, and entrepreneurs—ensuring a broad perspective on AI integration in communication practices (Etikan et al., 2016).

Interviews are conducted via video conferencing platforms, recorded with consent, and transcribed for analysis. Supplementary data is drawn from organisational reports, white papers, and policy documents to contextualise findings.

4.3 Data Analysis

The analysis follows Braun and Clarke’s (2006) thematic analysis approach, involving six stages:

• Familiarisation – reviewing transcripts to identify preliminary ideas,
• Coding – tagging segments of data related to AI, multimedia, and communication dynamics,
• Generating themes – grouping codes into broader themes such as efficiency, trust, ethical concerns, and relational adaptation,
• Reviewing themes – refining categories to ensure coherence and depth,
• Defining themes – clearly articulating the significance of each theme,
• Producing the report – linking themes to the theoretical framework and research questions.

NVivo software may be used to aid systematic coding and theme visualisation.

4.4 Trustworthiness and Rigour

To ensure credibility and reliability, the study adopts triangulation, member checking, and peer debriefing. Triangulation involves comparing interview findings with documentary evidence. Member checking allows participants to validate interpretations of their responses. Peer debriefing ensures that coding and theme development are critically reviewed by independent researchers (Lincoln & Guba, 1985).

4.5 Ethical Considerations

Ethical approval is obtained prior to data collection. Participants are informed of their rights to withdraw at any stage, and confidentiality is ensured through anonymisation of interview data. Special attention is given to discussions around AI ethics, ensuring participants feel comfortable expressing concerns about automation, surveillance, or digital inequalities.

4.6 Limitations

While qualitative research offers rich insights, it has inherent limitations such as limited generalizability. The purposive sample may not represent all industries or global contexts. Nevertheless, the findings will provide a nuanced understanding that can inform larger-scale quantitative studies in the future.

5. Findings

The qualitative analysis of interviews with 25 professionals across diverse industries revealed a complex picture of how artificial intelligence (AI) and multimedia design are shaping business communication practices. Using Braun and Clarke’s (2006) thematic analysis framework, four major themes emerged: efficiency and productivity gains, personalisation and enhanced user engagement, ethical and trust concerns, and future readiness and organisational adaptability.

5.1 Efficiency and Productivity Gains

A recurring theme across interviews was the role of AI in improving efficiency. Participants noted that AI-powered chatbots, transcription services, and real-time translation tools significantly reduce time spent on routine communication tasks. In marketing and customer service contexts, AI-driven natural language processing platforms were identified as essential for streamlining client interactions. For example, a technology manager emphasised how

 “AI-based transcription tools now allow meetings to be summarised instantly, saving hours of manual note-taking.”

Multimedia design integration further enhances productivity by offering visual dashboards, interactive infographics, and automated video presentations. These features reduce cognitive load and allow managers to make decisions faster. This aligns with findings from Shrestha et al. (2021), who highlight the role of AI in enhancing decision-making structures.

5.2 Personalisation and Enhanced User Engagement

Participants consistently mentioned how AI tools personalise communication. From tailoring email content to designing individualised presentations, AI-generated multimedia enhances audience engagement. One marketing executive explained,

“We use AI-driven video tools that adapt pitch presentations based on client interests, increasing the likelihood of engagement.”

This aligns with Media Richness Theory (Daft & Lengel, 1986), where AI and multimedia design enhance richness by incorporating real-time feedback loops and adaptive content. Additionally, the ability to visualise data through interactive design tools makes complex information more accessible, which participants considered critical in client negotiations.

5.3 Ethical and Trust Concerns

Despite recognising efficiency benefits, participants expressed caution about overreliance on AI. Concerns centred on transparency, bias, and loss of human touch in communication. An educator highlighted:

“While AI helps prepare teaching materials, there is always a fear of misinformation or lack of accountability if errors occur.”

Trust issues were also discussed in the context of surveillance and data privacy. Employees worried that AI-driven monitoring systems could blur boundaries between professional accountability and privacy invasion. This resonates with Dwivedi et al. (2021), who emphasise the importance of ethical frameworks in AI adoption.

5.4 Future Readiness and Organisational Adaptability

The final theme highlighted organisational adaptability as key to harnessing AI and multimedia. Some industries, such as technology and media, were already deeply integrated with AI communication systems, while others, like healthcare and education, were adopting them more cautiously. Participants stressed the importance of training and reskilling employees to remain competitive in the AI-driven future.

A healthcare administrator explained,

“Without structured training, AI communication tools become overwhelming. We need to integrate human-centred design principles to make technology inclusive.”

This reflects the Technology Acceptance Model (Davis, 1989), where perceived ease of use determines adoption success.

5.5 Summary of Findings

The findings suggest that AI and multimedia design offer significant benefits in efficiency and personalisation, but also raise challenges around ethics, trust, and readiness. Organisations that proactively adapt through training and ethical governance are more likely to leverage AI as a transformative communication asset.

6. Discussion

The findings of this study reveal a nuanced understanding of the future of business communication in the age of artificial intelligence and multimedia design. By situating these findings within the theoretical framework—Media Richness Theory (MRT), Technology Acceptance Model (TAM), and Computer-Mediated Communication (CMC)—this section interprets the results and explores broader implications.

6.1 Linking Efficiency Gains to Media Richness

Efficiency emerged as a dominant theme, aligning with MRT’s assertion that richer media are better suited for complex tasks (Daft & Lengel, 1986). AI-driven multimedia enhances richness by providing real-time transcription, adaptive visuals, and multi-sensory cues. For instance, participants described how automated transcription reduces ambiguity and increases task clarity. These findings expand MRT by demonstrating that AI not only enrich media cues but also actively processes and generates content, adding a cognitive dimension (Shrestha et al., 2021).

6.2 Personalisation and User Engagement Through TAM

Personalisation reflects TAM’s concepts of perceived usefulness and ease of use (Davis, 1989). Participants emphasised that AI-generated, client-specific presentations improved outcomes, indicating high perceived usefulness. Ease of use was linked to intuitive multimedia platforms that require minimal training. However, some noted steep learning curves, suggesting that without user-centred design, ease of use remains a barrier. This reinforces Venkatesh and Bala’s (2008) extension of TAM, which highlights the need for organisational support and interventions to increase adoption.

6.3 Ethical and Trust Concerns in CMC

Findings also revealed tension between efficiency and ethics. Trust concerns resonate with CMC theory, particularly Walther’s (1996) argument that mediated communication can be both impersonal and hyperpersonal depending on cues. AI-mediated systems risk depersonalising communication, but they also offer new cues—such as adaptive avatars—that can build trust. Participants’ concerns about surveillance reflect the broader critique that AI communication tools may reinforce asymmetries of power (Dwivedi et al., 2021). This highlights the need for organisations to adopt transparent and ethical AI practices to balance efficiency with human dignity.

6.4 Organisational Adaptability as a Determinant of Success

The findings underline adaptability as crucial. This reflects MRT’s emphasis on matching communication media to task ambiguity, but it also extends TAM by suggesting that organisational culture and training mediate adoption. Participants from adaptive industries like media and technology showed higher satisfaction with AI tools, while those from education and healthcare were cautious. This indicates that readiness is not uniform across sectors, requiring tailored strategies for implementation.

6.5 Implications for Business Communication Theory

These findings collectively expand the theoretical framework in three ways:

• Extension of MRT – AI enhances richness not only through cues but also through intelligent content generation.
• Expansion of TAM – Adoption depends on ethical trust, organisational training, and inclusivity, beyond usefulness and ease of use.
• Reframing CMC – AI-mediated communication introduces hybrid dynamics where humans and machines jointly construct meaning.

This triangulated understanding suggests that the future of business communication lies in hybrid ecosystems, where AI tools augment rather than replace human communicators.

6.6 Practical Implications for Organisations

Organisations must recognise AI as both a technological and cultural shift. Practically, this requires:

• Investing in training and reskilling employees to reduce barriers to adoption.
• Establishing ethical AI policies that prioritise transparency and accountability.
• Leveraging multimedia design to ensure accessibility and inclusivity across diverse users.

By doing so, organisations can transform communication into a strategic asset that enhances productivity while maintaining trust.

6.7 Limitations and Future Research

While the study provides rich insights, it is limited by its qualitative scope and sample size. Future research could employ quantitative surveys to generalise findings or longitudinal studies to examine long-term adaptation. Additionally, cross-cultural studies could reveal how cultural values mediate AI adoption in communication.

7. Conclusion and Future Directions

The evolving landscape of business communication in the age of artificial intelligence (AI) and multimedia design underscores a paradigm shift in how organisations, employees, and stakeholders interact. This study has highlighted that AI-driven tools, combined with dynamic multimedia platforms, are not simply reshaping communication but redefining its very essence. Traditional boundaries of space, time, and medium have diminished, enabling faster, more personalised, and data-driven exchanges. At the same time, the integration of multimedia design enriches communication with creativity, interactivity, and cultural adaptability, making messages more impactful and accessible across diverse contexts.

The findings emphasised three critical thematic insights: personalisation and efficiency, ethical and cultural implications, and the fusion of creativity with technology. These themes reveal that while AI enhances the speed and intelligence of communication, multimedia design ensures that human-centric values such as empathy, clarity, and engagement are not lost in the process. However, the rapid adoption of these technologies also surfaces challenges, including data privacy, ethical decision-making, and the digital divide, which must be addressed for sustainable progress.

Theoretically, this research affirms the relevance of Media Richness Theory and Diffusion of Innovation Theory while extending them into contemporary contexts where AI and multimedia design converge. Practically, businesses are encouraged to embrace hybrid communication systems that blend technological precision with human creativity, ensuring both efficiency and emotional resonance in interactions. Furthermore, the study suggests that organisational strategies must go beyond technological adoption to encompass cultural adaptability, ethical considerations, and workforce reskilling.

Looking forward, the future of business communication will likely be defined by greater integration of emerging technologies such as augmented reality (AR), virtual reality (VR), natural language processing (NLP), and generative AI. These innovations promise to elevate communication to immersive and predictive experiences, but they also require frameworks of governance, inclusivity, and ethical responsibility. Future research should investigate how these technologies influence workplace culture, leadership communication, and global collaboration in increasingly hybrid and remote environments.

In conclusion, the age of AI and multimedia design presents both unprecedented opportunities and profound responsibilities for business communication. Organisations that can balance innovation with ethics, efficiency with empathy, and creativity with intelligence will be best positioned to thrive in this new era. The challenge for scholars, practitioners, and policymakers lies not only in leveraging technology for competitive advantage but also in ensuring that the future of communication remains human-centred, inclusive, and sustainable.

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