Can AI Assistance Foster Social Cohesion?

Introduction

AI assistance has emerged as a powerful tool for enhancing social cohesion across various sectors, from enterprise environments to community settings. The integration of AI technologies offers unprecedented opportunities to bridge divides, facilitate communication, and create more inclusive digital spaces that strengthen social bonds. In today’s increasingly digitalized world, thoughtfully implemented AI systems can address existing inequalities while promoting collaboration and shared understanding. This report examines how various AI applications, enterprise systems, and collaborative development approaches can work together to foster greater social cohesion, while highlighting the importance of human oversight, community engagement, and ethical governance in achieving these goals.

The Digital Divide and Social Cohesion Challenges

Understanding the Digital Divide’s Impact on Social Cohesion

The relationship between digitalization and social cohesion is complex and multifaceted, with technology often amplifying existing social inequalities rather than alleviating them. According to Dr. Gesche Joost, Professor of Design Research at the Berlin University of the Arts, the digital divide can be understood across three critical levels: access to technology, skills to use it effectively, and the ability to employ digitalization for one’s own objectives. These disparities create barriers to participation in digital society, leaving many individuals and communities excluded from important conversations and opportunities. The resulting fragmentation of the social fabric undermines cohesion and limits the possibility of creating truly inclusive digital spaces where diverse voices can contribute equally to societal dialogue. In regions where digital infrastructure is inadequate or internet access is limited, entire communities may find themselves increasingly isolated from digital advancements, further widening societal gaps and reinforcing patterns of inequality.

AI as Both Challenge and Opportunity for Social Cohesion

While AI technologies present certain risks to social cohesion, particularly when deployed without careful consideration of their societal impacts, they also offer tremendous potential for connecting people across traditional divides. Current research suggests that AI can either strengthen or weaken social bonds depending on how it is designed, deployed, and governed. Without proper oversight, AI systems may reproduce or even amplify existing biases and discriminations already present in society, potentially locking people into cultural bubbles rather than exposing them to diverse perspectives and experiences. However, when thoughtfully implemented with community involvement, AI can serve as a powerful tool for strengthening social fabric and enabling new forms of large-scale solidarity and cooperation. The transformative impact of AI on social cohesion ultimately depends on whether we prioritize human-centered design principles that enhance connection rather than prioritizing efficiency at the expense of human relationships.

Enterprise Systems and Low-Code Platforms: Democratizing AI Development

Enterprise Software Systems as Foundations for Collaborative AI Solutions

Enterprise Systems and Enterprise Software provide robust foundations upon which organizations can build AI-powered solutions that foster social cohesion within and between communities. These comprehensive Business Enterprise Software ecosystems integrate various business processes and information flows, creating interconnected environments where AI assistance can be effectively deployed to enhance collaboration and understanding. Modern Enterprise Resource Planning (ERP) systems facilitate real-time information sharing across organizational boundaries, breaking down silos that traditionally impede cooperation and mutual understanding. By integrating AI capabilities into existing Enterprise Computing Solutions, organizations can develop applications that not only streamline operations but also promote inclusivity and participation across diverse stakeholder groups. Business Software Solutions enhanced with AI can be tailored to address social cohesion challenges specific to particular communities or regions, ensuring that technology serves human needs rather than the reverse.

Low-Code Platforms and the Democratization of AI Development

Low-Code Platforms have emerged as powerful tools for democratizing AI application development, allowing individuals without extensive programming backgrounds to create solutions that address social cohesion challenges in their communities. These platforms provide drag-and-drop interfaces, visual modeling tools, and pre-built templates that significantly reduce the technical barriers to creating functional applications. By 2025, low-code development environments are enabling non-technical users to rapidly prototype and deploy AI-powered tools for community engagement, cross-cultural communication, and collaborative decision-making. The accessibility of these platforms is particularly important for addressing social cohesion challenges, as they allow solutions to be developed by the very people experiencing these challenges, ensuring greater relevance and cultural sensitivity. When combined with AI Application Generators, low-code platforms empower community leaders and organizations to create specialized tools that facilitate dialogue, coordinate resources, and strengthen connections between community members who might otherwise remain isolated from one another.

Citizen Developers and Business Technologists: New Roles in Social Innovation

The Rise of Citizen Developers in Community-Centered AI Solutions

Citizen Developers represent a new approach to technology creation that aligns perfectly with the goal of enhancing social cohesion through AI assistance. These individuals, who develop applications using no-code and low-code tools rather than traditional programming languages, are bringing fresh perspectives to social challenges that might otherwise be overlooked by mainstream technology developers. The citizen development movement promotes a more accessible approach to coding, giving people sovereignty over their digital tools and the opportunity to develop projects rapidly and at lower costs. This democratization of technology creation is particularly valuable for addressing social cohesion challenges, as it enables diverse voices to contribute to solution development. Citizen Developers from marginalized communities can create AI-powered applications that specifically address the unique cohesion challenges facing their communities, ensuring that technology development becomes a more inclusive and representative process that strengthens rather than weakens social bonds.

Business Technologists: Bridging Technical Capability and Social Understanding

Business Technologists play a crucial role in developing AI solutions that enhance social cohesion by working outside traditional IT departments to craft innovative technological solutions tailored to specific community needs. These professionals apply their technological expertise to improve efficiency, drive growth, and facilitate informed decision-making in ways that strengthen social connections rather than undermining them. Their position at the intersection of business operations and technology development makes them uniquely qualified to identify opportunities where AI assistance can address social fragmentation and promote greater cohesion. By understanding both the technical capabilities of AI systems and the social contexts in which they operate, Business Technologists can design Enterprise Business Architecture that embeds cohesion-enhancing features directly into organizational systems and processes. Their work ensures that technology serves human connection rather than replacing it, focusing AI implementation on augmenting human capabilities for collaboration, understanding, and mutual support.

AI Applications in Community and Civic Engagement

AI-Enhanced Community Engagement Platforms

AI offers transformative approaches to community engagement that can significantly strengthen social cohesion by making participation more accessible, meaningful, and responsive. Modern AI applications can personalize communications to community members based on their preferences, behaviors, and interests, making each person feel valued and understood rather than just another name on a list. These personalized interactions create stronger connections between community members and the organizations serving them, fostering a sense of belonging that is essential to social cohesion. AI-powered chatbots can provide immediate responses to community inquiries, ensuring that people receive timely information and support even outside regular business hours. This consistent availability helps maintain engagement and prevents the frustration that can result from delayed responses, particularly in crisis situations where timely information is crucial for maintaining community trust and cohesion.

AI for Civic Participation and Collective Decision-Making

In the civic sphere, AI assistance is transforming how communities participate in governance and collective decision-making processes, creating more inclusive and cohesive democratic systems. Gen AI technologies now help overcome language barriers through real-time translation services for civic engagement activities such as public meetings, making participation possible for linguistically diverse communities. This language accessibility is crucial for social cohesion in multicultural societies, where language differences can otherwise lead to the exclusion of immigrant communities from important civic processes. AI can also synthesize complex technical documents into more understandable formats, making government information more accessible to people with varying levels of education and expertise. Additionally, Large Language Models (LLMs) are being applied to enhance collective dialogue systems that allow thousands of participants to engage in structured conversations that feel less chaotic and more productive, ensuring that everyone feels heard and finds value in participating. These enhanced dialogue spaces help communities find common ground and build bridges across traditional divides, strengthening the fabric of social cohesion.

Healthcare Systems: AI in Care Management and Hospital Management

AI-Powered Care Management for Equitable Health Access

The integration of AI into Care Management systems represents a significant opportunity to enhance social cohesion by making healthcare more accessible, personalized, and equitable across diverse communities. AI and automation are transforming care management by promoting seamless care coordination while accounting for cost, quality, equity, and patient experience factors that strongly influence social cohesion. AI-powered systems can reduce administrative burdens on healthcare professionals by automating tasks like appointment scheduling and insurance verification, freeing up valuable time for more meaningful patient interactions that build trust and connection. This efficiency doesn’t just save money-it creates space for the human relationships that form the foundation of cohesive communities. AI can also enhance risk identification and care personalization, analyzing patterns in historical data to help care managers develop more effective strategies for serving vulnerable populations. By ensuring that healthcare resources reach those who need them most, AI-enhanced care management can help address health disparities that often correlate with and reinforce social fragmentation.

Hospital Management Systems and Community-Centered Healthcare

In the broader context of Hospital Management, AI systems are enabling more community-centered approaches to healthcare delivery that strengthen bonds between healthcare institutions and the communities they serve. AI can optimize numerous facets of hospital operations, including administrative processes, clinical decision-making, and patient engagement initiatives that collectively enhance a hospital’s role as a community anchor. By streamlining operations and improving efficiency, AI allows hospitals to dedicate more resources to community outreach and engagement programs that build relationships across diverse populations. AI-powered data management systems can organize and analyze Electronic Health Records (EHRs) to identify community-level health trends and social determinants of health that may be undermining cohesion. This population-level insight enables hospitals to develop more targeted interventions that address not just individual health needs but also community-wide challenges that impact social cohesion. As hospitals increasingly serve as hubs for community well-being beyond just medical treatment, AI systems that enhance their operational effectiveness directly contribute to stronger, more cohesive communities.

Case Management and Enterprise Resource Planning for Social Services

AI-Enhanced Case Management Systems for Vulnerable Populations

Case Management systems enhanced with AI capabilities are revolutionizing how organizations coordinate services for vulnerable populations, directly strengthening social cohesion by ensuring no one falls through the cracks of social support systems. AI automates routine tasks, enhances data accuracy, and enables faster case resolutions, allowing teams to focus on more strategic and high-value activities that build relationships with clients and communities. These efficiencies are particularly important in sectors like legal aid, healthcare, and social services, where timely interventions can prevent crises that undermine both individual wellbeing and community stability. AI-powered case management can process both structured and unstructured data, using natural language processing and machine learning to categorize and prioritize relevant information, making it easier to access and analyze at scale. This comprehensive data integration enables more holistic approaches to addressing complex social needs that cross traditional service boundaries. Additionally, AI can analyze historical case outcomes to identify patterns that lead to successful resolutions, offering case managers insights into the most effective strategies for supporting clients while ensuring consistency in decision-making across cases.

Enterprise Resource Planning for Coordinated Social Services

Enterprise Resource Planning (ERP) systems, when augmented with AI capabilities, provide powerful platforms for coordinating social services across multiple agencies and programs, creating more cohesive support networks for vulnerable communities. Modern ERP systems facilitate the integrated management of main business processes in real-time, collecting, storing, managing, and interpreting data from many activities within a unified framework. This integration is particularly valuable for social service coordination, where fragmentation between different programs and funding streams often creates barriers for clients and undermines the effectiveness of interventions. AI-enhanced Enterprise Resource Systems can analyze complex patterns of service utilization across different agencies, identifying gaps and redundancies that may be leaving certain populations under-served. Enterprise Systems Groups managing social services can use these insights to develop more coordinated approaches that strengthen community safety nets and foster greater cohesion. By ensuring that Enterprise Products and services work together seamlessly to address human needs, AI-enhanced ERP systems help create more responsive and inclusive social support ecosystems that strengthen rather than fragment communities.

Open-Source AI and Technology Transfer: Sharing Innovation for Social Benefit

Open-Source AI Development for Inclusive Innovation

Open-source artificial intelligence has emerged as a powerful approach for democratizing access to AI technologies, thereby promoting greater inclusivity and social cohesion across different communities and socioeconomic groups. Open-source AI systems are freely available to use, study, modify, and share, with these attributes extending to all components including datasets, code, and model parameters. This accessibility ensures that AI innovations can benefit a wider range of communities rather than being concentrated among those with the most resources, directly addressing one aspect of the digital divide that threatens social cohesion. The collaborative and transparent nature of open-source development also encourages diverse contributions, bringing together perspectives from different cultural backgrounds, disciplines, and life experiences to create more inclusive and culturally sensitive AI systems. While concerns exist about potential risks from removing safety protocols in open-source models, the collaborative oversight of the open-source community often provides a counterbalance through shared responsibility for ethical development. By lowering barriers to AI innovation, open-source approaches enable more communities to develop solutions tailored to their specific cohesion challenges.

Technology Transfer and AI-Enabled Social Innovation

Technology transfer processes enhanced by AI are accelerating the spread of social innovations that promote cohesion across diverse communities and contexts. The technology transfer process, which involves moving innovations from research settings to practical applications, benefits from AI tools at every stage from invention disclosure to licensing and financial return. AI-based prior art search tools help evaluate new inventions more efficiently, while automation streamlines contract management and patent drafting, making the entire process more accessible to a wider range of innovators. This democratization of innovation pathways helps ensure that useful social technologies can spread more rapidly to communities that need them, rather than remaining siloed in academic or corporate environments. For technology transfer to effectively support social cohesion, four critical elements must be addressed: good quality data for AI training, affordable data storage, well-established policies for AI use in technology transfer, and security measures for confidential information. When these conditions are met, AI-enabled technology transfer can serve as a powerful mechanism for sharing social innovations that strengthen community bonds and address cohesion challenges across different contexts.

Governance and Community Engagement: Ensuring AI Promotes Cohesion

AI Governance and Bill of Materials for Responsible Implementation

Effective governance frameworks for AI implementation are essential to ensuring that these technologies enhance rather than undermine social cohesion across diverse communities. An AI Bill of Materials (AI-BOM), similar to a Software Bill of Materials (SBOM), provides a complete inventory of all assets in an organization’s AI ecosystem, documenting datasets, models, software, hardware, and dependencies across the entire lifecycle. This comprehensive documentation creates the visibility needed to secure AI systems effectively and identify potential sources of bias or exclusion that could harm social cohesion. Unlike traditional software, AI involves non-deterministic models, evolving algorithms, and data dependencies that require more expansive monitoring and governance. Organizations implementing AI must ensure their governance frameworks address these complexities while prioritizing inclusive development practices. As AI becomes increasingly embedded in enterprise systems that shape community interactions, governance approaches that prioritize transparency, accountability, and inclusivity become essential safeguards for social cohesion, particularly when AI applications directly impact vulnerable or marginalized communities.

Community Engagement in AI Design and Implementation

Community engagement must be central to AI development processes to ensure these technologies genuinely promote social cohesion rather than reinforcing existing divides. Public health researchers have highlighted that there is a critical need for community engagement in the process of adopting AI technologies, particularly when these technologies affect population-level outcomes. Without such engagement, AI adoption may exclude significant portions of the population, particularly those with the fewest resources, potentially exacerbating inequities that undermine social cohesion. A multi-faceted approach to ensuring safer and more effective integration of AI includes: incorporating AI fundamentals in professional training, using community engagement approaches to co-design AI technologies, and introducing governance mechanisms that guide AI use to prevent potential harms. This participatory approach enhances the relevance and acceptability of AI solutions while also identifying and addressing potential biases early in the development process. The field of public health, with its established tradition of community engagement, offers valuable models for how AI development can incorporate diverse perspectives to create technologies that genuinely strengthen rather than weaken social bonds.

Digital Transformation Through AI: Building More Cohesive Communities

AI-Driven Digital Transformation for Inclusive Growth

Digital transformation powered by AI offers pathways to more inclusive economic and social development that can strengthen cohesion within and between communities. When thoughtfully implemented, AI-driven digital transformation can help address inequalities rather than amplifying them, creating more opportunities for marginalized communities to participate in the digital economy. Enterprise Systems that incorporate AI capabilities can help businesses become more responsive to diverse customer needs and more inclusive in their operations and hiring practices. By automating routine tasks, AI frees human workers to focus on relationship-building and creative problem-solving that strengthen social connections within organizations and with the communities they serve. However, achieving these positive outcomes requires intentional design choices that prioritize human connection over pure efficiency and profit maximization. Organizations undertaking AI Enterprise initiatives must consider how their technological choices will impact social dynamics both internally and in the broader communities where they operate. When digital transformation strategies explicitly include social cohesion as a goal, AI can serve as a powerful tool for building more connected and inclusive communities.

Building AI-Enabled Community Platforms for Collaborative Action

AI-enabled community platforms are emerging as powerful tools for facilitating collaborative action across traditional social divides, directly enhancing social cohesion through structured interaction and cooperation. These platforms use AI to create more accessible and inclusive spaces for community dialogue, resource sharing, and collective problem-solving. For example, AI can help moderate online discussions in ways that promote constructive engagement rather than polarization, identifying points of common ground and helping participants understand diverse perspectives. AI-powered collective dialogue systems like Pol.is are making it possible to conduct structured conversations involving thousands of participants in ways that ensure everyone feels heard and finds value in participating. These enhanced dialogue capabilities are particularly valuable in diverse communities where language barriers, different communication styles, or historical tensions might otherwise impede productive engagement. By creating structured spaces for collaborative interaction, AI-enabled community platforms help build the mutual understanding and shared purpose that form the foundation of social cohesion. These platforms demonstrate how thoughtfully designed AI systems can strengthen rather than weaken the human connections that bind communities together.

Conclusion: A Framework for AI-Enabled Social Cohesion

The integration of AI assistance across enterprise systems, community platforms, and public services offers tremendous potential for enhancing social cohesion, but realizing this potential requires thoughtful implementation guided by clear principles. As we have seen, AI can either strengthen or undermine social cohesion depending on how it is designed, deployed, and governed. The democratization of AI development through low-code platforms and open-source approaches helps ensure these technologies reflect diverse community needs rather than reinforcing existing power structures. New roles like Citizen Developers and Business Technologists are bringing fresh perspectives to technology creation, making AI more responsive to real community challenges. AI applications in community engagement, healthcare, case management, and civic participation demonstrate concrete ways these technologies can strengthen social bonds by making systems more accessible, responsive, and inclusive.

To maximize AI’s positive impact on social cohesion, organizations must prioritize community engagement in AI development, ensure transparent governance through mechanisms like AI-BOMs, and design systems that augment rather than replace human connection. Successful integration of AI for social cohesion must be powered by people who use their judgment to validate outputs, mitigate potential errors, contextualize results, and build trust between institutions and communities. Without this human oversight and direction, even the most sophisticated AI systems may inadvertently reinforce divides or create new forms of exclusion. By embedding social cohesion goals directly into AI development processes and governance frameworks, we can harness these powerful technologies to build more connected, inclusive, and resilient communities that bridge traditional divides of geography, language, culture, and socioeconomic status.