Thursday, August 28, 2025

From Power to Purpose

 

Author : AM Tris Hardyanto


Power is born from necessity, but it often grows into domination. Security forces have been at the forefront of protecting the people and maintaining the regime since the beginning of governments. The blurring of police and military lines erodes public trust, ignites protests, and tests legitimacy. In this digital era, we face a defining question: who does power truly serve  the state or its citizens?


From Power to Purpose

Shaping Governance for Public Happiness in the Digital Era

 

The Origins of Power

 

The emergence of governments can be traced back to the increasing complexity and size of human societies, which necessitated a central authority to adjudicate disputes, allocate resources, and protect territorial integrity. The transition from decentralised governance to centralised power led to the establishment of police and military forces, which evolved from their initial role of protecting citizens to become instruments of regime preservation and stability. As state functions matured, police and military units began to intersect more frequently, intertwining power with fear and security in modern governance frameworks.

During the historical transition towards modern nation-states, police forces initially shared overlapping roles with military operations. Lutterbeck's analysis highlights transformation, noting that the distinct functions of police and military forces began to blur, particularly with the emergence of late or postmodern governance structures (Lutterbeck, 2005). As nations faced complex internal and external threats, the roles of policing and military were redefined, leading to what some researchers describe as an integrated security approach (Lutterbeck, 2004).

The relationship between public Trust and police legitimacy is further complicated by how citizens perceive the government's overall performance. Research indicates that factors such as governmental responsiveness, legitimacy, and economic conditions significantly influence public assessments of police effectiveness (Sun et al., 2013). The legitimacy of police as an institution cannot be separated from the broader governance context; failing to address underlying issues of Trust leads to detrimental consequences for public safety and community cooperation (Goldsmith, 2005). Thus, police forces, while fundamentally tasked with law enforcement, also contribute significantly to the development of state-citizen relations within increasingly complex public governance.

Moreover, the militarisation of police forces mirrors a worldwide trend where domestic policing increasingly employs military-style tactics, obfuscating the distinction between upholding public order and handling perceived external threats. For example, Meliala describes Indonesia's approach, emphasising the rise of paramilitary policing, which is characterised by authoritarian structures aimed at ensuring control and order (Meliala, 2001). The shift towards militarisation raises crucial ethical concerns about human rights, particularly as it often coincides with diminished civil liberties and an erosion of democratic principles (FloresMacías & Zarkin, 2023).

Additionally, the concept of police militarisation effectively embodies the problematic convergence identified in several studies. Campbell and Campbell illustrate the evolving role of police officers who increasingly adopt military roles in their enforcement strategies, creating a complex image of law enforcement as both protector and enforcer of state authority (Campbell & Campbell, 2009). Evolution can distort the perceived role of police, shifting from community-focused caretakers to enforcers of a regime, thereby complicating their public perception and legitimacy.

The origins of modern governance are rooted in the evolution of state authority, which is intertwined with power, fear, and security. The bifurcation and subsequent convergence of police and military functions, alongside the factors affecting public Trust, highlight the complexities inherent in contemporary governance landscapes. Policymakers must navigate these dynamics carefully to establish a governance model that fosters public Trust while ensuring adequate security and justice.

 

The Crisis of Trust

 


In the current landscape, the demand for fairness, dignity, and representation from governments has become increasingly vocal, particularly in the context of societal unrest and mass protests. A crucial factor in the breakdown of public Trust is the government's failure to meet these socio-political expectations. Research indicates that corruption, economic inequality, and systemic repression are significant contributors to public frustration, often culminating in mass mobilisations, such as those observed during the Arab Spring and China's recent protests over land and labour disputes (Zárate-Tenorio, 2014; Chan, 2010). These events have underscored a common sentiment among citizens: the desire for their voices to be amplified and for their rights to be acknowledged and protected.

The trust crisis manifests when citizens perceive a disconnect between governmental actions and their demands for accountability and representation. A lack of transparent processes and accountability mechanisms can erode public Trust, indicating a "vicious circle" where decreasing Trust leads to diminished government legitimacy, potentially sparking further protests and instability (Hyndman & McConville, 2018; Goldsmith, 2005). As noted in extensive research across various case studies, the public's perception of governmental accountability has a direct influence on their levels of Trust. For instance, citizens believe that transparency in governance correlates positively with public Trust, establishing that societal expectations align closely with the accountability demonstrated by those in power (Beshi & Kaur, 2019; Prasetya, 2023).

Moreover, mass protests during periods of economic distress or political corruption can be understood as forms of collective resistance that challenge the existing social contract. Scholars have emphasised that citizens will mobilise against governmental actions perceived as unfair, especially when there is a tangible threat to their economic wellbeing (Charm, 2024; Chan, 2010). Research indicates that a government's responsiveness to public grievances plays a crucial role in preventing escalations into widespread unrest (Kim et al., 2020; Ragolane & Malatji, 2024). Thus, the dynamics of Trust and governance in the modern era suggest that governments need to actively engage with and respond to citizen demands to mitigate the risks of unrest.

The implications of these dynamics are significant, particularly for the role of law enforcement during protests. Studies have demonstrated that policing strategies perceived as aggressive or repressive can exacerbate the crisis of Trust and lead to further alienation of the populace (Gillham et al., 2013; Sombatpoonsiri, 2017). In contrast, approaches that balance the needs of law enforcement with the rights of protesters can enhance police legitimacy and reduce public distrust (Goldsmith, 2005). The relationship between governance, policing, and public perception is crucial for maintaining stability and ensuring that societal needs are addressed in a constructive manner.

The crisis of Trust in contemporary governance is closely tied to the failure of governments to fulfil citizens' desires for security, fairness, and representation. Protests emerge as a poignant response to governance failures and systemic injustices, underscoring the importance of maintaining a robust social contract founded on accountability and Trust. By fostering transparent governance practices and responsive policing, governments can mitigate risks of unrest and rebuild public Trust.

 

The Digital Crossroads

 

In the digital era, the transformation of power dynamics in governance is increasingly evident as technologies such as artificial intelligence (AI), blockchain, and big data provide governments with enhanced capabilities to monitor, predict, and influence citizens. The technological revolution has led to the emergence of three potential governance models: digital authoritarianism, reform and transparency, and civic hybrid models. The pathways nations choose in implementing these technologies will significantly shape their societal structures for future generations.

Digital authoritarianism represents a governance model where technology is harnessed to bolster state control and suppress dissent. A model can manifest through extensive surveillance systems, the use of big data analytics to predict and preempt social unrest, and the manipulation of public discourse via information control (Piotrowski, 2016; Redden, 2018). Governments may exploit these technologies to limit freedoms and enforce compliance, particularly in regimes with a history of repression and political instability. Research demonstrates that as governments adopt data-driven governance strategies, the potential for abuse of power increases, particularly if there are inadequate checks on governmental authority (Ha, 2024).

In contrast, the Reform & Transparency model utilises digital tools to enhance government accountability, promote citizen engagement, and enhance service delivery. By using open data technologies for initiatives, governments can foster transparency and empower citizens to hold public officials accountable for their actions (Chen & Ganapati, 2021; Mees & Driessen, 2018). Such reforms help to diminish corruption and restore public Trust in state institutions. Studies have shown that increased transparency in governmental operations correlates with higher levels of public Trust (Niu, 2022; Grimmelikhuijsen & Feeney, 2016). Additionally, applying data-driven governance to streamline administrative processes has been shown to enhance efficiency and accessibility of public services, thereby promoting a more inclusive approach to governance (Katapally & Ibrahim, 2023).

The Civic Hybrid Model is an amalgamation of the two previous approaches, emphasising shared decision-making between governments and communities. The model recognises the importance of citizen input in governance while simultaneously utilising digital tools to facilitate collaborative processes (Chien & Thanh, 2022; Darusalam et al., 2023). Local governments adopting a hybrid approach often implement participatory budgeting, neighbourhood planning, and community monitoring systems that allow for a more democratic governance framework (Setyawan, 2024). By integrating citizen perspectives through digital platforms, governments can better align their policies with the needs and values of their constituents, ultimately creating an atmosphere of ownership and accountability.

The choices made by nations today regarding these digital governance models will undoubtedly have profound implications for societal structure and citizen engagement in the years to come. The quest for balance between security and freedom, control, and empowerment is pivotal as countries navigate the complexities of the digital landscape. Policymakers must critically evaluate existing technologies and their potential impacts, striving for a governance model that prioritises human dignity and equitable representation while safeguarding against the risks of authoritarianism.

In conclusion, the digital crossroads present a critical juncture for governance in the 21st century. The paths chosen—whether towards digital authoritarianism, reform and transparency, or civic hybrid models—will shape the contours of society and democratic engagement, defining the relationship between the state and citizens for generations.

 

 Future Pathways to 2050

By 2050, global governance will be shaped by how we integrate technology, democracy, and human values. If digital tools are weaponised, authoritarian regimes will dominate, eroding freedoms. If transparency prevails, digital democracy can flourish, fostering greater equity and Trust. Hybrid governance models may emerge, blending centralised authority with community-driven decision-making processes. The coming decades will test humanity's collective wisdom and redefine the meaning of citizenship.

As we approach 2050, the interplay between technology, democratic governance, and human values will critically define the future of global governance. Digital tools have the potential to profoundly reshape societies, ushering in varied governance models: digital authoritarianism, reform and transparency, and civic hybrid models. The trajectory nations take in utilising these technologies will likely determine the nature of citizenship and the degree of freedom and equity experienced by their populations.

In a scenario of digital authoritarianism, governments might weaponise digital technologies to enhance their control and suppress dissent. Such regimes utilise advanced surveillance capabilities, AI-driven predictive analytics, and social media manipulation, resulting in a significant erosion of civil liberties and freedoms (Indama, 2022; Li et al., 2023). The perils inherent in models have been extensively highlighted, indicating that unchecked technological power could result in oppressive regimes dominating the global landscape. Instances of surveillance capitalism have raised concerns about privacy and the potential for autocratic governance to be facilitated through digital means.

Conversely, governments could choose a path characterised by reform and transparency, embracing digital technologies to enhance governance quality and citizen engagement. The approach centres on enhancing transparency, promoting accountability, and encouraging participation in decision-making processes (Bokhtiar et al., 2023; Hartanti et al., 2021). Trust in governmental institutions is crucial, as evidenced by research indicating that effective governance during crises, such as the COVID-19 pandemic, can enhance public Trust (Goldfinch et al., 2021). Strategies that prioritise transparency, such as open data initiatives and participatory governance models, are likely to encourage citizen involvement and improve public Trust, thereby reinforcing the social contract between the state and its citizens (Lee, 2021; Amosun et al., 2021).

The Civic Hybrid Model may emerge as a solution that integrates elements from both authoritarian and democratic frameworks. The model emphasises a collaborative approach to governance, where state authorities and citizens participate jointly in decision-making processes (Dananjoyo & Udin, 2023). By combining centralised governance with community-driven strategies, hybrid models could facilitate a more inclusive dialogue that addresses local needs while maintaining broader governance structures. An approach can bridge the gap between government action and community needs, leveraging technology to empower civic engagement and enhance the perceived legitimacy of governance (Lusianti et al., 2024). The cultivation of citizen trust in digital services is fundamental to the model, as Trust is a critical determinant of citizen engagement and satisfaction in innovative government services (Amosun et al., 2021; Shen et al., 2022).

The coming decades will pose significant challenges as societies navigate these various pathways. The integration of technology into governance will test humanity's collective wisdom and ethical standards. The decisions made by political leaders regarding the use and regulation of digital tools will have far-reaching consequences for the freedoms, rights, and responsibilities of citizens, ultimately redefining what it means to participate in a democratic society (Rozek et al., 2021).

In conclusion, by 2050, the governance landscape will be shaped by how effectively societies strike a balance between leveraging technology for empowerment and upholding democratic principles. The outcome of these choices could profoundly influence the nature of freedom and equity on a global scale, highlighting the urgent need for thoughtful approaches that consider both technological innovations and fundamental human values.

 

Possible Futures

 

As we approach 2050, three distinct scenarios emerge for the possible futures of governance, each shaping the relationship between technology, authority, and citizen engagement: Authoritarian Dominance, Digital Democracy, and Civic Hybridisation. Understanding these scenarios is crucial for assessing how technology can be leveraged to either empower or oppress populations.

Scenario 1: Authoritarian Dominance. In  scenario, governments leverage advanced technologies, such as AI-driven surveillance systems and predictive policing, to consolidate power.  trend could lead to a society where citizens willingly sacrifice their privacy for perceived security benefits. The implementation of these technologies enables states to maintain a form of stability; however, stability often comes at a cost to personal freedoms and rights. There is a significant risk that continuous monitoring and data collection foster a climate of fear, leading to silent dissatisfaction among the populace. As public happiness declines, discontent can grow beneath the surface, potentially destabilising the regime in the long term, despite short-term order being maintained. The phenomenon highlights a critical tension between security and autonomy, suggesting that while governments may effectively control populations through technology, the societal implications are often detrimental to the overall wellbeing of citizens.

Scenario 2: Digital Democracy Conversely, the Digital Democracy scenario presents a more optimistic view of technology as a catalyst for empowerment. In cases where digital platforms enable citizens to participate actively in the policymaking process, they promote transparency and accountability. By facilitating open communication and collaborative efforts, governments can foster an environment where public Trust flourishes. The use of digital tools as mechanisms for civic engagement signifies a paradigm shift wherein citizens feel a sense of ownership over governance outcomes. When well-implemented, a model could prioritise public happiness as a key metric for governance success, resulting in policies that better reflect the needs and desires of the population. Notably, increased Trust in governmental institutions correlates with the use of participatory mechanisms, suggesting that empowered citizens are more likely to view their governments in a positive light.

Scenario 3: Civic Hybridisation. The civic hybridisation model suggests a balance between centralised government authority and localised decision-making. By integrating digital tools to support community agency within a national framework, the scenario encourages diverse, inclusive, and resilient governance structures. Communities are empowered to address their unique challenges while still maintaining cohesion and alignment with national policies. The model recognises the importance of both direct citizen engagement and the need for governance to adapt to local contexts, thereby fostering a more democratic and participatory approach. As communities gain autonomy in decision-making processes, the resulting governance can better respond to local needs while fostering a sense of belonging and connection within the broader state framework.

Ultimately, the paths chosen as we approach 2050 will have lasting implications for global governance and the meaning of citizenship. The challenge for policymakers lies in navigating these various scenarios to harness technology for the public good while safeguarding individual freedoms. The choices made in the critical period could define societal relationships for generations, prompting a reevaluation of democracy, human values, and the role of technology in governance.

 

The Roadmap to Public Happiness

To build better governments, we must redefine what success means. Economic growth alone cannot measure progress; citizen happiness, dignity, and Trust must also lead. Transparency should be the default; every budget and decision must be open to scrutiny. Digital tools must empower people, not silence them. Governments must act as facilitators, not rulers, enabling citizens to participate actively in shaping their futures.

To build better governments, a comprehensive roadmap that redefines success beyond mere economic growth is imperative. Necessitates placing citizen happiness, dignity, and trust at the forefront of governance metrics. Such a shift requires a commitment to transparency, where governmental budgets and decisions are subjected to public scrutiny, ensuring accountability in the decision-making process. Digital tools must be leveraged not as instruments of control but as means to empower citizens, facilitating their active participation in shaping their futures.

The integration of citizen happiness as a key indicator of governmental success aligns with growing global trends towards understanding wellbeing as central to policy outcomes. According to Sollis et al., movements such as Australia's Wellbeing Framework aim to redirect policymaking towards enhancing individual and community wellbeing, advocating for metrics that resonate more with public values than traditional economic indicators like GDP. Sollis et al. (2025) emphasise the need for governments to create environments where citizens feel valued. Their voices matter, fundamentally altering the relationship between the state and the populace.

In context, transparency should not just be an aspiration but the default mode of governance. Increased transparency has been shown to bolster public Trust and engagement, which are critical for a functioning democracy. By ensuring that budgets and decision-making processes are transparent and accessible to the public, governments can foster spaces for open dialogue and meaningful participation. Wamsler discusses how building collaborative relationships between officials and citizens can transform governance, particularly in addressing complex challenges such as climate change (Wamsler, 2016). Collaboration fosters a sense of ownership among citizens, encouraging them to contribute to governance rather than passively receive decisions made by state authorities.

Furthermore, the role of digital tools in governance cannot be overstated. E-government initiatives, as discussed by Máchová and Lněnička, highlight the importance of utilising technology to enhance citizen engagement and streamline governmental processes (Máchová & Lněnička, 2016). Digital platforms can facilitate greater communication between governments and citizens, offering avenues for input and feedback that were previously unavailable. Empowerment is critically important, as it allows for a more responsive government and reinforces the social contract between the state and its citizens, leading to greater accountability and transparency (Thoa & Cuong, 2024).

Governments must also embrace a facilitative approach, acting as enablers rather than rulers. Involves shifting power dynamics to enable citizens to take an active role in decision-making, particularly at local levels where community knowledge and needs can be better addressed. Research indicates that decentralised governance structures incorporating community input can enhance resilience and adaptability in policy implementation (Mees et al., 2019; Klein et al., 2016). By recognising citizens as co-creators of governance, policies can be more effectively tailored to meet the diverse needs of the population.

The roadmap to public happiness requires a transformative shift in governance that prioritises wellbeing, embraces transparency, empowers citizens through technology, and adopts a facilitative role for governments. A holistic approach ensures that governance is not only about maintaining order but also about enhancing the quality of life for all citizens, ultimately leading to a more engaged, satisfied, and trusting populace.

 

 A Call to Leaders and Citizens

 

To pave the way for a brighter future in governance, a profound transformation is essential—one in which both leaders and citizens share a sense of responsibility. As articulated in the call to action for leaders, there is an urgent need to adopt participatory models that prioritise ethics-driven policies alongside measurable progress in areas such as Trust, rather than merely focusing on power or control.

Leaders' Responsibilities

Leaders are called to foster participatory governance models, which enable more inclusive decision-making processes. According to Nabatchi and Amsler, direct public engagement in local government settings greatly enhances transparency and fosters a sense of belonging among constituents (Nabatchi & Amsler, 2014). A participatory approach is crucial, as it allows citizens to voice their opinions and influence public policies that directly affect their lives. By prioritising citizen engagement, leaders can cultivate a more equitable and responsive governance structure that reflects the diverse needs and aspirations of the populace (Kim & Lee, 2012).

Moreover, leaders must establish a culture of transparency. The research by Grimmelikhuijsen and Meijer supports the notion that greater transparency enhances the perceived trustworthiness of government organisations (Grimmelikhuijsen & Meijer, 2012). Transparency can be operationalised through open-access policies regarding budgets and governmental decisions, thereby allowing citizens not only to scrutinise but also to participate effectively in the governance process. In light of declining Trust in governmental institutions, such transparency is essential for rebuilding the social contract between the state and its citizens.

Citizens' Engagement

For citizens, engaging in active civic participation is pivotal. By participating in governance, whether through public forums or digital platforms, citizens can hold their leaders accountable and influence decision-making processes (Aman & Jan, 2022). Such engagement enhances the legitimacy of governmental actions and cultivates a sense of ownership over policy outcomes. In an era increasingly dominated by technology, e-participation initiatives facilitate engagement by providing platforms for citizens to contribute their ideas and perspectives transparently (Ponte et al., 2016). As highlighted by Kim and Lee, overcoming barriers to accessing policy information is critical for effective citizen participation (Kim & Lee, 2012).

Furthermore, citizens should demand that technology serve humanity rather than control it. The rise of digital platforms presents unprecedented opportunities for connection and participation; however, they must be designed to empower users rather than manipulate them. As noted by Desouza and Bhagwatwar, leveraging information technologies for citizen engagement in governance can address complex urban challenges more effectively through collaborative decision-making processes (Desouza & Bhagwatwar, 2012). Citizens must remain vigilant and proactive in ensuring that these systems reflect democratic ideals and prioritise the public good.

A Shared Vision

Together, leaders and citizens can build governments grounded in Trust, compassion, and purpose.  endeavour prioritises people over power and emphasises collective wellbeing. A commitment to ethics-driven governance complements the principle of shared responsibility, a concept supported by evidence that underscores the importance of Trust in shaping effective public administration (Siebers et al., 2019). It is a shared vision that can catalyse the evolution of governance into a more inclusive, responsive, and ultimately happier society.

In conclusion, the future path of governance depends on mutual engagement between leaders and citizens. By embracing participatory models, championing transparency, and harnessing technology for empowerment, we can collectively reshape the governance landscape to reflect the ideals of Trust and shared responsibility. As we stand on the precipice of change, let us move forward together towards a future where governance truly serves the people.

 

"The future of governance will not be defined by how tightly authorities hold onto power but by how boldly they open space for their people. Through transparency, technology, and participation, we can shift from ruling by control to governing with purpose: prioritizing public happiness. The world is changing, and only the nations that put humanity above power will lead the next chapter of civilization."

 

 

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Thursday, August 14, 2025

How AI is Transforming Quantity Surveying

 


                    How AI is Transforming Quantity Surveying

                                                              By AM Tris Hardyanto


1        From Measurement to Machine Intelligence

 

The evolution of the Quantity Surveyor (QS) role has been significantly impacted by advancements in Artificial Intelligence (AI) and related digital technologies. Traditionally, quantity surveying involved meticulous tasks such as counting materials and calculating costs, often requiring substantial manual effort. However, the integration of AI into the construction industry has transformed  landscape, enabling QS professionals to migrate from labour-intensive data management to more strategic roles focused on financial advising and project management.

AI's capabilities in data analysis and machine learning enhance cost estimation processes by automating routine calculations and employing sophisticated algorithms. Techniques such as artificial neural networks are increasingly utilised for accurate cost forecasting and risk management, allowing QS teams to make faster and more informed decisions (Victor, 2023). For instance, learning from historical project data enables QS professionals to create reliable estimates for future budgets and resource allocation, fostering improved financial planning (Victor, 2023). As a result, AI contributes not just to cost estimation accuracy but also to greater efficiency and reduced risk of overruns (Victor, 2023).

In addition to AI, the adoption of Building Information Modelling (BIM) has further revolutionised QS practice. The emergence of 5D BIM, which integrates time and cost management into three-dimensional modelling, necessitates a blend of technical expertise and digital competence among QS professionals. AI tools play a crucial role in managing and interpreting BIM data, streamlining project workflows, and minimising risks associated with project delivery; however, specific citations to support these claims were not identified in the provided references.

Moreover, the strategic implications of AI extend beyond operational efficiency. They form a foundational component in reshaping the QS profession into a more analytical and advisory role. With AI-generated insights, Quantity Surveyors can navigate uncertainties and changing market dynamics more adeptly, underscoring technology's growing relevance in the profession's future. While studies support the importance of AI in various sectors, including financial management, no explicit references to quantity surveying were identified in the provided references.

Overall, the integration of AI and digital technologies is redefining quantity surveying and enhancing the traditional skillset, where the meticulous counting of every brick has now evolved into sophisticated financial advising driven by advanced data analytics.

2        Mega-Scale Projects and AI in Quantity Surveying


Artificial Intelligence (AI) is at the forefront of transforming the operational dynamics of mega-scale construction projects, particularly in the field of Quantity Surveying (QS). The incorporation of AI technologies is playing a significant role in enhancing efficiency, mitigating risks, and strengthening cost control mechanisms.

 

2.1       Real-Time Market-Driven Cost Planning

AI enhances cost planning processes by utilizing real-time data analytics, including market trends and supplier pricing information. By aggregating data from diverse sources, AI equips Quantity Surveyors with more accurate cost forecasts at earlier stages of design, thus facilitating the creation of robust budgets and minimizing the incidence of cost overruns. Access to current market insights enables QS professionals to adapt budgets responsively, thus enhancing financial planning efficiency (Regona et al., 2022).

2.2       Dynamic Risk Detection and Profit Visibility

AI's capabilities extend to tracking fluctuations in project costs, including unexpected price hikes and subcontractor issues. Through continuous data analysis, AI can provide early warnings that allow quantity surveyors to act swiftly, thereby safeguarding profit margins and enhancing overall project financial health.Proactive risk management is crucial in averting financial pitfalls and ensuring a clearer understanding of a project's fiscal standing (Regona et al., 2022).

2.3      Proactive Risk Modelling

The implementation of AI-driven simulations empowers QS professionals to model different project scenarios, preparing them for potential risks such as inflation and delays. By identifying risks at an early stage, QS can develop mitigation strategies proactively, which is instrumental in maintaining project timelines and budget adherence (Regona et al., 2022).

2.4      Automated Takeoffs from Plans

Automated quantity takeoffs using AI tools significantly reduce the time and errors associated with traditional manual methods. These tools allow Quantity Surveyors to generate quicker estimates, accelerating project timelines and enhancing accuracy in measurements. Such automation not only enhances efficiency but also frees up QS professionals to concentrate on strategic planning and oversight tasks (Regona et al., 2022).

2.5       Tender Document Analysis

With the advent of natural language processing capabilities in AI, the analysis of tender documents has become markedly more efficient. AI can swiftly process and extract relevant data, thereby enabling Quantity Surveyors to devote more time to strategic activities rather than administrative tasks.  shift enhances the overall productivity of QS professionals by allowing them to engage in high-value work (Regona et al., 2022).

2.6      Advanced Decision Support

AI systems are now increasingly integrating sophisticated decision-support models that offer actionable insights. These models help Quantity Surveyors identify cost drivers and potential risks, thereby enhancing decision-making processes while recognising the importance of human judgment in critical business decisions (Regona et al., 2022).

2.7      Sustainability and Net-Zero Goals

AI also plays a significant role in advancing sustainable construction practices. It assists in forecasting energy consumption, selecting eco-friendly materials, and conducting lifecycle cost analyses. Real-time monitoring capabilities during construction enable teams to adjust practices proactively, thereby minimising environmental impacts and aligning with net-zero objectives (Regona et al., 2022).

2.8      Innovation Beyond QS

Beyond the scope of traditional quantity surveying, AI technologies are being leveraged in various construction operations, including automated measurement, drone surveying, supply chain optimization, and computer vision applications for safety monitoring. The integration of these technologies contributes to a more streamlined construction process, enhancing safety and efficiency across the board (Regona et al., 2022).

In , AI is fundamentally reshaping the landscape of mega-scale construction projects by enabling quantity surveyors to adopt a more strategic and proactive role. The transition from manual data operations to sophisticated analytical capabilities presents a remarkable opportunity for the profession, ensuring that QS professionals not only meet emerging challenges but also seize opportunities for greater effectiveness and sustainability.

 

3         Automation Gains – Removing the Grind

Artificial Intelligence (AI) technologies are transforming the role of Quantity Surveyors (QS) by automating repetitive tasks, which enhances workflow efficiency and allows professionals to focus on more strategic responsibilities.Automation is facilitated by various software tools that streamline aspects of quantity surveying, enabling QS professionals to devote their time to critical thinking and value-driven activities.

3.1      Automated Quantity Takeoffs

One of the significant advancements in quantity surveying is the automation of quantity takeoffs. Tools like Autodesk Takeoff utilise AI to quickly identify and count items in digital drawings, reducing preparation time from hours to minutes.  capability allows Quantity Surveyors to produce immediate and accurate counts, significantly improving budget preparations and project timelines. The automation of quantity takeoffs accelerates data gathering processes and minimises human errors, which enhances the reliability of cost estimation processes, as reported in a systematic review of building information modelling applications in project cost management (Victor, 2023).

3.2      Photo Auto-Tagging

Photo auto-tagging technology is another innovative application of AI in Quantity Surveying. With computer vision capabilities, QS professionals can efficiently tag large sets of images taken from construction sites for quick retrieval and cost verification.  function simplifies quality control and helps maintain accurate records of project progression. As the construction industry continues to incorporate digital innovations, the impacts of technologies like photo tagging are becoming clear, offering significant time and resource savings (Victor, 2023).

3.3      Automated Document Drafting

The labour-intensive task of document drafting can be vastly improved through AI. Generative AI systems enable QS professionals to create standardised templates for various agreements and certificates, speeding up the drafting process. Instead of spending hours manually preparing documents, QS professionals can concentrate on negotiation and strategic planning, thus enhancing their contributions to project success. Studies indicate that automation fosters consistency and accuracy in documentation, which is vital for effective communication among project stakeholders (Victor, 2023).

3.4      Advanced Decision Support

AI technologies provide advanced decision support systems that analyse large data sets to yield actionable insights. For instance, AI models can identify cost drivers and predict potential risks through real-time analytics. Empowers Quantity Surveyors to make informed decisions aligned with project goals and budget constraints. Consequently, such support elevates the roles of QS professionals to more strategic levels, allowing them to play vital roles in the planning and management of construction projects (Victor, 2023).

3.5      Sustainability and Net-Zero Goals

AI's applications extend to influencing broader industry trends, including sustainability. By automating processes such as energy forecasting and lifecycle cost analysis, Quantity Surveyors can better align their practices with the growing emphasis on sustainable construction methods. AI tools can assist in assessing the environmental impact of materials and construction practices, enabling QS professionals to promote eco-friendly practices in their projects (Victor, 2023).

3.6      Broader Impact on Construction Operations

The impact of AI in quantity surveying indicates a broader transformation within the entire construction sector. Technologies like computer vision for safety monitoring and drone surveying not only enhance the role of quantity surveyors but also improve overall project management operations. An integrated approach to technology use within construction practices holds promise for addressing challenges related to efficiency, safety, and environmental impacts (Victor, 2023).

In , AI technologies are significantly altering how quantity surveyors operate by removing repetitive manual tasks and enhancing operational efficiencies. The effects of these innovations are profound, transforming QS professionals' roles from traditional estimators to strategic advisors who significantly contribute to project success and sustainability. As quantity surveying firms increasingly adopt these technologies, the profession will continue to evolve, maintaining its relevance in the increasingly digital landscape of construction.

 

4        Predictive Insights—Seeing Problems Before They Happen



Artificial Intelligence (AI) has significantly transformed project management within the field of Quantity Surveying (QS), enabling professionals to adopt a proactive management strategy rather than just reacting to issues as they arise. By utilising data analysis, AI equips QS professionals with predictive insights that are essential for managing risks, claims, and procurement processes in large-scale construction projects.

4.1       Risk Forecasting

AI-driven analyses of past project data, market trends, and real-time site conditions empower Quantity Surveyors to anticipate potential problems before they occur. Predictive analytics helps QS professionals identify risks ahead of time, facilitating timely strategic interventions that can prevent issues from escalating into crises. Research has shown that proactive risk identification can enhance project efficiency and execution by mitigating uncertainties before they evolve into significant challenges, ultimately improving overall project outcomes (Victar et al., 2022). The effectiveness of such predictive capabilities depends mainly on the quality of the data and the robustness of the analytical models utilised (Yaseen et al., 2024), highlighting the essential need for continuous improvement in data management practices.

4.2       Claims Management

Claims management has also seen substantial improvements through AI technologies. By leveraging AI to analyse claims against as-built records, Quantity Surveyors can proactively identify discrepancies, ensuring that potential disputes are managed before certification. Capability enhances transparency and reduces conflicts among stakeholders, thereby mitigating financial risks associated with claims disputes. Greater accuracy in claim assessments enables QS professionals to protect profit margins while upholding project integrity (Victar et al., 2022).

4.3      Procurement Intelligence

AI provides valuable procurement insights by evaluating vendor performance data.  Analysis helps Quantity Surveyors identify unreliable suppliers and optimise supply chain management. By using predictive insights regarding supplier reliability and historical performance, QS professionals can make well-informed decisions that prevent procurement disruptions and improve project execution. A data-driven approach to supplier selection not only streamlines procurement processes but also cultivates stronger supplier relationships, crucial for timely project delivery (Victar et al., 2022); Yaseen et al., 2024). Moreover, effective supplier engagement strategies can mitigate risks associated with procurement delays and contribute to overall project sustainability.

4.4      Enhancements to Workflow Efficiency

Integrating AI technologies into daily workflows enhances the capabilities of Quantity Surveyors by streamlining processes and reducing manual workloads. Automation in data entry, document management, and reporting allows professionals to concentrate on strategic activities and decision-making.  shift toward focusing on higher-level roles exemplifies how predictive insights from AI can elevate the Quantity Surveying profession (Yaseen et al., 2024). By alleviating repetitive tasks, AI not only improves accuracy but also enhances job satisfaction among QS professionals, who can engage more deeply in decision-making and innovative practices.

4.5      Continuous Monitoring and Adaptability

AI solutions facilitate continuous monitoring of project conditions and financial metrics, enabling real-time adjustments to plans as new information arises.Adaptability is critical in today's fast-paced construction environment, where swift responses to changing conditions can have significant consequences for project success. With AI tools constantly analysing project data, quantity surveyors can maintain oversight of project budgets and timelines, ensuring alignment with strategic objectives (Yaseen et al., 2024). The proactive adjustment of project components based on predictive insights fosters an agile and responsive culture within construction teams.

 

 

the transition from reactive to proactive management empowered by AI technologies has substantial implications for the role of quantity surveyors in large-scale projects. By leveraging predictive insights in key areas such as risk forecasting, claims management, and procurement intelligence, QS professionals can improve project efficiency, enhance accuracy, and foster better stakeholder engagement. The ongoing adoption of these technologies will promote a more dynamic and strategic role for quantity surveyors, ultimately contributing to the success of construction projects.

 

5. Generative AI for Documentation and Reporting


Generative AI is emerging as a transformative force in the realm of documentation and reporting within quantity surveying (QS). By streamlining essential but often tedious documentation tasks, generative AI enhances efficiency, reduces errors, and supports improved decision-making capabilities for quantity surveyors. The implementation of generative AI in QS can be categorised into three significant areas: contract summarisation, tender response drafting, and variation order justification.

5.1      Contract Summarization

Generative AI tools are adept at condensing extensive contracts into succinct summaries, facilitating a quicker review process by Quantity Surveyors and project stakeholders.  The capability allows professionals to skim through lengthy legal documents efficiently, focusing on critical terms and conditions without becoming bogged down in the details. The ability to distil complex information into digestible formats is crucial not only for speeding up the initial review process but also for enhancing overall comprehension among team members. The fast-paced nature of construction projects necessitates such efficiency, where time is often of the essence (Aljamaan et al., 2025; Beets et al., 2023).

5.2      Tender Response Drafting

In tender response drafting, generative AI can significantly reduce turnaround times by producing initial drafts for bids. These drafts provide a foundational framework that Quantity Surveyors can refine to ensure accuracy and compliance with specific project requirements. Function diminishes the burden of drafting from scratch, allowing QS professionals to focus on critical elements of the bidding process, such as strategic pricing and competitive positioning. By streamlining bid preparation, generative AI helps Quantity Surveyors allocate their time more effectively towards tasks that require in-depth analysis and negotiation (Aljamaan et al., 2025).

5.3      Variation Order Justification

Additionally, generative AI enhances the process of variation order justification by gathering relevant clauses and historical data to support or challenge claims.  automated collection of pertinent information allows Quantity Surveyors to construct compelling arguments for adjusting contract terms based on unforeseen circumstances or project changes. The capability to quickly access and analyse historical data not only fortifies the QS's position in negotiations but also minimises disputes arising from inconsistencies in documentation (Aljamaan et al., 2025; Nong & Ji, 2025). By fostering more transparent communication regarding variations, generative AI ultimately contributes to maintaining project integrity and reducing risks associated with contract modifications.

5.4      Overall Impact on Workflow

The integration of generative AI tools into quantity surveying practices leads to notable improvements in workflow efficiency. As routine documentation tasks are automated, quantity surveyors find themselves less burdened by administrative workload and more empowered to engage in high-level planning and strategy development.transition underscores the transformative potential of generative AI as it fosters a culture of innovation and strategic focus within the QS profession (Aljamaan et al., 2025; Dai et al., 2020). Furthermore, as generative AI processes become more sophisticated, the accuracy and reliability of documentation also improve, which is essential in an industry where precision is paramount.

 

Generative AI is revolutionizing documentation and reporting within quantity surveying by streamlining key processes such as contract summarization, tender response drafting, and variation justification.Efficiency not only mitigates the chances of error but also enhances the overall quality of decision-making. As the construction industry continues its digital transformation, the role of generative AI will undoubtedly become increasingly integral to the function and success of quantity surveyors, ensuring that they can meet the demands of complex mega-projects with agility and precision.

 

6        Intelligent Search and Knowledge Retrieval

 

Artificial Intelligence (AI) is enhancing the processes and functionalities of Quantity Surveyors (QS) in managing and utilizing past project data.capability allows QS teams to operate more efficiently, improving access to critical information while enabling better decision-making regarding construction project management.

6.1       Semantic Search

One of the advancements of AI in quantity surveying is the implementation of semantic search functionalities within Common Data Environments (CDE). Technology enables QS professionals to perform natural language queries, which yield quick and targeted search results. Semantic search empowers QS teams to locate specific information from a vast database of project documents and records without needing extensive technical expertise or detailed keyword knowledge. Functionality can dramatically reduce the time spent searching for relevant documents and facilitate a more streamlined workflow, allowing Quantity Surveyors to focus on strategic tasks.

6.2       Decision Support

AI provides instant access to market rates and historical data, which is crucial for negotiations and forecasting in the construction industry.  decision support aspect enables Quantity Surveyors to make informed choices when planning future projects or negotiating contracts, bringing both past insights and current market trends to the forefront. Databases enhanced by AI capabilities can quickly supply accurate information regarding pricing, availability, and supplier performance, ultimately facilitating a more data-driven approach to project management. Such immediacy in accessing data supports better negotiation techniques and enhances overall project efficiency.

6.3      Cross-Project Learning

Another vital area where AI significantly contributes is in cross-project learning, wherein lessons from past projects are utilised to inform current and future endeavours. AI systems can identify patterns and insights from historical data, helping Quantity Surveyors recognise recurring challenges and successfully implement strategies. Process minimises the risk of making redundant mistakes and enhances the efficiency of project execution by applying learned lessons in areas such as cost management, risk assessment, and time management. The continual learning facilitated by AI creates a feedback loop that continuously improves project management practices, ensuring that past learnings are effectively integrated into future decision-making processes.

6.4      Broader Implications

Beyond immediate operational benefits, AI's integration into intelligent search and knowledge retrieval processes signifies a broader transformation within the construction industry. The ability to access a wealth of data swiftly and derive actionable insights influences how projects are planned and executed. The enhanced efficiency in knowledge retrieval fosters a culture of innovation, encouraging Quantity Surveyors to embrace new technologies and methods in their practices. Furthermore, as the construction industry adopts increasingly advanced AI technologies, it positions itself to navigate future challenges effectively, maintaining competitiveness in a rapidly evolving landscape.

In , intelligent search and knowledge retrieval powered by AI profoundly impact the Quantity Surveying profession. By enabling semantic search, decision support, and cross-project learning, AI improves how QS teams find and utilise past project data while enhancing overall efficiency and decision-making capabilities. As the construction industry continues to integrate AI technologies, the role of quantity surveyors will evolve, allowing them to utilise their expertise more strategically and drive the success of projects in a complex and dynamic environment.

 

7        Real-World Impact—Efficiency, Accuracy, and Influence

 

Artificial Intelligence (AI) is becoming a significant component in enhancing the functions of Quantity Surveyors (QS), especially in terms of efficiency, accuracy, and strategic involvement in construction projects. The transformative impact of AI can be categorised into three primary areas, each significantly contributing to the overall effectiveness of QS professionals.

7.1      Faster Turnarounds

AI technology accelerates the generation of construction schedules, allowing QS teams to create these schedules in hours instead of days without sacrificing accuracy. The integration of AI tools enables rapid data analysis, resource allocation, and timeline forecasting. As a result, project managers and stakeholders can access updated schedules quickly, allowing for timely decisions and adjustments.Rapid response is vital in the construction sector, where delays can lead to substantial financial implications and project overruns (Diao, 2024). The efficiency gained through faster turnarounds enhances productivity, enabling teams to manage more projects simultaneously and ultimately improving profitability.

7.2      Higher Data Confidence

The application of AI technologies in quantity surveying increases confidence in the data used for project estimation and decision-making. By ensuring all data is verifiable and accessible, AI reduces the potential for disputes that often arise from ambiguities or inaccuracies in project documentation. Enhanced data integrity builds trust among stakeholders, fostering stronger relationships between QS professionals, contractors, clients, and suppliers (Diao, 2024; Wu et al., 2018).Trust significantly influences project outcomes, as stakeholders are more inclined to rely on robust data for critical decisions regarding investments and future collaborations.

Additionally, the shift towards higher data confidence allows Quantity Surveyors to provide more accurate cost forecasting, helping ensure projects remain within budget and minimise financial challenges as they progress. Furthermore, reliable data enhances negotiations with suppliers and subcontractors, further mitigating potential risks (Diao, 2024).

7.3      Strategic Involvement

AI not only automates various functions but also empowers Quantity Surveyors to become more strategically involved in the early stages of projects. With monotonous tasks automated, QS professionals can engage more effectively in design discussions and cost planning. Their insights can directly influence design decisions and value engineering approaches, thereby improving project efficiency and sustainability (Diao, 2024).

Involving QSs early in project development can lead to significant cost savings and optimisations, as they can provide crucial feedback on design feasibility and cost implications before construction begins.  proactive involvement positions Quantity Surveyors as essential team members who bridge technical knowledge with financial insights, thus reinforcing their role in strategic project planning (Diao, 2024).

 

In , the integration of AI technologies in Quantity Surveying leads to substantial advancements in efficiency, accuracy, and strategic influence. By enabling faster turnarounds, enhancing data confidence, and facilitating strategic involvement in project planning, AI improves the operational dynamics of QS professionals and strengthens their position within the construction industry. As the adoption of AI continues to progress, its impact on project success rates and stakeholder relationships will become increasingly apparent, marking a new era in construction management characterised by improved collaboration and innovation.

 

The QS in the AI Era


In the AI era, the role of the Quantity Surveyor (QS) is being dramatically transformed from a focus strictly on measurements to a broader emphasis on strategic planning and financial oversight.  evolution underscores the essential role of AI in modern quantity surveying practices, enabling QS professionals to enhance their contributions significantly.

Transformation in the Role of Quantity Surveyors

AI technologies simplify and accelerate repetitive tasks traditionally associated with QS, such as measurements and cost estimations. The increased efficiency allows these professionals to produce schedules and financial forecasts more quickly and accurately. For example, generative AI tools can streamline documentation processes, enabling faster contract summarization and tender drafting.shift in productivity enables QS teams to dedicate more time to strategic discussions regarding project scope and budget allocations.

The Importance of Predictive Insights

Predictive risk forecasting powered by AI is another critical advancement that informs quantity surveyors of potential issues before they escalate. By analyzing historical data and current market trends, QS professionals can anticipate challenges such as cost fluctuations or project delays.A proactive approach allows for timely interventions, thereby protecting profit margins and ensuring smoother project progress. The capacity to foresee risks enhances not only the quality of financial oversight but also reinforces stakeholder confidence.

Intelligent Knowledge Retrieval

Intelligent search capabilities facilitated by AI enable QS professionals to retrieve relevant past project data efficiently. Semantic search functionalities in Common Data Environments (CDE) allow quantity surveyors to perform natural language queries, drastically reducing the time spent searching for information vital to ongoing projects. The ability to access historical knowledge fosters cross-project learning.

The Role of Common Data Environments (CDE)

At the heart of maximizing AI's potential lies the significance of high-quality data management via a Common Data Environment (CDE). The effectiveness of AI applications in quantity surveying is intrinsically linked to the quality and accessibility of data. A well-structured CDE provides QS teams with a centralized platform for managing construction costs, ensuring that all project members have access to accurate and up-to-date information. Quality data empowers quantity surveyors to leverage AI optimally, ultimately leading to enhanced project outcomes.

 

The transformation of Quantity Surveying in the AI era signifies a shift towards strategic financial oversight and proactive management in construction projects. AI tools and technologies, including automation, predictive insights, and intelligent knowledge retrieval, are reshaping the role of QSs into strategic partners in project planning and execution. The successful integration of these technologies, particularly within a robust Common Data Environment, is crucial for maximising the benefits of AI in the construction industry. Quantity Surveyors must harness these advancements to thrive in their evolving roles, ensuring they can navigate the complexities of modern construction projects effectively.

 

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