The 2AM Wake-Up Call: Why Change Management is Dead and AI is the Answer

An in-depth conversation with Angelos Nicolaou, CEO of Sector, on the future of construction technology

There's a moment that haunts every technology leader in construction. It's 2AM, and you're lying awake thinking about the same persistent problem that has plagued the industry for decades. For Angelos Nicolaou, CEO of Sector, that moment crystallised into a simple but profound realisation: "I hate change management. I think everybody hates change management. And the thought that wakes me up at 2 a.m. is that technology should be doing the work for us. People don't have time to change. People don't have time for change management."

This isn't just another tech executive's midnight musings. It's a fundamental shift in how we think about technology adoption in an industry drowning in digital solutions. With over 10,000 apps in the construction tech space alone, and another 30,000 in PropTech, the construction industry faces an unprecedented paradox: we have more technological solutions than ever before, yet productivity gains remain elusive, and workers spend up to 80% of their day on what Nicolaou calls "grunt work."

In a recent episode of the Project Flux podcast, Nicolaou shared insights that challenge conventional wisdom about technology adoption, change management, and the future of work in construction. His company, Sector, offers a unique perspective on this challenge by providing free technology recommendations to help organisations navigate the overwhelming landscape of available solutions. But more importantly, Nicolaou's vision points toward a future where artificial intelligence doesn't just augment human work—it fundamentally transforms how we approach the relationship between people and technology.

The conversation reveals a construction industry at an inflection point. While executives worry about AI displacing workers, the reality is starkly different: "We're worried that AI will take our jobs. We can't hire people fast enough. We can't build fast enough because we can't hire people," Nicolaou observes. This contradiction highlights a deeper truth about the current state of construction technology—we're not lacking solutions; we're lacking effective adoption strategies that actually work for the people who need to use these tools daily.

The Overwhelming Reality of Construction Tech

The numbers alone tell a staggering story. When Nicolaou reveals that there are 10,000 applications in the construction technology space and another 30,000 in PropTech, the scale of choice becomes almost incomprehensible. "That's the stuff your clients want. Your clients want that. And then what you can use is your decision pool, let's say that you have to pick it. It's insane."

But the real impact becomes clear when you examine how this translates to daily work life. Sector's customers routinely operate with 400 to 450 different SaaS product subscriptions.

On an individual level, each user relies on 12 to 13 different applications every single day just to perform their job functions. The productivity implications are profound and largely hidden from traditional metrics.

"Think of the productivity loss of searching between all these apps," Nicolaou emphasises. This isn't merely about the time spent switching between platforms—it's about the cognitive load, the context switching, and the fundamental disruption to deep work that occurs when professionals must constantly navigate between disparate systems to accomplish basic tasks.

The situation becomes even more complex when you consider the typical workflow in construction project management. A document controller, for example, might spend their entire day downloading files from Autodesk, uploading them to Aconex, then downloading from Aconex to upload to ThinkProject, all based on whatever specific platform a particular client requires. "And then we have to, you know, employ people, just do that unfulfilling job, like you said, you know, not feeling smart doing that. Cause it is just grunt work. So much."

This reality challenges the fundamental assumption that more technology equals better outcomes. Instead, what we're witnessing is a form of digital overwhelm that paradoxically reduces productivity while increasing complexity. The construction industry has become a victim of its own digital transformation success, creating an ecosystem so rich with solutions that navigation itself has become the primary challenge.

The human cost of this technological abundance cannot be understated. Workers report feeling frustrated, overwhelmed, and disconnected from meaningful work. When 70 to 80% of a professional's day is consumed by what amounts to digital housekeeping—moving information from one system to another, searching for files, or trying to reconcile data across platforms—there's little time left for the creative, strategic, and relationship-building activities that actually drive project success.

This fragmentation also creates significant risks for project delivery. When critical information is scattered across dozens of platforms, the likelihood of miscommunication, missed deadlines, and costly errors increases exponentially. The very tools designed to improve coordination and efficiency can become barriers to effective collaboration when they're not properly integrated or when teams lack the time and training to use them effectively.

Why Traditional Change Management is Fundamentally Broken

The traditional approach to technology adoption in construction follows a predictable pattern that Nicolaou identifies as fundamentally flawed. "We saw a lot of decisions in the past being made from companies where they, you know, the C suite would sit together and they see a software and the software looked amazing and that they made that decision and they bought it and then everybody, you have to use the software. It doesn't really work that it's proven not to work well that way."

This top-down approach to technology procurement creates an immediate disconnect between the decision-makers who select tools and the end-users who must integrate them into their daily workflows. The result is predictable: low adoption rates, user resistance, and ultimately, failed implementations that waste both financial resources and organisational goodwill.

The fundamental problem lies in the assumption that people can and should adapt to technology, rather than technology adapting to people. Traditional change management programmes are built on the premise that with enough training, communication, and incentives, workers will eventually embrace new systems. But this approach ignores a basic human truth: people are naturally resistant to change, especially when that change adds complexity to their already demanding work lives.

"People don't have time to change," Nicolaou states bluntly. This isn't about laziness or resistance to innovation—it's about the practical reality of working in an industry where project deadlines are tight, margins are thin, and the consequences of mistakes can be severe. When workers are already stretched to capacity, asking them to learn new systems, adapt to new workflows, and maintain productivity during a transition period is often unrealistic.

The traditional change management model also fails to account for the cumulative effect of constant technological change. In an environment where new tools are introduced regularly, workers experience "change fatigue"—a psychological state where the prospect of yet another new system triggers automatic resistance, regardless of the potential benefits. This creates a vicious cycle where each failed implementation makes subsequent changes even more difficult to achieve.

Moreover, the conventional approach often treats technology adoption as a discrete event rather than an ongoing process. Organisations invest heavily in initial training and rollout activities, but fail to provide the sustained support and iteration necessary for true adoption. When users encounter problems or discover that the new system doesn't quite fit their specific needs, they often revert to familiar tools and workarounds, undermining the entire implementation.

The cost of this broken approach extends far beyond wasted software licences. Failed technology implementations damage trust between management and workers, create cynicism about future innovations, and can actually reduce overall productivity as teams struggle with partially implemented systems. In some cases, organisations end up maintaining parallel systems—the official new platform and the unofficial tools that people actually use to get work done.

Nicolaou's insight points toward a different paradigm entirely: "I honestly think it's a matter of getting the technology to work for the end user instead of the user having to work for the technology." This represents a fundamental shift from adaptation-based change management to technology that seamlessly integrates into existing workflows and mental models.

AI as the First True "Next Big Thing" Since the Internet

In an industry that has seen countless technologies promised as revolutionary breakthroughs, Nicolaou's assessment of artificial intelligence carries particular weight: "I think AI is since the dawn of the internet, I think it's the first technology that is actually the next big thing. And I'm seeing it not just, you know, theoretically, it's not just people saying it's the next big thing. It's the speed of adoption of AI that we're seeing, right?"

The evidence for this claim lies not in marketing promises or venture capital investments, but in user behaviour and adoption patterns that represent a fundamental shift in how people interact with technology. The statistics Nicolaou cites are remarkable: Facebook took 12 months to reach one million users, Instagram achieved the same milestone in one month, but ChatGPT accomplished it in just five days.

This acceleration in adoption speed reflects something deeper than mere novelty or hype. "It's intuitive, people get it, it's very helpful. And I think that's the key of a really useful technology that can increase our productivity," Nicolaou explains. Unlike previous waves of construction technology that required extensive training and workflow changes, AI tools often feel immediately familiar and useful to users.

The key difference lies in AI's ability to meet people where they are, rather than requiring them to adapt to new paradigms. When someone asks ChatGPT a question in natural language and receives a helpful response, there's no learning curve, no manual to read, no training programme to complete. The interaction model is fundamentally human—conversation—rather than the abstract interfaces and complex feature sets that characterise most enterprise software.

This intuitive accessibility has profound implications for construction, an industry where technology adoption has historically been slow and uneven. "What we're seeing with most AI tools out there today is that it helps us get our jobs done, you know, faster, easier. I would just, you if you told me to choose one word I'd say just easier," Nicolaou observes.

The "easier" factor cannot be overstated. In an industry where workers are already managing complex projects with tight deadlines and multiple stakeholders, any technology that adds friction or complexity faces an uphill battle for adoption. AI's promise lies in its ability to reduce friction rather than add it—to make existing tasks simpler rather than introducing new ones.

But perhaps most importantly, AI represents the first technology in decades that delivers on the long-standing promise of productivity improvement. "What I like about AI and agentic AI in particular is that I feel that for the first time we're seeing those leaps in productivity that we were promised for the last 20, 30 years. We're seeing them for the first time now," Nicolaou states.

This productivity impact is qualitatively different from previous technological advances. While earlier innovations often required organisations to restructure processes or retrain workers to realise benefits, AI can often provide immediate value within existing workflows. A project manager can use AI to quickly summarise lengthy documents, generate initial drafts of reports, or analyse data patterns without changing their fundamental approach to the work.

The implications extend beyond individual productivity gains. When technology becomes genuinely easier to use and immediately beneficial, it creates positive feedback loops that accelerate adoption across organisations. Success stories spread organically, resistance decreases, and the traditional barriers to technology implementation begin to dissolve.

This shift also represents a maturation of the technology industry's understanding of user needs. Rather than building increasingly complex systems that showcase technical capabilities, AI development has focused on solving real problems in ways that feel natural and effortless to users. The result is technology that enhances human capability rather than replacing human judgment—a crucial distinction in an industry built on relationships, experience, and contextual knowledge.

The Rise of Agentic AI: When Technology Finally Does the Work

While conversational AI tools like ChatGPT have captured public attention, Nicolaou identifies agentic AI as the truly transformative development for construction professionals. His definition is elegantly simple: "I would define an agent as a, you know, when AI does the work for you. It's something that I used to do, you know, it's an action, right?"

To illustrate this concept, Nicolaou uses a relatable analogy: "I used to, you know, open my email, read through my calendar, and then sort of schedule my day the way I want to schedule it. If now I have an agent doing that, then that's what I consider to be agentic AI." The distinction is crucial—this isn't about AI providing information or suggestions, but about AI actually performing tasks that previously required human intervention.

The implications for construction workflows are profound. Consider the mundane but time-consuming tasks that consume so much of a construction professional's day: downloading files from Autodesk and uploading them to Aconex, then downloading from Aconex to upload to ThinkProject, all based on specific client requirements. These repetitive, rule-based activities are perfect candidates for agentic AI automation.

"Think of it as a robot. It's doing something that you used to do," Nicolaou explains, using another accessible metaphor. "If I don't know, you were used to, I don't know, pouring, pouring milk in your coffee, you just press a button. It's like, all right, as soon as my coffee's done, open the fridge and pour the milk in there. That's it. That's how I think of an agent."

This coffee machine analogy reveals something important about the nature of agentic AI—it's not about replacing human intelligence or creativity, but about automating the routine, predictable tasks that consume disproportionate amounts of time and mental energy. Just as an automatic coffee machine doesn't replace the human desire for coffee but makes the process of obtaining it effortless, agentic AI doesn't replace human expertise but removes the friction from accessing and applying that expertise.

The construction industry is particularly rich with opportunities for this type of automation. Document management, compliance checking, progress reporting, resource scheduling, and quality control inspections all involve significant amounts of routine work that follows predictable patterns. When these tasks are automated, professionals can focus on the aspects of their work that truly require human judgment, creativity, and relationship-building skills.

The productivity impact of this shift cannot be overstated. If 70 to 80% of a construction professional's day is currently spent on routine tasks, agentic AI has the potential to fundamentally restructure how work gets done. "And that's what really captures the imagination. It's when you are used to doing one thing, something especially that you hated to do, and all of a sudden the solution is just there, and it's just there in seconds too," Nicolaou observes.

The speed factor is particularly important. Traditional automation solutions often required extensive setup, configuration, and maintenance. Agentic AI promises to deliver automation that is both immediate and adaptive—systems that can understand context, handle exceptions, and improve their performance over time without requiring constant human oversight.

This represents a fundamental shift from the traditional relationship between humans and technology in construction. Instead of workers adapting to rigid software systems, agentic AI adapts to human workflows and preferences. The technology becomes invisible, working in the background to handle routine tasks while humans focus on the complex, creative, and interpersonal aspects of construction projects.

The psychological impact of this shift may be as important as the productivity gains. When professionals are freed from the frustration of repetitive, unfulfilling tasks, they can rediscover the aspects of their work that originally drew them to the construction industry—problem-solving, building relationships, creating something tangible and lasting. This could help address some of the industry's ongoing challenges with worker satisfaction and retention.

The Great Role Evolution: From Document Controllers to Tech Superstars

One of the most compelling examples Nicolaou shares involves the transformation of document controllers—traditionally one of the most routine-heavy roles in construction project management. "A document controller before AI agents would have to do this manual task that we just said, download from one, upload on the other, make sure it's all checked. I'm seeing document controllers today sort of rise the ranks to become these superstar construction tech experts."

This transformation illustrates a broader principle about how AI changes the nature of work rather than simply eliminating jobs. Instead of replacing document controllers, AI has elevated their role by automating the mundane aspects of their work and freeing them to focus on higher-value activities that require human insight and expertise.

"These are the ones who truly understand the software and are the ones that are leading the agents that, my gosh, can I do this thing? And can I do that thing? And can I do the other thing?" Nicolaou explains. The document controllers who once spent their days manually moving files between systems have become the strategic advisors who understand how different technologies can be orchestrated to solve complex workflow challenges.

This evolution has had profound implications for organisational dynamics. "These are the people who used to be not even be involved in the conversations that we had with our clients two, three years ago, who now are part of every single meeting making decisions on what solutions to use today by what solutions are the most friendly for the people."

The transformation reveals an important truth about expertise in the age of AI. Technical knowledge about software systems, understanding of workflow optimisation, and the ability to bridge between human needs and technological capabilities have become increasingly valuable skills. The document controllers who developed deep familiarity with various platforms through their daily work are now uniquely positioned to guide AI implementation and optimisation.

This pattern extends beyond document controllers to other roles throughout the construction industry. Project coordinators who once spent hours manually updating schedules and tracking progress are becoming strategic advisors on project optimisation. Quality control inspectors who previously focused on documentation are now able to spend more time on actual site analysis and problem-solving. Cost estimators can move beyond data entry to focus on market analysis and risk assessment.

The key insight is that AI doesn't eliminate the need for human expertise—it amplifies it. When routine tasks are automated, the value of human judgment, creativity, and relationship-building skills actually increases. "I think we have a lot more talents than we give ourselves credit for, a lot more creativity that is lost in operational work that should really just be automated," Nicolaou observes.

This perspective directly challenges the common fear that AI will lead to widespread job displacement in construction. Instead, Nicolaou points to a fundamental contradiction in these concerns: "We're worried that AI will take our jobs. We can't hire people fast enough. We can't build fast enough because we can't hire people."

The construction industry faces a significant labour shortage, particularly in skilled positions. Rather than eliminating jobs, AI has the potential to make existing roles more attractive and fulfilling by removing the frustrating, repetitive aspects that often drive people away from the industry. When work becomes more engaging and meaningful, it can help address recruitment and retention challenges.

The evolution also suggests a democratisation of technical expertise within construction organisations. Previously, technology decisions were often made by IT departments or senior management with limited understanding of day-to-day operational needs. Now, the people who actually use these systems daily are becoming the experts who guide technology strategy.

This shift requires organisations to recognise and nurture the evolving expertise of their workforce. The document controller who has become a technology expert may need new job titles, compensation structures, and career development opportunities that reflect their expanded role. Companies that fail to recognise and reward this evolution risk losing their most knowledgeable technology advocates to competitors who better understand the changing nature of expertise.

The transformation also highlights the importance of continuous learning and adaptation. The professionals who have successfully evolved their roles are those who embraced new technologies, experimented with different approaches, and developed a deep understanding of how various systems can work together. This suggests that curiosity and adaptability may be more important than traditional technical credentials in the AI-enabled construction industry.

Innovation Beyond the Buzzword: Why Adoption is Everything

In an industry where every company claims to be innovative, Nicolaou cuts through the marketing rhetoric with a stark observation: "Innovation is not a tick in the box anymore. I think it used to be, but it's really not anymore because there's so, so many solutions out there."

The proliferation of technology solutions has fundamentally changed the competitive landscape. When every construction company has access to similar tools—project management platforms, reality capture technology, AI-powered analytics—simply having these technologies no longer provides a meaningful advantage. The differentiator has shifted from acquisition to implementation.

"Most companies use some program or other that is give or take the same, you know, like Android versus iPhone kind of thing," Nicolaou explains. The real question becomes not what technology you have, but how effectively you use it. This shift has profound implications for how construction companies approach technology strategy and competitive positioning.

The evidence for this new reality is visible in client interactions. "Tech vendors, tech companies have found ways to get to the owners as well. So now the owners are aware. So you know, if you're going in and saying, Hey, I deployed, you know, copilot is not something like, Oh my gosh, where's this guy talking about? It's like, they know they probably use it too. And they'll start judging you. How are you using Co-pilot? Are you using him for this? And then the minute they start breaking down, it's, you you lost it."

This informed client base means that construction companies can no longer rely on technology name-dropping to win projects. Clients want to understand specific outcomes, measurable benefits, and concrete examples of how technology has improved project delivery. The conversation has evolved from "what tools do you use?" to "what results do you achieve?"

Nicolaou illustrates this with a practical example: "If you're saying, you know, I use open space and another consultant says, I use open space, what truly differentiates you is how you use open space. I use OpenSpace and I produce 30% more quality control inspections per month. I use OpenSpace and I reduce my travel by 50%. And by the way, here are 10 projects where I did it."

This level of specificity requires a fundamental shift in how organisations think about technology implementation. It's not enough to deploy a tool and hope for the best—companies need to develop systematic approaches to measuring outcomes, optimising workflows, and documenting results. The most successful organisations are those that treat technology adoption as an ongoing process of experimentation, measurement, and refinement.

The adoption challenge is particularly acute with AI tools like Microsoft Copilot, which Nicolaou uses as a case study. "You could have one company, and I know this is true, who rolled out copilot, spent an awful lot of money on it and didn't do any kind of training or any kind of kind of onboarding with it at all. Adoption 1%. Another company who rolled out in small waves, got the champions on board, really kind of built it into the psyche of the company. 80% adoption."

The contrast between 1% and 80% adoption rates represents the difference between wasted investment and transformative change. The companies achieving high adoption rates understand that technology implementation is fundamentally a human challenge, not a technical one. They invest in change management, identify and empower champions, and create cultural conditions that support experimentation and learning.

This focus on adoption also requires organisations to develop new metrics and measurement systems. Traditional project metrics—cost, schedule, quality—remain important, but they need to be supplemented with technology-specific indicators like user engagement, process efficiency gains, and outcome improvements. Companies need to be able to demonstrate not just that they use certain tools, but that those tools are delivering measurable value.

The shift toward adoption-focused innovation also changes how construction companies should approach vendor relationships. Rather than simply purchasing software licences, successful organisations are seeking partners who can provide ongoing support, training, and optimisation services. The most valuable vendors are those who understand that their success depends on their clients' success in achieving meaningful adoption.

This evolution has implications for talent management as well. The professionals who can drive successful technology adoption—the former document controllers who have become tech experts, the project managers who can optimise AI workflows, the field supervisors who can integrate new tools into daily operations—are becoming increasingly valuable.

Organisations need to recognise, develop, and retain these adoption champions.

The message for construction leaders is clear: in a world where everyone has access to similar technologies, competitive advantage comes from execution, not acquisition. The companies that will thrive are those that can consistently achieve high adoption rates, measure meaningful outcomes, and continuously optimise their technology implementations to deliver superior results for their clients.

The Future of SaaS and Technology Procurement

The emergence of "vibe coding" tools like Lovable and Replit, which allow users to create applications without traditional programming skills, has sparked debate about whether Software as a Service (SaaS) is becoming obsolete. When asked about this trend, Nicolaou offers a nuanced perspective: "I do think SaaS is changing. I wouldn't call it dead quite yet. But I do think SaaS is changing."

The evolution he describes is driven by market saturation and user fatigue. With customers managing 400 to 450 different SaaS subscriptions and individual users juggling 12 to 13 applications daily, the current model is clearly unsustainable. "So there is certainly some saturation happening there. Do I think SAS is dead? No, I don't think SAS is dead. I think SAS is here to stay for a long time."

Instead of disappearing, SaaS is evolving toward greater specialisation and vertical focus. "What I think we will start seeing, is you know, SAS is starting to take verticals very, seriously. You know, I think that we might have, you today we have project management solutions, you know, for the entire world. Tomorrow we might have, because it's easier to launch it, you know, a project management solution for London, for Manchester, you know, for San Francisco, for New York."

This trend toward hyper-localisation and industry-specific solutions reflects a broader shift in how technology companies approach market opportunities. Rather than building one-size-fits-all platforms, developers are increasingly creating targeted solutions that address specific regional requirements, regulatory environments, or industry practices.

The implications for construction companies are significant. Instead of adapting their processes to fit generic software platforms, organisations may soon have access to tools designed specifically for their geographic market, project types, and regulatory environment. A construction company operating in London might use different project management software than one in Manchester, not because of preference, but because each tool is optimised for local planning requirements, building codes, and industry practices.

This evolution raises important questions about technology strategy and vendor management. "The question is who is going to be the one who's going to launch these solutions. Will it be [existing companies] or will it be, you know, Procore or Autodesk?" Nicolaou wonders. The answer will likely determine whether the construction industry sees increased competition and innovation or further consolidation around established platforms.

The rise of vibe coding tools adds another dimension to this evolution. While Nicolaou sees their impact as "small," he acknowledges their potential for addressing very specific, narrow use cases. "Sometimes people have got no choice but to use a sledgehammer to crack a nut with, they'll have to, they might want a very, very small part of a SAS software and they have to buy the whole suite to be able to do something quite small."

This observation highlights a persistent frustration in enterprise software procurement—the need to purchase comprehensive platforms when only specific functionality is required.

Vibe coding tools could enable construction companies to create custom solutions for unique workflow requirements without the overhead of full enterprise platforms.

The trend also reflects a broader democratisation of software development. When project managers, site supervisors, or document controllers can create simple applications to solve specific problems, it reduces dependence on IT departments and external vendors for routine automation tasks. This could lead to more responsive, user-driven technology solutions that better fit actual work patterns.

However, this democratisation also creates new challenges around data integration, security, and maintenance. While it may be easy to create a simple application to solve an immediate problem, ensuring that it integrates properly with existing systems, meets security requirements, and remains functional over time requires ongoing technical expertise.

The future likely involves a hybrid approach where established SaaS platforms provide core functionality and integration capabilities, while custom applications and specialised tools address specific needs. This ecosystem approach could offer the best of both worlds—the reliability and integration of enterprise platforms combined with the flexibility and specificity of custom solutions.

For construction companies, this evolution suggests the need for more sophisticated technology strategies that balance standardisation with customisation. Organisations will need to develop capabilities for evaluating and integrating diverse technology solutions while maintaining overall system coherence and data integrity.

The key insight from Nicolaou's perspective is that regardless of how the technology landscape evolves, the fundamental challenge remains the same: ensuring that tools actually improve productivity and user experience rather than adding complexity and friction to daily work.

The Undervalued Innovation Teams: Bridging Strategy and Execution

Perhaps no group in construction organisations faces a more challenging paradox than innovation teams. As Nicolaou observes, "I think innovation teams are both undervalued in the business and overwhelmed at the same time. They are super busy and they're not valued nearly enough for the amount of value they generate for a business."

This contradiction reflects a fundamental misunderstanding of the innovation team's role in modern construction organisations. While senior leadership often views these teams as cost centres focused on experimental technologies, their actual function has evolved into something far more strategic and operationally critical.

"They're the key differentiator. They help drive adoption of these tools. They help drive ROI. They are sometimes the only ones who truly know what's going on in terms of tech, all the tools that we have, all the solutions that we have," Nicolaou explains. In an environment where organisations are managing hundreds of software subscriptions and constantly evaluating new solutions, innovation teams serve as the institutional memory and strategic compass for technology decisions.

The challenge becomes even more complex in large, geographically distributed organisations. "If you have a team in Peru testing a software that you could be benefiting from here in the UK or in India, your innovation team really should know about that and start to include that in their bids and their proposals and that should be communicated with the project manager."

This global coordination challenge highlights one of the most critical but underappreciated functions of innovation teams: knowledge management and organisational learning. Without effective systems for capturing, sharing, and applying lessons learned from technology experiments across different regions and projects, organisations repeatedly reinvent the wheel and miss opportunities for competitive advantage.

The disconnect between innovation teams and operational execution creates another layer of complexity. Nicolaou identifies a persistent problem: "One of the key problems that we need to solve is the complete disconnection between the tendering teams and the project management teams. They'll put something in there, the project manager doesn't even know about it, was never consulted, the project starts three months in, hey, what happened to that software we promised?"

This disconnect undermines both client relationships and internal efficiency. When tendering teams make technology commitments without involving the project managers who will be responsible for implementation, it creates unrealistic expectations and sets projects up for failure. The innovation team often finds itself caught in the middle, trying to bridge between strategic commitments and operational realities.

The solution requires a fundamental restructuring of how innovation teams operate within construction organisations. Rather than functioning as isolated research and development units, they need to be integrated into both the business development process and ongoing project delivery. This integration requires new tools, processes, and organisational structures that support real-time communication and knowledge sharing.

"I think innovation teams need tools. Companies like sector need to start now. That's why I'm proud to say we have started building tool solutions for them that help them do their job a lot easier, which is to connect adults to make sure they're always up to speed," Nicolaou explains. The reference to "connecting adults" is particularly telling—it suggests that the primary challenge isn't technical but organisational, involving communication and coordination between different functional groups.

The evolution toward AI and agentic systems creates both opportunities and challenges for innovation teams. On one hand, AI tools can help automate some of the routine research and evaluation tasks that consume significant time. On the other hand, the rapid pace of AI development means that innovation teams must constantly update their knowledge and assessment frameworks to keep pace with new capabilities.

The most successful innovation teams are those that have evolved beyond technology evaluation to become strategic advisors on digital transformation. They understand not just what technologies are available, but how they can be integrated into existing workflows, what training and support will be required for adoption, and how success should be measured and communicated.

This evolution requires innovation teams to develop new skills and capabilities. Technical knowledge remains important, but it must be supplemented with change management expertise, business analysis skills, and the ability to translate between technical possibilities and business requirements. The most valuable innovation team members are those who can speak both languages—understanding the technical capabilities of emerging tools while also grasping the practical constraints and requirements of project delivery.

The organisational implications are significant. Companies that continue to treat innovation teams as peripheral functions focused on experimental technologies will find themselves at a competitive disadvantage. Those that recognise innovation teams as strategic assets and invest in their integration with core business processes will be better positioned to achieve the adoption rates and outcome improvements that differentiate truly innovative organisations from those that merely purchase innovative tools.

The Path Forward: From Fearing Change to Embracing Automation

The conversation with Nicolaou reveals a construction industry at a critical juncture. The traditional approaches to technology adoption—top-down procurement decisions, extensive change management programmes, and adaptation-focused training—are proving inadequate for the scale and pace of current technological change. The path forward requires a fundamental shift in mindset, from viewing technology as something people must adapt to, toward creating technology that adapts to people.

The key insight is that successful technology adoption in construction isn't primarily a technical challenge—it's a human one. "The story of humans is a story of evolution. I think we have a lot more talents than we give ourselves credit for, a lot more creativity that is lost in operational work that should really just be automated," Nicolaou reflects.

This perspective reframes the entire discussion around AI and automation in construction. Rather than viewing these technologies as threats to employment, they represent opportunities to unlock human potential that has been constrained by routine, repetitive tasks. When 70 to 80% of a professional's day is consumed by "grunt work," there's enormous untapped capacity for creativity, problem-solving, and relationship-building.

The practical implications of this shift are significant. Construction companies need to move beyond the traditional metrics of technology success—deployment rates, training completion, and feature utilisation—toward outcome-based measures that focus on productivity gains, user satisfaction, and business results. As Nicolaou emphasises, "The Edge is adoption, 100%."

This adoption-focused approach requires organisations to develop new capabilities in change management, user experience design, and continuous improvement. The most successful implementations will be those that prioritise user needs from the beginning, involve end-users in design and testing processes, and create feedback loops that enable ongoing optimisation.

The financial approach to technology investment also needs to evolve. Rather than promising unrealistic returns on investment, Nicolaou advocates for a more pragmatic approach: "Let's first focus on recovering the cost that we paid for the tech. First and foremost, let's realistically look at the total cost of ownership of this technology. Let's look at what the licenses cost you. Let's look at what it costs you to operate and maintain this block. Let's make sure that at the very least, you're making that money back."

This conservative approach to ROI calculations creates a foundation for sustainable technology adoption. When organisations can demonstrate that their technology investments are at least paying for themselves, it builds confidence and credibility for future innovations. The spectacular returns can come later, but the foundation must be solid cost recovery and measurable productivity improvements.

The role of leadership in this transformation cannot be understated. The most successful technology adoptions occur when senior leaders understand that their role isn't to mandate change, but to create conditions where beneficial change can occur naturally. This requires investment in training, support systems, and organisational culture that rewards experimentation and learning.

Perhaps most importantly, the conversation highlights the need for construction professionals to maintain their humanity while embracing technological change. Nicolaou's recent reading of "The Inner Game of Tennis" led him to a crucial realisation about the importance of presence and focus in an increasingly technology-mediated world.

"I think this is something because we're so overwhelmed with technology and I'm seeing it as someone who's the active promoter, the active evangelist of technology. I see it as my life's purpose. It really truly surprised me to read that we really should be focusing on staying present, you know, in the here, in the now, understanding, you know, what's going on around us, being conscious about the world around us."

This insight provides a crucial counterbalance to the enthusiasm for technological solutions. While AI and automation can eliminate routine tasks and improve productivity, they cannot replace the human elements that make construction projects successful—creativity, judgment, empathy, and the ability to build relationships and solve complex problems in dynamic environments.

The future of construction technology lies not in choosing between human expertise and artificial intelligence, but in creating synergistic relationships where each amplifies the capabilities of the other. The most successful construction professionals will be those who can leverage AI to handle routine tasks while focusing their human capabilities on the aspects of work that require creativity, judgment, and interpersonal skills.

Key Statistics: The Scale of the Challenge

The numbers that emerged from this conversation paint a stark picture of the current state of construction technology:

•10,000 applications available in the construction technology space

•30,000 additional applications in the broader PropTech ecosystem

•400-450 different SaaS subscriptions managed by typical Sector customers

•12-13 applications used daily by individual construction professionals

•70-80% of a typical workday spent on routine "grunt work"

•5 days for ChatGPT to reach one million users (compared to 12 months for Facebook)

•1% vs 80% adoption rates for Microsoft Copilot, depending on implementation approach

These statistics underscore both the magnitude of the current challenge and the potential for transformation. When the majority of professional time is consumed by routine tasks, and when workers must navigate dozens of applications daily, there's enormous opportunity for AI-driven automation to create meaningful productivity improvements.

Final Thoughts: The Human Element in an AI-Driven Future

As construction companies navigate this technological transformation, Nicolaou's insights provide a roadmap that balances technological optimism with practical realism. The future belongs to organisations that can achieve high adoption rates for beneficial technologies while preserving the human elements that make construction projects successful.

The conversation ultimately returns to a fundamental truth about technology in construction: the best solutions are those that make people's work easier, more fulfilling, and more effective. When technology serves human needs rather than demanding human adaptation, adoption becomes natural, productivity improvements become sustainable, and the promise of digital transformation finally becomes reality.

The 2AM wake-up call that haunts technology leaders isn't really about change management or software deployment—it's about creating a future where technology genuinely serves human potential rather than constraining it. In Nicolaou's vision, that future is not only possible but already beginning to emerge in construction organisations that prioritise adoption over acquisition, outcomes over features, and human needs over technological capabilities.

Angelos Nicolaou is the CEO of Sector, a company that provides free technology recommendations to help construction organisations navigate the complex landscape of available solutions. You can connect with him on LinkedIn and learn more about Sector at https://sektor.build/

This article is based on Angelos Nicolaou's appearance on the Project Flux podcast, hosted by James Garner and Yoshi. Project Flux explores the intersection of technology and construction, featuring conversations with industry leaders about the future of built environment.