The construction industry generates colossal amounts of data, with much of it unused or locked in spreadsheets. AI is now changing this, enabling teams to accelerate decision-making, enhance margins, and improve project outcomes. According to new research from Dodge Construction Network (Dodge) and CMiC, the true transformative impact of AI is highlighted by contractors, with 87% believing AI will \u201cmeaningfully transform their business,\u201d despite current low adoption rates.
\nThe latest research, entitled, \u2018AI for Contractors,\u2019 discovered automated proposal generation and progress tracking from site photos both reached a 92% effectiveness rating. Meanwhile, contract risk review achieved 85% effectiveness when compared to previous, more traditional methods.
\nThe report highlights how AI is allowing project managers to focus on strategic decisions rather than time-consuming administrative tasks. Finance teams are also benefiting from AI technology, shifting from historical reporting to predictive insights, while operations leaders are able to apply data-driven intelligence for improved project delivery. Rather than AI fully replacing human expertise, the report found it actually enhances human input.
\n\u201cFor decades, construction firms have lacked the tools to transform the data they\u2019ve collected into action. AI-enabled solutions are changing that,\u201d says Gord Rawlins, president and CEO of CMiC. \u201cThis research highlights the high-impact results contractors are achieving today.\u201d
\nAI changing contractor roles
\nSurveyed contractors see AI as a catalyst in reshaping everyday aspects of their operations, enabling predictive insights rather than reacting to problems once they have occurred. This introduces wider benefits, like tighter cost controls, improved scheduling, and higher quality project delivery. In other words, improved overall outcomes.
\nA substantial 85% of contractors foresee less time spent on repetitive tasks, while 75% have faith that AI can help mine historical data to learn from previous projects. Rather than relying fully on AI, 70% said the technology helps them make better, more informed decisions thanks to insights that may otherwise not be present.
\nAI implementation remains low, but companies are preparing for wider adoption
\nCurrently, AI adoption in the construction industry is low, despite awareness levels of 32% to 34%. This seems to be due to several reasons, including a lack of clear understanding, internal approvals, and software access. However, Dodge\u2019s research discovered more than half of companies surveyed are strategically preparing for AI with pilot programmes and staff training for AI-related positions.
\nAccording to the report, 40% of companies have a set budget for AI, 38% are developing teams for implementation, 19% are adapting old workflows, and 51% are assessing AI changes.
\nEarly adopters lead the way
\nOverall awareness of AI use in the industry is quite low, with just 20% to 50% of contractors knowing that certain management tasks implement AI, and very few actively use these functions. Nevertheless, early adopters of AI provided positive feedback, as more than 70% revealed that AI tools are hugely effective compared to more traditional methods, suggesting a potential for quick growth in AI use throughout the industry.
\nSecurity and accuracy lead concerns
\nThe main concerns of adopting AI revolve around security and accuracy. The report reveals that 57% are worried about the accuracy of AI output, while 54% have doubts over the security of company data.
\nInternal resistance to change (44%) and implementation costs (41%) are also cited as key concerns, but perhaps surprisingly, just 21% expressed concern over job losses. 31% believe current data quality is not yet adequate to support AI analysis.
\nAccording to the report, larger contractors are likely to rely more on AI than smaller firms, thus are more concerned about data quality and reliability. For instance, 69% of larger contractors cited lack of reliability or accuracy of AI outputs as a major concern, compared to 54% of smaller or mid-size contractors.
\nResearch data confirms that contractors are generally open to adopting AI, but the accuracy of AI outputs tend to stand in the way, as well as the desire for better tools, more information, and greater internal support.
\n17% of contractors said they do not sufficiently trust AI results, an issue that becomes more pronounced in sensitive areas like payments. Distrust in AI operations rises to 35% and 31% not having faith in AI managing project budgets.
\nA major theme is the need for more understanding before using AI. On average, 21% of respondents said they want a better insight of how AI works before considering using it, climbing to 31% for more complex tasks like safety risk assessments.
\nContractors also believe they are limited by their current software capabilities, with an average of 19% reporting their software does not offer the AI functions they require. The increases to 33% for managing resources.
\nInternal approval remains a notable obstacle, with 22% saying their company has not yet approved the use of AI, despite personal interest. Another barrier is a lack of time or resources that effectively evaluate AI tools. 13% stated this as a main reason why AI has not yet been adopted.
\nAlthough there are obvious challenges to mass AI use in the construction industry \u2013 and therefore significant market opportunity \u2013 only 5% believe AI would not be beneficial or improve current methods. That indicates a resistance that stems from various concerns rather than a lack of perceived value.
\nSteve Jones, Senior Director, Industry Insights Analytics at Dodge, spoke on the findings.
\n\u201cWe designed this study to look at the use of AI in the digital tools already deployed by contractors because that may offer the best solution to the challenge of data quality. But it is also heartening to see that many contractors are aware of the key challenges and the need for a rigorous approach to successfully implementing these tools at their organisations,\u201d the Dodge research states.
\nKey interest in emerging AI functionalities
\nAI\u2019s potential is clearly recognised, even if the industry\u2019s readiness to adopt it isn\u2019t quite matching the data. Certain areas are attracting the most attention when it comes to AI functions, like automated construction analysis, where 81% see potential benefits. 80% also show interest in intelligent permit submissions, while 79% believe in autonomous schedule and resource optimisation.
\n92% appreciate automated contract management and 76% recognise potential in AI-powered dynamic pricing. Although AI adoption remains limited, these strong numbers suggest the tide may soon be turning.
\nAI and the new age of the construction industry
\nThe latest data suggests a strong openness, maybe even an eagerness, to AI adoption in the construction sector. However, better tools, clearer guidance, and more trustworthy outputs are just some of the areas that need to be addressed before interest becomes implementation.
\n\u201cWith high awareness, strong interest, and powerful validation from early adopters, contractors appear poised for significant expansion in their use of AI-enabled tools in meaningful ways,\u201d said Steve Jones.
\nThe industry is on a \u201ctipping point for AI adoption\u201d according to Jones. When companies start to provide clearer pathways for adoption, the move towards AI-powered construction workflows will undoubtedly accelerate rapidly, reshaping how projects are delivered forever.
\n(Image source: \u201cTianjin Construction Site.\u201d by @yakobusan Jakob Montrasio is licensed under CC BY 2.0.)
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The construction industry generates colossal amounts of data, with much of it unused or locked in spreadsheets. AI is now changing this, enabling teams to accelerate decision-making, enhance margins, and improve project outcomes. According to new research from Dodge Construction Network (Dodge) and CMiC, the true transformative impact of AI is highlighted by contractors, with [\u2026]<\/p>\n
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