Artificial intelligence has the potential to significantly improve safety, efficiency, and decision-making in construction, highlighting the importance of AI adoption in the construction industry. However, several barriers continue to slow widespread AI adoption in the construction industry. According to Kaushal Diwan, leader of WND Ventures, the venture arm of DPR Construction, the biggest obstacles are data quality, cybersecurity concerns, and gaps in technology comfort across the workforce.
Diwan shared these insights during the BuiltWorlds 2025 Venture East Conference in Boston, emphasizing that AI is not meant to replace construction professionals, but to empower them throughout the project lifecycle.
Data Quality Challenges
One of the most persistent issues in construction is fragmented and inconsistent data. Information is often stored across multiple systems, and the level of detail varies widely, making it difficult for AI models to learn effectively. Addressing data quality is essential for the successful adoption of AI in the construction industry.
Safety data illustrates this challenge clearly. While the industry collects large amounts of information on incident rates, reporting methods and storage systems differ significantly across organizations. This inconsistency limits AI’s ability to identify reliable patterns and insights.
Diwan highlighted data standardization and strong leadership support as critical enablers. He also noted that startups that understand the complexity of construction data are well positioned to support AI adoption. At DPR, leadership-backed steering committees help identify and pilot AI opportunities across the business.
The Need for Strong but Practical Cybersecurity
Cybersecurity presents another major hurdle. As AI tools become more accessible, they also introduce new risks related to data exposure and misuse. Security teams are often cautious, but overly restrictive or unclear policies can slow innovation and experimentation. These challenges affect the process of integrating AI into the construction industry.
Improper deployment of AI tools in open enterprise environments can create vulnerabilities. Diwan stressed the importance of practical and simple security standards that protect the organization while still enabling employees to explore AI safely.
Collaboration between cybersecurity, IT, and business teams is essential to define where and how AI tools can be securely deployed within the organization.
Bridging the Technology Comfort Gap
Technology fluency varies widely across the construction workforce. While some professionals regularly use advanced digital tools, others rely heavily on face-to-face communication and minimal technology, particularly on jobsites. Therefore, bridging this gap is crucial for AI adoption within the construction industry.
Successful AI adoption requires empathy, patience, and easy-to-use interfaces that work both in offices and in the field. Diwan pointed out that organizations should provide safe environments for experimentation to encourage hesitant users.
At DPR, enterprise-wide access to tools such as Microsoft Copilot and licensed versions of ChatGPT helped lower the barrier to entry and encouraged broader engagement with AI.
Looking Ahead
While deploying AI at scale involves costs, Diwan believes the long-term benefits outweigh the challenges. Companies that adopt AI effectively can deliver greater value to clients, improve safety outcomes, and accelerate project timelines. The benefits highlight the growing importance of adopting AI in the construction industry.
AI is expected to significantly reshape the construction industry over the next five years. According to Diwan, the real question is no longer whether AI will transform construction, but how quickly companies can adapt and integrate these tools into everyday operations.
