AI is redefining the consulting landscape
The rise of large-scale AI models is transforming traditional industries at an unprecedented pace. A McKinsey report estimates that by 2030, up to 30% of human working hours could be replaced by AI-powered systems. For cost consultants, this shift challenges the industry’s core value proposition—data and experience. Will professionals be sidelined or emerge as strategic leaders? The answer lies in how effectively firms adapt to the rapidly evolving AI landscape.
The rise of AI and its impact on cost consulting
Large-scale AI models like ChatGPT and DeepSeek are evolving from support tools into industry disruptors. Their impact on cost consulting is driven by two key capabilities:
- Large-scale pre-training: By learning from vast datasets, including historical project and regulatory frameworks, these models can perform domain-specific tasks—such as quantity takeoff, contract clause review, and report generation—with increasing precision.
- Round-the-clock automation: AI systems work tirelessly, executing repetitive tasks like data validation and indicator analysis with minimal error.
These capabilities are driving a revolution in efficiency. Tasks that once took weeks—like complex quantity calculations—can now be completed in hours. AI also reduces reliance on individual experts by learning from best-in-class projects, mitigating risks tied to staff turnover.
Industry challenge or catalyst?
At its core, cost consulting resolves information asymmetry in construction by translating vague requirements into clear financial strategies—balancing cost, quality, and investment. The industry’s edge has long relied on two strengths: interdisciplinary expertise and the ability to harness historical project data.
AI now challenges both. Tasks like quantity surveying, pricing, and proofreading are increasingly automated, while standardized outputs—such as bid analyses and contract comparisons—are especially at risk. As clients demand faster, more accurate results, firms face fee pressure and the growing commoditization of traditional services.
However, AI also unlocks new value. Data, once a byproduct, becomes a strategic asset. Firms with rich archives can train proprietary AI models, turning experience into a competitive advantage. As machines handle routine work, consultants can shift to higher-value roles—like strategic advisory and dispute resolution—boosting both productivity and the industry’s technical depth.
Future divergence: industry leaders vs. SMEs
Unlike the gradual adoption of BIM, AI’s integration is swift and far-reaching. It will affect every sector, and resistance is not a viable strategy. As the cost and value structures of the industry evolve, firms will need to choose their path.
- Industry leaders: With deep data reserves and digital platforms, they can quickly integrate or develop AI tools, reinforcing their market dominance.
- SMEs: Traditionally reliant on low-cost labor, they risk being left behind in an AI-driven marketplace. Survival will depend on forming alliances or specializing in niche markets.
Strategic framework: how to win in the AI era?
As AI continues to permeate our professional and personal lives, cost consultants must act decisively to seize the initiative. The following strategies are recommended:
Short-term strategy: digitize data and introduce AI tools
The first step is to convert historical project data into structured formats suitable for AI training—such as BQ lists, cost databases, and case repositories. At the same time, firms should begin integrating AI tools into core workflows like quantity takeoff and pricing. This frees up human resources to focus on higher-value activities such as client engagement and solution design.
Mid-term investment: build AI-ready talent
The future competitiveness of cost consultants will depend on the synergy between human expertise and AI tools. The ideal firm will be built on three pillars: high-caliber professionals, project databases, and an AI platform. To achieve this, firms must invest in talent with a blend of cost consulting knowledge, AI fluency, and data literacy. Additionally, firms must establish barriers through data governance, such as data ownership frameworks and blockchain-based evidence storage, to avoid being reduced to mere “data suppliers” for AI companies.
Long-term vision: establish proprietary AI systems
Ultimately, forward-looking firms should develop in-house AI platforms. Internally, these platforms can serve as intelligent command centers, driving enterprise-wide operations. Externally, they can function as client-facing value portals—delivering tailored, high-impact services that differentiate the firm in a competitive market.
Looking ahead
Large-scale AI models are evolving at an exponential speed. The future belongs to those who embrace this transformation—turning data into strategic assets and blending human expertise with AI capabilities. As China’s real estate market undergoes a prolonged period of adjustment, AI provides a critical opportunity for the industry to break through stagnation. Only by elevating technology from a tool to a strategic imperative can firms transcend cyclical challenges and define the rules of a new era.
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