Table 2 Key themes from the industry... | Emerald Publishing

Table 2

Key themes from the industry workshop and mapping to business model components (derived from 25 respondents' feedback)

Question and focus area	Themes identified from feedback	Count	Representative quote (translated)	Business model mapping
Q1: Near-term AI potential	Tendering and risk analysis: Using AI to parse proposals, check contract interfaces and identify risks	4	“Check contract interfaces and exceptions with AI.”	C2, C7
	Knowledge management: Improving data/document use and learning between projects	4(+1)	“Improve use of project documentation during construction.”	C6, C7
	Project execution and quality: Automating on-site supervision and quality control	2(+1)	“Automate supervision and raise quality.”	C7
	Disruptive models: Unbundling procurement of labor/materials; shifting competition to customer experience	2(+4)	“Separate materials and labor; logistics becomes decisive.”	C2, C7, C8
Q2: Realism of AIaaS	Skepticism and barriers: Concerns over data privacy, competitive advantage and the limited value of single-firm data	3	“The data from one operator is ultimately very thin … who will boldly utilize information paid for by someone else?”	C5, C6
	Conditional optimism: Feasible if quality, traceability and maintenance are guaranteed	4	“Realistic if quality metrics, traceability and maintenance are guaranteed.”	C4, C5
	Internal focus first: View AI primarily as a tool for internal productivity gains before external sales	3	“I currently see AI services as an internal productivity leap for companies.”	C5, C7
Q3: New ecosystem partners	Data and AI Specialists: Need for partnerships with data analytics and AI expert firms	2(+1)	“Data analytics and AI expert companies will become partners for construction companies.”	C8
	Technology and Logistics Providers: Importance of data platform providers and JIT logistics operators	2	“Data are definitely key, but, e.g. logistics operators will become more diverse.”	C8
	New Strategic Alliances: Deeper partnerships with clients, research labs and certification bodies	2	“Research institutes, certifiers, labs, component manufacturers … ”	C8

Question and focus area	Themes identified from feedback	Count	Representative quote (translated)	Business model mapping
Q1: Near-term AI potential	Tendering and risk analysis: Using AI to parse proposals, check contract interfaces and identify risks	4	“Check contract interfaces and exceptions with AI.”	C2, C7
	Knowledge management: Improving data/document use and learning between projects	4(+1)	“Improve use of project documentation during construction.”	C6, C7
	Project execution and quality: Automating on-site supervision and quality control	2(+1)	“Automate supervision and raise quality.”	C7
	Disruptive models: Unbundling procurement of labor/materials; shifting competition to customer experience	2(+4)	“Separate materials and labor; logistics becomes decisive.”	C2, C7, C8
Q2: Realism of AIaaS	Skepticism and barriers: Concerns over data privacy, competitive advantage and the limited value of single-firm data	3	“The data from one operator is ultimately very thin … who will boldly utilize information paid for by someone else?”	C5, C6
	Conditional optimism: Feasible if quality, traceability and maintenance are guaranteed	4	“Realistic if quality metrics, traceability and maintenance are guaranteed.”	C4, C5
	Internal focus first: View AI primarily as a tool for internal productivity gains before external sales	3	“I currently see AI services as an internal productivity leap for companies.”	C5, C7
Q3: New ecosystem partners	Data and AI Specialists: Need for partnerships with data analytics and AI expert firms	2(+1)	“Data analytics and AI expert companies will become partners for construction companies.”	C8
	Technology and Logistics Providers: Importance of data platform providers and JIT logistics operators	2	“Data are definitely key, but, e.g. logistics operators will become more diverse.”	C8
	New Strategic Alliances: Deeper partnerships with clients, research labs and certification bodies	2	“Research institutes, certifiers, labs, component manufacturers … ”	C8