This EY analysis captures a gap I see every day in Italian real estate and construction. People are already using AI in a spontaneous way to draft emails, refine reports, translate documents, even support design and marketing. All this use rarely turns into measurable value at project or portfolio level. It remains “shadow AI”: individual experiments, unmanaged risks (especially on data and confidentiality), and no real impact on cost, time, quality, or user experience. So, the most useful contribution of the article becomes a very practical roadmap: - identify a few high-impact use cases for each phase: feasibility (planning and market checks), design (BIM support, code hints), tender (drafting and analysing offers), construction (site reporting, delay/risk analysis), sales and asset management (buyer support, documentation); - build targeted training on these workflows, not generic “AI showcases”; - provide company-approved tools and clear rules, reducing dependence on personal accounts and lowering legal and reputational risk

To get the employee to use AI for more than the basics the company needs to give them time and education. AI is still a new tool and new technology and what we can do today is not what we will do tomorrow so time to learn is the best way to go.

Employees need continuous upskilling through targeted training programs that expose them to more sophisticated AI tools and use cases relevant to their specific roles.

Great 👍

♟Building the AI-native talent pipeline falls into three main buckets: 1️⃣ Base technical skills — Gen AI tools & models — our India is doing good here — these skills are certifiable, teachable & scalable. For example: ▪︎Prompt engineering ▪︎LLM workflows ▪︎RAG systems ▪︎Python coding 2️⃣ Agentifying skills — Fusing AI autonomy, self-learning workflows, & self-correcting intelligent agents with deep sector-specific, domain intelligence & global value chains — India is not keeping pace here — and carefully harnessing agentic AI with a clear understanding of sector‐specific nuances, & domain context can't be taught in a 3-month bootcamp. The real shift: from a "cost-center" mindset to an "AI-native product /platform innovation" culture". For example: ▪︎Agentic AI-led cyber security across the global banking value chain. ▪︎AI-native fashion design. ▪︎Agentic, self-learning, & autonomous shoe factory. 3️⃣ AI-first strategizing & conceptualization skills + Emotional courage for continuous leadership reinvention + AI-native judgement — This is where our India's talent pipelines are missing or lagging behind. For example: ▪︎Envisioning a responsible AI-first GCC-as-a-Service.

The fact that 88% of AI is used for basic tasks is the starting point. AI is already here; the challenge for leadership is to create the mindset and tools to use it for complex, high-value tasks.