Negotiation time down 20%.
Void periods cut by 1.5 months.
A scoring-based lease-negotiation tool that combines lease and market data to recommend optimal negotiation points — cutting void periods and preserving six figures in monthly rental revenue for a PE-backed shopping centre joint venture.
negotiation time
per turnover event
revenue per month
partner approval secured
Client
A private equity-backed regional shopping centre operating in commercial real estate and retail, structured as a joint venture between the mall operator and external partners.
Goal
Analyse the current data environment, develop a data strategy, define a roadmap to data maturity, and lead delivery of its first phase.
No way to tell a good AI bet from a bad one — and no agreement on who’d own it.
There were no clear metrics or prioritisation framework for selecting AI use cases. Business teams pitched plenty of high-potential ideas, but with no consistent way to weigh commercial impact against delivery complexity, investment was hard to justify and quick wins were hard to demonstrate.
The mall operated under a complex joint-venture structure, and partners held conflicting views on who should own and control any AI solutions built. Without a clear operating model, governance approach and IP framework, stakeholders were reluctant to fund or adopt shared data products — creating risk around resourcing, maintenance and commercial return.
Three constraints were non-negotiable:
- No consistent way to score AI use cases against commercial impact and delivery complexity
- JV partners disagreed over IP ownership and control of any AI solution built
- Stakeholders would not fund shared data products without a clear governance model
A scoring framework first, a lease tool second.
A strategic framework linked the company’s vision and value-creation targets — EBITDA uplift and void-period reduction — directly to a pipeline of proposed AI use cases. Each was scored on three dimensions: expected commercial impact, alignment to those value targets, and ease of delivery, covering data availability, technical complexity and time to value.
In a joint venture, the hardest part isn’t the model — it’s agreeing who owns what it produces.
An operating model defined roles across data ownership, product-facing SMEs and a central AI delivery lead. The IP model split the difference the JV needed: foundational models and data stayed jointly governed under shared terms, while solution-specific IP and commercialisation rights were allocated in proportion to each partner’s contribution and investment.
The first use case selected through this framework was a lease-negotiation accelerator: consolidated lease and market data, automated contract clause identification, and an analytics-driven scoring model recommending optimal negotiation points and their likely impact on occupancy timelines. The Fractional Head of AI led the build, pilot and rollout, coordinating IT, leasing and legal teams on data access, model validation and operational integration.
A 20% faster negotiation, and a green light from every partner.
The engagement turned a stalled JV — no prioritisation criteria, no agreement on IP — into a funded, value-aligned AI roadmap. The prioritisation framework built a pipeline of further use cases across tenant mix optimisation and customer experience, and the governance model removed the ownership friction that had been blocking investment.
* Case studies reflect work undertaken by our Heads of AI either during their tenure with Head of AI or in prior roles before they were part of the Head of AI network; they are provided for illustrative purposes only and are based on conversations with our Heads of AI.
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*Case studies reflect work undertaken by our Heads of AI either during their tenure with Head of AI or in prior roles before they were part of the Head of AI network; they are provided for illustrative purposes only and are based on conversations with our Heads of AI.