The Tipping Point: AI’s Role in Reshaping ROCE

Every time it has happened in the past, I've kicked myself for missing the ride. For the most part, I've been like a busy frog in the well, not seeing it coming in time or just letting it pass, thinking it’s too late to dive in.

In 1996, Raju Louzado introduced me to the Internet. At the time, I dismissed it as a communication tool—something my computer science classmates could dominate. What could it possibly do for a hotel management student like me? Little did I realize it would transform into the backbone of business across industries, reshaping how hotels operate, market, and grow.

Now, in the 2020s, the industry is shifting again. But before we explore this change, let’s revisit the fundamentals—the four pillars of our business:

1. The Owner
2. The Operator
3. The Brand
4. Distribution

International brands often consolidate roles like operations, branding, and distribution, but the owner remains pivotal. The investor injects capital and expects returns. And let’s be clear—there’s one metric that determines success: Return on Capital Employed (ROCE).

As my friend Aaditya Agarwal from Kolkata once explained, ROCE is the purest measure of how efficiently capital generates returns. Asset appreciation is nice, but it’s agnostic—it could happen to a commercial complex or even a warehouse. Hotels, however, offer the unique ability to deliver consistent operational returns, which is why ROCE remains king for hotel owners.

Breaking the Cycle

Two metrics define ROCE:

1. Development Cost Per Room
2. Gross Operating Income (GOI) Per Available Room

The problem is clear. Rising construction costs and cyclical revenue (ADR and RevPAR) are squeezing ROCE. Revenue hasn’t recovered to pre-2007 levels, while development costs keep escalating. Owners are trapped in a vicious cycle—capital investments outpace revenue generation.

Enter AI-Powered Material Science

This is where AI reshapes the narrative. It tackles costs, durability, and sustainability head-on. Examples -

1. Optimizing Load-Bearing Materials

AI-driven predictive modeling has transformed material design. High-strength, lightweight alternatives like AI-enhanced self-compacting concrete (SCC) reduce structural load while maintaining durability. These innovations speed up construction and reduce labor costs.

2. Smarter Alloys

Machine learning has unlocked alloys with superior corrosion resistance and thermal stability, which are critical for properties in challenging climates like beach resorts or deserts. My colleagues Muthu Krishna shna and Srikantan Raghavan often stress the operational challenges of managing such properties. AI tools minimize these risks by ensuring infrastructure durability.

Interior Case Study: The Den, Bangalore

Let’s consider The Den Hotel in Bangalore, which boasts interiors made from raw silk—an aesthetic choice but at ?40 lakhs per room, a financial stretch. AI-driven material science could rewrite this equation:

• AI-Enhanced Prefabrication: AI designs silk-like composites using recycled polymers or bioplastics. These alternatives mimic raw silk’s texture and sheen but cost half as much, cutting interior costs from ?40 lakhs to ?20 lakhs per room.
• Prefabricated Panels: AI ensures precise manufacturing tolerances for prefinished luxury panels. This reduces reliance on labor-intensive, on-site applications, cutting timelines by 30-50%.

Case study - Scaling Impact for 100 Rooms

How AI Enables These Reductions:

1. Shell & Core: Prefabrication minimizes waste and labor, while AI designs lightweight, high-strength materials for efficiency.
2. Fa?ade: AI discovers cost-effective composites and optimizes fa?ade designs, reducing material and installation costs.
3. Interior Fit-outs: AI-driven alternatives mimic luxury materials like silk and wood at lower costs, providing significant savings.
4. MEP Systems: AI optimizes HVAC and plumbing layouts, reducing redundancies and enhancing energy efficiency.
5. Vertical Transportation: AI simulates usage patterns to minimize elevator systems and incorporates lightweight shaft materials.
6. Facility Equipment: AI streamlines procurement and optimizes layouts for kitchens, laundries, and other operational systems.
7. Other Building Works: Modular equipment designs simplify installation and reduce material waste, driven by AI insights.
8. Enabling Works: AI tools streamline logistics and site preparation, avoiding over-preparation and related expenses.
9. Professional Services: AI accelerates scheduling, task management, and cost tracking, reducing consultancy fees.
10. Contingency: AI predictive tools accurately assess risks, reducing unnecessary reserves.
11. Indirect Costs: AI improves workforce allocation and reduces rework through better collaboration and communication tools.

Real-Time Quality Control

AI’s impact doesn’t stop at cost reductions.

• Defect Detection: AI-powered imaging systems identify microdefects in prefabricated panels, preventing costly post-construction repairs.
• Longevity Testing: AI simulations test material wear over decades, ensuring resilience in harsh climates like Bangalore’s humidity.

Asset Beta - The Next Chapter for Hospitality -

RevPARs have hit a 13-year high, and AI is set to revolutionize how hotels are built, breaking free from the relentless cycle of rising costs and stagnant profits. Development timelines will shrink, efficiency will soar, and at the heart of it all, ROCE will take center stage.

For a long time, income-based valuations haven’t quite added up—it's always been an asset-driven business. But that’s about to change. The Asset Beta is set to shift, and it’s going to change for the better.

Operators who drive Asset beta will become more important, in other words, the measure of business risk independent of financial leverage, will shift from shifting from asset-heavy strategies (owning real estate) to asset-light strategies (Development efficiency and operating through leases, franchises, and management contracts)

The question is, who’s ready to dive in?