Jun 30, 2026, 4:29 PM ETInterview, Fireside Chat

The Future of Industrial AI with Honeywell Technologies Chairman and CEO Vimal Kapur

Separation into Three Entities: Honeywell is executing a split into three public companies: Honeywell Aerospace, Solstice Advanced Materials, and the residual Honeywell entity, with Vimal Kapoor remaining CEO of the latter.
Rationale for Split: The decision was driven by the view that corporate complexity had become a barrier to growth; the CEO explicitly stated the company needed to "do something simple" to unlock its next chapter.
Strategic Drivers: The move followed a two-year analysis triggered by the CEO's 2022 interview and the 2022 launch of Generative AI, which raised questions about the future of automation and the optimal housing of the aerospace cycle.
Portfolio Adjustment: The separation includes divesting businesses that did not fit the core growth themes, as the Chemical business was identified as a misfit requiring exit.
Shareholder Value: The process involved significant portfolio adjustments and was designed to create value through pure-play exposure, with Goldman Sachs assisting in scenario planning and board persuasion.

Revenue Composition: The automation segment generates revenue from a mix of 60% front-end capital spend and 40% ongoing operations expenditure (maintenance, services, and software).
Growth Characteristics: This dual-revenue model creates a "mid-single-digit" secular growth baseline that is resilient to cyclicality in any single end market.
R&D Investment: R&D spending increased to 4.8% of total revenue in 2025, representing a 40 to 50 basis point increase over the previous baseline to drive new product development.
Forge Platform: Honeywell's AI platform, Forge, achieved profitability (break-even) in the previous year and is now a profit center rather than a loss leader.
Future Growth Traction: Growth is projected to come from three compounding sources: the capital cycle, the OPEX maintenance cycle, and AI-driven operational efficiency over the next 5 to 10 years.

Market Problem: Physical AI addresses the critical shortage of skilled operators in industrial settings, with global labor replacement rates ranging from 1.5 to 1.6, far below the 4-5% annual productivity gains required by the sector.
Definition of Physical AI: Unlike consumer AI, this focuses on solving known industrial problems (uptime, operational excellence) using proprietary, non-public data to manage continuous 24/7 systems like data centers, refineries, and semiconductor fabs.
Data & Domain Friction: The sector faces significant barriers to entry for competitors due to the necessity of proprietary data and the need for deep domain-specific context (e.g., distinct requirements for pharmaceutical plants vs. hospitals).
Augmentation over Autonomy: Honeywell is building "agentic systems" that augment human decision-making rather than replacing it; the strategy involves providing multiple options to humans (similar to Google Maps) rather than making the final decision.
Workforce Shift: The technology is expected to reduce manual data lookup time by approximately 20% and shift the workforce requirement toward a different skill mix rather than reducing total headcount.

Timeline for Utility: The CEO estimates that identifying practical use cases and solving the economic equation for quantum computing will take 2 to 3 years.
Engineering Milestone: The scientific feasibility of quantum computers is considered solved, with the current focus shifting to engineering challenges and the expectation of quantum advantage over classical computers within a year.
Strategic Application: Quantum computing is viewed as a complement to classical AI, specifically targeting unsolved problems in drug discovery, fusion, and cryptography.
Market Inflection: The CEO likens the current quantum development phase to the pre-2022 Generative AI landscape, where a sudden breakthrough is expected to drive rapid, slow-inflection adoption.

Corporate Role Simplification: Post-separation, the corporate function will focus exclusively on three pillars: portfolio strategy, operating system design, and talent management.
Metrics Reduction: The company is simplifying its performance metrics, arguing that a two-dimensional matrix is sufficient compared to complex multi-dimensional scoring systems.
Time Management Discipline: The CEO enforces strict boundaries on leadership time, dedicating 33% of time to external customer engagement and refusing to stay late in the office to signal organizational efficiency.
Decision Rights: The leadership philosophy emphasizes reducing corporate interference in day-to-day business decisions to prevent bureaucratic friction and value dilution.

Political Cycle Theory: While acknowledging current political instability, the CEO predicts a return to stability once the current global cycle concludes.
Purpose-Driven Growth: Optimism is derived from the existence of unsolved global issues (aging, energy, infrastructure) that require the company's solutions to improve human quality of life.
Forward-Looking Stance: The company rejects pessimism, maintaining that continued progress is essential to prevent a regression in human development and economic value creation.