How AI & Automation are Changing Cleaning Products Manufacturing.pdf

This article delves into key regulations across the major markets, emerging compliance strategies, and innovative alternatives that are reshaping the cleaning products industry in US, Europe, Australia, and other parts of the world.

1. How AI & Automation are Changing
Cleaning Products Manufacturing?

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Overview
AI innovations are tackling longstanding pain points for cleaning product manufacturers, from
regulatory impediments to sustainability pressures, while fulfilling customers’ demand for
smart, hygienic, and green cleaning solutions. With AI-powered robots transitioning from
pilot projects to mainstream deployment in the cleaning industry, this transformation is
occurring across the entire value chain.
While AI-driven and automated industrial cleaning products are effective and strategically
vital, the switch from simply offering products to delivering a comprehensive and integrated
data-driven ecosystem poses both challenges and opportunities for industry players at
present. Now, manufacturers must re-engineer their operations, business frameworks, and
product formulations around sustainability, intelligence, and changing regulatory measures.
In this transformational phase, the market outlook looks quite promising for the industry
players. The global home & laundry care market is estimated to reach
around US$206.83bn by the end of 2025, with an annual growth projection estimated to be
3.12%. Especially, the laundry care segment is anticipated to attain the market volume of
US$110.02bn in 2025, with the US amounting to around US$33bn in the home & laundry
care market in 2025.
These figures underscore the growth prospects of industrial cleaning. Therefore, it is
beneficial to explore emerging trends/innovations, potential challenges of AI and automation
use in the cleaning businesses, and key factors defining the future of this sector.
Emerging Trends in AI and Automation Shaping Cleaning Products
Manufacturing
Product Innovation for Robotic Compatibility
Future-focused cleaning formulations must cater to robotic constraints, as autonomous
cleaning is swiftly replacing human users. Thus, manufacturers are looking forward to
investing in high-viscosity and low-residue formulations coupled with unit-dose water-soluble
pods for averting clogs in robotic dispensers. Further, QR-ingrained chemical cartridges
allow robots to determine optimal dilution, type of chemical, and application protocol,
reducing human input and improving precision. Apart from this, AI-driven fragrance
personalization, a prominent consumer differentiator, is enabling businesses to optimize
fragrance formulations for laundry and home care products for diverse customer bases as
per their skin compatibility and fragrance preferences.
AI-Driven Formulation and Sustainable R&D

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The household cleaning sector in the US is projected to grow at an approximate CAGR of
around 2.86% from 2025 to 2029, driven by stringent health regulations and the adoption of
green cleaning. AI actively helps balance environmental performance and compliance
through rapid innovations in R&D. In-silico formulation and automated lifecycle analysis are
emerging trends in this field, where AI frameworks assist in pre-screening for toxicity,
environmental impacts, and cleaning efficiency, eliminating the need for animal testing and
speeding up product development. Additionally, AI platforms help manufacturers comply with
corporate ESG mandates and the FTC’s Green Guides by providing real-time data on
toxicity, water use, and carbon footprints during innovation.
Regulatory Compliance through AI Automation
Cleaning products manufacturers struggle to navigate through a complex and fragmented
regulatory landscape, comprising state and federal laws. For instance, the Toxic
Substances Control Act (TSCA) continued being the focal point, with the US
Environmental Protection Agency (EPA) finalizing a regulation to prevent exposure to
trichloroethylene (TCE) and actively re-evaluating other chemicals like perchloroethylene
(PCE) in 2025. Meanwhile, the Federal Insecticide, Fungicide, and Rodenticide Act (FIFRA)
made it mandatory for manufacturers to submit annual production reports. On the state level,
the California Cleaning Product Right to Know Act asks for full ingredient disclosure on
websites and product labels. Hence, the focus is shifting towards devising a sustainable AI-
accelerated manufacturing ecosystem.
Automation of reformulation tags, eco-labels, and ingredient-level adherence is possible
through AI tools’ active tracking and interpretation of laws like California’s Per- and
polyfluoroalkyl substances (PFAS), disclosure laws of New York, and California’s SB 258.
Verified green claims through AI-generated, auditable information aid in averting penalties
concerning greenwashing.
Smart Factories for Agility and ESG
AI-driven smart facilities decrease risk factors while simultaneously cutting costs and
fostering compliance, reducing risk, mainly via predictive maintenance, tracking of energy of
water usage by IoT sensors for EPA reporting, and hyper-personalized or customized
productions.
Robotics-as-a-Service (RaaS) & Chemical Management as a Service (CMaaS)
Labor pressures and demand for efficiency are accelerating robotics adoption. Devices like
Pudu Robotics’ CC1 Pro (May 2025) integrate real-time dirt detection, UV-C disinfection, and
retractable LiDAR for dynamic cleaning in complex spaces. AI janitor robots have evolved
from robotic vacuum cleaners, which were used extensively for cleaning spaces in the last

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decades. Further, manufacturers are exploring the space of data and service providers with
analytics dashboards for clients, smart dispensers, and subscription models.
Complexities Involved in Wider Adoption of AI and Automation in Cleaning
Products Manufacturing
Financial Constraints and Implementation Barriers
Substantial investment is needed for rebuilding existing products and developing novel,
robotics-compatible solutions, such as high-viscosity and low-residue formulas that put an
added burden on companies. To address this challenge, companies are focusing on
adopting Robotics-as-a-Service (RaaS) models and CMaaS, turning capital expenditure into
operating expenses. This subscription-based approach is seen in sectors like healthcare,
aviation, and retail. However, AI janitor robots still struggle with performing cleaning tasks
like corner cleaning or navigating through stairs that explicitly require seamless human-robot
collaboration. For instance, Heathrow airport deploys RaaS robotic fleets to clean large
areas, while human staff handle detailing tasks and oversight. Also, issues remain in
creating formulations that meet the viscosity and solubility demands of the automated
dispensing system.
Data Privacy, Cybersecurity, and Compliance Concerns
Autonomous cleaning robots integrated with LiDAR, stereoscopic cameras, as well as
environmental sensors collect extensive spatial data, raising severe concerns around data
security, privacy, regulatory compliance, and data storage with evolving regulatory measures
in the US. To address these concerns, manufacturers are introducing privacy-aware
features, including camera activation only in unoccupied zones and built-in data
anonymization. Additionally, GDPR-compliant encryption and secure cloud systems under
emerging state laws like the California Consumer Privacy Act have become the norm as
businesses expect robust, transparent data protection in smart building and cleaning
solutions.
Socio-ethical and Market-specific Barriers
Increasing scrutiny surrounding potential greenwashing and eco-friendly claims of industry
players poses a major obstruction as manufacturers need to thoroughly follow the FTC
Green Guides, along with state-level legislations that demand verifiable, AI-supported data
to validate eco-friendly product and processes claims. Additionally, a significant barrier to the
adoption of next-gen AI and automation trends is workforce resistance rooted in job security
fears and privacy issues. For instance, New York City’s push to deploy cleaning robots in
public transit faced backlash over surveillance and job displacement concerns. Further,
questions are raised about fairness in AI’s decision-making and potential biases inherent in

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automated systems. Addressing these challenges requires robust retraining programs and
active community engagement to build trust, ensuring automation complements rather than
replaces frontline workers and aligns with labor standards.
Growth Prospects and Novel Business Avenues
Improved Service Delivery and Hygiene Standards
The future of cleaning industry manufacturers will be shaped by AI technologies that set new
hygiene benchmarks. Tools such as UV-C disinfection robots and air quality sensors will
become standard, enabling consistent, measurable health outcomes. With real-time data
validating cleaning protocols, cleaning operations will evolve into strategic assets that
support sustainability goals and ESG compliance, fostering green cleaning.
New Business Models and Service Offerings
The industry will extensively adopt models like Robotics-as-a-Service (RaaS), transitioning
to an OpEx framework that decreases entry barriers. Multi-robot coordination accompanied
by AI-integrated facility management platforms facilitates scalable, efficient operations, along
with opening new revenue streams and positioning home and laundry care firms as tech-
forward service providers. Also, advanced AI janitor robots and AI innovations in
nanotechnology will ensure enhanced multitasking and self-cleaning surfaces with intelligent
coatings. As pointed out in the emerging trends section, AI-powered assessment for product
development enables manufacturers to harness benefits from fragrance trends in laundry
and home care for unique market positioning in the sector. Other than this, AI-powered
green chemistry can be used to develop effective and sustainable ingredients for brand
differentiation.
Accelerating Market Growth and Investment Potential
The cleaning automation market is set for rapid expansion due to ongoing labor scarcity and
increasing hygiene standards. Voice-controlled AI janitor robots and customized cleaning
solutions are key areas to watch when investing in AI and automation within the cleaning
sector. Investor activity, M&A, and R&D are ramping up as the industry transitions from early
adoption to full-scale industrialization, forming a high-growth market.
Final Words
For cleaning product manufacturers, AI tools and automation technologies have taken a leap
from being optional to strategic assets. They serve as critical infrastructure in shaping the
future-focused industry from perspectives of operations and innovations. From robot-
optimized formulations to data-driven business frameworks and compliance automation, AI
technologies are opening new avenues for industry players where the market is strictly

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governed by regulatory and sustainability dimensions, demanding precision and rapid
product development. For manufacturers, success in the future will be defined by R&D
centered on robotics-compatible, eco-friendly & viable formulations, and upskilling teams to
sell data-driven service models (like Chemical Management as a Service) for better brand
positioning and competitive edge.
For more insights on the changing landscape of the cleaning products industry in the US,
join our industry experts at the US Cleaning Products Conference.

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