“ Education is the advanced guard of progress, and it is to education that we must look for the conception and caring through of all progressive and constructive movements.”
The giant leap AI tech has made in the past couple of years has made it an invaluable resource in the kitchen and bath industry. Artificial intelligence makes the complicated process of remodeling a kitchen easier by providing a springboard for outstanding customer experiences. This is made possible by streamlining time-consuming elements of the process’s selection, purchasing, retaining, ordering, and installation aspects. How homeowners invest in a remodeling project has changed, and it has always been challenging and more favorable to the shopping experience or profitable for kitchen and bath firms.
As Standford Emeritus Professor John McCarthy coined and defined the term, Artificial intelligence is the science and engineering of making intelligent machines.
The variables involved in the education and selection through the platforms make product education more accessible for the prospect to digest. Streamlining the sales design and remodeling processes is about making them faster, smoother, and less complicated. Ultimately, AI demystifies the investing experience so that the cost of products and the investment is transparent and the design and execution are done much faster.
Competitive kitchen and bath design firms streamline the homeowner’s investing experience by leveraging technology advancements to improve the shopping experience on their website through interactive budgeting, 3-D modeling, estimating, and customer service.
Tech innovation improves virtually every aspect of kitchen remodeling, so homeowners have a better experience investing in their homes.
The grand news in AI development is that machine learning and deep learning via large language models – discussed in the Emerging trends, opportunities, and impacts section of this paper – are strengthening algorithms, raising their intelligence and capacity to learn so that machines can be relied on to analyze complicated issues and make in the moment decisions. AI has already matured to astounding capability, but the near future will bring more accessibility to AI discoveries by making those discoveries less expensive to produce en masse.
The kitchen and bath industry has finally grappled with the need to integrate technology into business. Instead of the great distance it used to be from competitive technology use, it’s now a much closer race in the adoption of tech resources among kitchen and bath firms. Independent kitchen and bath remodelers are now pulling business from their websites and using software to price, sell, design, and install kitchens. Artificial intelligence is indubitably streaming part of competitive technology available to the public.
AI is indubitably changing our lives by presenting conglomerate results and concerns in observation. Since virtually everyone is affected by artificial intelligence, its effects can be seen as its reach affecting the entire global population to some degree. Users of artificial intelligence undergo a different experience due to their engagement with technology. However, users and non-users may benefit from and potentially be at risk of privacy and safety concerns arising from AI advancements.
This paper provides a comprehensive overview of how AI is used in business, favoring the kitchen and bath industry. It discusses design and planning, how AI enhances customer experiences, its role in efficiency and optimization in project management, sustainability, building and remodeling, employee training programs, and emerging trends and opportunities resulting from continued AI development.
Kitchen design innovation
If you’re designing a kitchen, there are all these really detailed decisions that become difficult to work through, what we try to do is bridge that—take the design you like and apply it to your space. Basically, we’re trying to turn inspiration into reality.
—Ian Jaffrey
CEO, Skipp
Project optimization starts within a firm and works outward to the prospect. Automating tasks can satisfy customers’ needs for available products, cost, and efficient, speedy delivery.
While the excitement and apprehension about the rise of AI technology are both logical responses to its presence in the workplace, the concerns about AI can be dismissed as governments, regulatory authorities, and ethicists implement parameters for its use.
AI can handle many tasks that people do faster, making it ideal for streamlining services. However, AI is taking over only some of the kitchen and bath industry work. People still want to interact with other people when investing.
The high-yielding effects of AI in kitchen and bath remodeling are found in the streamlining of its services.
Algorithms can perform many time-consuming tasks, such as initial remodeling designs.
This leaves designers free to start designing a kitchen for the client from the available space and engage clients on their desired products. Kitchen and bath designers, professionals, and amateurs interested in algorithm-based designs can hire Skipp to generate them.
A straightforward effort accomplishes the complicated task.
First, a surveying instrument takes images of the preexisting kitchen. The data is implemented into an algorithm, generating a space model. A second algorithm changes the model into a new kitchen plan replete with current construction documents. After final changes are made and the design is complete, an architect reviews the plans, and the plan is ready to be built.
Skipp may enormously impact the kitchen and bath industry, enabling anyone with a kitchen to implement a remodeling design independently.
Predictive analytics for resource allocation and risk management
The demand for innovative, beautifully designed, and technologically advanced home appliances continues to grow every year, which means homeowners expect their appliances to work harder for them.
—Laura Fletty
Whirlpool
The decisions kitchen and bath firms make regarding the chance-taking questions it has can be measured by predictive analytics.
- How can our company earn leads and win clients more effectively through our website?
- How will job pricing be organized?
- What are the best cabinet vendors to carry?
As massive amounts of data are acquired, a method of understanding the data needs to be implemented. This wealth of information is interpretable by predictive analytics.
Predictive analytics is a branch of advanced analytics that uses historical data combined with statistical modeling, data mining techniques, and machine learning to predict outcomes.
Through predictive analytics, businesses can mine data, assess risk factors, and identify patterns and trends in buyer habits. By reading customer information, companies can see which of their strategies worked well and which ones did not.
Predictive analytic algorithms make it easier for companies to decide what part of their strategy should be changed, why it should be changed, and what it should replace it. This sort of immersion into consumer behavior comes at a minimal investment of time and risk.
Companies such as IBM, SAP, and MasterCard offer predictive analytic services.
MasterCard’s Test and Learn program helps companies find answers to key questions via data analysis to predict consumer behavior.
Applying how customers have operated in the past makes it possible to predict future behavior accurately.
Test new ideas to answer essential questions regarding strategy development.
Use predictive analytics to:
- Identify the impact of an initiative
- Discover the most effective and ineffective aspects of an initiative and why
- Learn who benefits from applied and hypothetical strategies
- Decide how to target rollout to maximize ROI
Benefits of predictive analytics
Predictive analytics provides a nexus of security, risk reduction, operational efficiency, and smart decision-making by showing where and why changes need to be made in operations and where maintenance can continue as usual.
Root cause analysis – The method of articulating problems’ causes to suggest specific solutions.
- Generate outstanding success and customer feedback
- Increase customer satisfaction
- Identify consumer patterns, such as product selection
- Firms can improve their viability with prospects and their relationships with clients, past and present
- Increase cross-selling opportunities by engaging clients in products and services suited to their taste
- Maximize profitability and productivity by connecting people processes and assets
- Strategize plans with a high probability of success and lower the occurrence of unproductive campaigns
- Focus on solving high-value problems
- Sustain healthy activity in successful endeavors and implementations
AI-driven inventory management systems
Supply chain management is getting smarter. AI interconnectivity is the future of supply chain management.
AI supply chain management is pointing the way for customers, vendors, and businesses to be connected not only with products but also with the smart objects that monitor them. Networks will be able to execute decisions faster and more accurately and will be able to detect and troubleshoot issues that arise.
Recognition algorithms are no longer merely predictive but hierarchical, so they can solve issues in order of significance and materialize as problems.
- Around-the-clock data transparency
- Forecast inventory control systems
- Optimize stock levels to reduce excess inventory and carrying cost
- Track and automatize recordings
- Accurately monitor stock levels
- Predict product demand
- Optimize logistics to ensure timely delivery of product
- Synchronize production with market demand
Through natural language processing, supply chain predictive analytics are being applied to service customer demand with exponentially greater service accuracy than ever before, as well as inventory checks, networking, optimization for preventative maintenance, and digital manufacturing. As real-time inventory calculations using supply chain AI become widely used, businesses can execute decisions worldwide.
AI assistance: Streamlining sales designers’ procedures for prospects’ benefit
Within the rise of virtual assistance is artificial intelligence virtual assistance. Many of the tasks sales design teams need to take care of on a week-to-week basis can be satisfied through artificial intelligence virtual assistants/agents (AIVAs) rather than outsourcing or hiring.
Uses of AIVAs
- Recruitment
- Providing job descriptions
- Assessing job applications
- Posting ads and conducting initial screenings
- Conduct employee onboarding
- Payroll administration
- Reconciling employee discharge and attendance data
- Create HR portals to capture hours logged in and leaves taken, handle discrepancies
- Notetaking and transcribing
- Document preparation
- Schedule meetings
- Secondary research
AIVAs streamline operations on both the inside for sales design teams and from the outside for the benefit of prospects and clients.
AIVAs remove much of the clerical work that needs to be done from day to day.
AIVAs can arrange inflow traffic from prospects, clients, and job candidates and serve outflows such as payroll, initiate interviews with viable candidates, or set up showroom visits with prospects. Handling these tasks frees sales design teams to focus on more nuanced aspects of the work, such as consulting, designing, or following up with ongoing remodels.
From the prospect or client’s perspective, AIVA streamlines and speeds up the intake and makes many things needed before an in-person meeting happen faster so the customer is served sooner. They also assist in streamlining the remodeling process by setting up follow-up meetings, note-taking, and scheduling.
Chatbots
Commonly, homeowners in the market remodeling their kitchen or bath will familiarize themselves with the products and services available before entering a showroom.
Chatbots have become more effective tools for solving customers’ needs in the past two years.
Advanced chatbot designs characterize greater vocabulary and accuracy in understanding and answering, making them more valuable than just collecting basic customer information.
Chatbots can answer questions about products and facilitate the payment process. They can also link users to a human being and live chat or receive a phone call.
Two styles of chatbots
Lower-ability chatbots are often deployed when a user appears on a webpage. These chatbots may help answer broad questions quickly, but they’re less sophisticated than other bots and may be more of a distraction than an assistance.
Higher-ability chatbots are accessed by users who know what they want and activate the bot for a specific reason. These chatbots use machine learning to understand inquiries beyond general questions and better assist users. They are designed to lead users to a human being for person-to-person communication when their assisting capabilities have been exhausted.
Natural language processing (NLP) links language models with statistical and machine learning models to program computers to recognize and generate text and speech.
Advanced chatbots use natural language processing to understand human speech, provide customer recommendations, and anticipate user needs.
AI for sustainability and energy conservation
The future of buildings is green. Cost-efficient, low-carbon, and no-carbon admitting structures have become viable objectives in the contracting industries.
Commercial buildings and residential now contribute to energy efficiency and production.
Indoor climate, predictions, holistic studies, and optimization of both new constructions and refurbishments optimal results within defined financial and physical boundaries.
With AI integration in automated demand response (ADR) and building energy management systems (BEMS), it is possible to monitor and control energy consumption, as well as identify opportunities to reduce energy waste and lower operational costs. AI can identify potential safety hazards during the building process and predict situations that may present risks in the future.
AI algorithms are useful for overseeing scheduling, product quality, efficiency, and customer satisfaction. AI can also manage concerns related to a building to create safer living spaces and protect against potential issues that could arise once the building is occupied.
Three phases of smart building
Phase 1 Gathering data
Sensors are deployed to measure and understand the pre-existing space. Sensors will gather information on virtually every area that pertains to using it. Airflow, humidity, and temperature are collected and applied to algorithms to increase efficiency.
Phase 2 Response to information
Phase 2 increases efficiency wherever needed. AI Algorithms may use historical data to forecast energy output and identify consumption patterns such as cost and CO2 emissions and water quality to reduce negative impacts on humans and the earth. At the time of writing, it’s possible to improve the efficiency of buildings by up to 30%.
Phase 3 Protection of occupants and property
AI can identify faults and make reconfigurations before they manifest as problems. AI in infrastructure is now maturing into widespread use and inclusion in new buildings.
It can direct the functionality of HVACs by filtering air during flu seasons, modifying temperatures, turning appliances on and off, and providing enhanced security.
Assessing energy consumption
Commercial and residential buildings can contribute to energy efficiency and production by AI algorithms defining financial and physical parameters. Cloud high-performance computing optimization is used to run simulation models that optimize properties and holistic studies, supply air and modify its temperature, and optimize the size and scope of solar power collectors and their corresponding results.
AI can be considered a virtual manager that monitors important factors such as temperature, pressure, and speed. Any deviations from optimal conditions trigger immediate adjustments.
Monitoring and controlling energy consumption systems
AI systems can identify opportunities to reduce energy waste and lower operational costs. Using automated demand response AI in building energy management systems, artificial intelligence can deliver up to 20% energy savings to buildings and 15% in transportation. These percentages may increase after new developments have been released for public implementation.
Concerns of AI in building
Privacy issues have always been a concern of technological advancement, and today, they are greatly increased by the simple fact that machines can learn like humans through data absorption. AI has demonstrated comprehensive knowledge and skill with extraordinary ability in multifarious applications. However, humans continue to guide the parameters of development at which AI functions for accuracy and safety.
AI requires massive amounts of data to be loaded into its system for it to have comprehensive knowledge and skill in simulating how to learn like a human being. With the transfer of data comes privacy risks and concerns about data leakage.
Privacy concerns are raised or settled in the handling of data. The most potent privacy-threatening concerns and how to handle them follow.
Opacity
AI systems operate in assertive “black box” protection. Users, no matter who they are, frequently cannot see or understand how AI algorithms arrive at a conclusion or act. Due to this feature, individuals or businesses may violate subject confidence and official regulations.
Algorithm bias
A wealth of concerns abound if biases perpetuate themselves from corrupted data or algorithms that are themselves flawed. From social, political, ethnic, and gender discrimination or advantage, potentially dire situations could arise for people or businesses.
Theft and unauthorized use of data
Great amounts of data are needed to train algorithms. Suppose the data needs to be carefully filtered for copyright and intellectual property rights. In that case, running AI algorithms can lead to the possibility of copyright infringement due to stolen or illegally distributed material.
Biometric breaching
AI systems must be monitored to avoid biometric data breaches such as face, eye, voice, and fingerprint scans.
The unauthorized use of data, whether intentionally or unintentionally, can lead to data leaks, theft, corruption, and system malfunctions. Astringent data protection must be monitored continuously, and the method by which data systems are protected must often be revised to compete against hacking.
Implementing robust cybersecurity measures
Safeguarding privacy risk requires proactive strategy. Leveling bias, maintaining transparency, competitive encryption, and fair handling – the methods that can be implemented to create safe cyber atmospheres and AI implementation fit into one of three defense categories.
- Technical solutions
- Ethical guidelines
- Governmental policy
Foundational privacy
Companies implementing AI algorithms into their business should encrypt their data and regularly audit systems. Privacy considerations should be made by design rather than improvised or attempted to solve through troubleshooting.
Limit retention times
Part of the purpose of ethical communities is to determine how long data should be accessible. Choosing short-term data accessibility reduces the chance that it can be illegally mined or compromised.
Transparency advocation
Data usage transparency discourages unethical action. Two fundamental proponents of transparency are using copyrighted data with permission or avoiding collecting it. Proactively identifying data and why it is being collected supports its ethical use.
User rights and control
Users should have control over their data, such as viewing, adding, and deleting options as inviolable rights.
Protecting rights and regulations
Data transfer and usage should be continuously visible and monitored by users.
Auditing business practices in AI algorithm development and implementation is a crucial measure against being proactive in upholding human rights, privacy, transparency, and concern for safe and legal business practices.
Emergence of new AI applications in kitchen and bath remodeling
Technology for virtually every aspect of service has made it possible for firms to build a competitive advantage by training their team in areas needed to advance its services. The specialist services of kitchen and bath remodeling are improved by mastery of programs such as DesignAlign, Chief Architect, Design 2020, Vive, Live Home 3D, and Prokitchen Oculus.
As profit augmentation is achievable by streamlining business, the programs mentioned above save hours by eliminating the rudimentary aspects of their service while operating in a transparent environment, allowing customers to note costs or see divine design development so they are fully aware of what happens behind the scenes during the design and product selection processes.
Integration of AI education and training programs in the industry
Advancing a team for competitive services is predicated on understanding each member’s personality and learning styles and identifying their aptitudes and weaknesses. Training team members is, therefore, ideally designated by what individuals already know and where they excel.
Newer innovations such as low-code/no-code programming offer a service to entrepreneurialism on the universalist scale. Now, coding possibilities bypass the skill gap between the non-coder and the coder. In France, programs can be generated through natural language rather than code. ChatGPT is an example of this development.
Low-code requires users to have some programming capability, such as HTML and Javascript, while no-code allows users with no coding experience to be involved in the coding process.
Low-code/no-code benefits
- Enables developers to spend less time on repetitive tasks so they can focus on optimizing an application’s functionality
- Enables researchers to leverage speed by removing the lower components of developing platforms
- Researchers can save time by avoiding any investment in infrastructure when testing prototypes and tools
- Buttresses visual development – instead of writing code developers, with dragon drop components or visual flow charts to define applications’ logic and functionality for better user experiences
- Developers can spend more time creating. Pre-built components, such as form, buttons, and data help free time up for the engaging aspects of development
- Reduces the need for custom coding
- Democratizes development, making it accessible to citizens, developers, business users, and even non-technical individuals
Low-code/no-code makes developing software more cost-effective, improving product scalability and streamlining user experience.
Emerging trends, opportunities, and impacts
The maturation of robotics lays a foreground for the mass integration of robots into daily life. Robot performance suitable for mass implementation requires precision accuracy, predictive maintenance, improved decision-making, and adaptability at a cost low enough for mass production and implementation.
AI capabilities are expanding through machine learning and deep learning. As the abilities of AI expand through machine learning and deep learning, the impact will be enormous.
Advanced robotics results from creating intelligent robots capable of learning and problem-solving.
Machine learning is a branch of artificial intelligence and computer science that uses algorithms to imitate the way people learn so that the system’s responses and capabilities improve over time.
Deep learning is an extension of machine learning that uses deep neural networks to simulate the decision-making power of the human brain.
Large language models (LLMs) are used to brainstorm emails and other vital communications that need to be made. The personalization comes from the author of the communication. However, AI can help the author brainstorm by offering suggestions, which may prompt the author to pull words and phrases here and there to generate their elocution.
These technologies are paving the way for the integration of robots into diverse industries, such as workforce labor and medical and scientific fields.
Cobots and mobile manipulators – Sensory advancements have led to the creation of robots that simulate sight and can grip objects, making them useful for assisting humans in loading and unloading, such as in factory settings. Mobile manipulators (MoMas) have been used in the logistics, aerospace, and automotive industries. They have dexterous arms, can manipulate objects, and can navigate through complicated environments.
Humanoids – With a build replicating that of human beings, humanoids can work in spaces designed for human beings, therefore integrating into pre-existing structures, theoretically able to do things that human beings can do faster and at a lower cost.
Safety and cost-saving measures
Predictive maintenance analyzes robot performance to determine how equipment and programming may operate. It is a time-saving measure. For example, downtime can cost the automotive parts industry $1.3 million an hour.
Digital twins are digital replications of robots that use real-world operational data to simulate and predict outcomes. They can be stress-tested and modified safely at a lower cost than their physical counterparts.
Digital twins can identify the most cost-efficient way to develop or change production methods, such as by discovering how to reduce energy expenses, downtime, and carbon emissions.
Implementing digital twins is a significant expense. They require the purchase of software and hardware and the hiring of skilled personnel to operate them. Since digital twins generate data, measures should be taken to avoid data leaks and privacy breaches.
Positive and negative impacts
Advanced robotics will make complicated and expensive performances easier to implement faster and ultimately less expensive. Using machine learning and deep learning, AI is changing how we live – from food service to military operations, agriculture, and driving.
For the convenience that AI brings to the workforce’s daily life and protects national and individual security, there is a concern about increased production capabilities and privacy compromises.
Since AI relies on massive quantities of personal data for machine learning and deep learning to occur, when data is compromised, it can have a catastrophic impact on the target of hacking or accidental data breaches.
Near future advances in AI
Rather than becoming something that chronicled the progress of the industry, Moore’s Law became something that drove it.
—Gordon Moore
President, Co-founder, Intel
Tech visionaries will continue to produce astonishing technological innovations that will bring benefits and concerns to the public.
Artificial intelligence has had an enormous impact on the world, and its abilities and users will continue to grow. AI found in various platforms used in the kitchen and bath industry makes it possible for firms to streamline their business and deliver fast, reliable service like big box stores while offering an intimate kitchen and bath remodeling experience.
While AI can be leveraged to help firms turn their enterprises into wealth-building machines, all users of AI should rigorously protect the privacy of those subjects and users who have helped build its algorithms.
Owners should encourage their teams to monitor future developments and opportunities in the kitchen and bath industry in AI.
Moore’s law teaches that approximately every two years, a significant development in some tech area is released to the public. As tech becomes smaller and more powerful, the cost to produce it remains about the same.
The advancements that have made it easier to sell kitchen and bath projects, virtual showrooms, and 3D modeling will continue to advance so that what fascinates today will be considered a necessary step in developing technology breakthroughs.
One event to watch for is Sora. Sora is a text-to-video program set to be released by OpenAI soon. With Sora, it will become easier for laypeople to design kitchens and baths and bring their designs to a firm to brush it out to a workable model. All it will take to manifest a kitchen design using Sora is feeding carefully thought-through text to its algorithm and watching it produce an image of the user’s dream kitchen.
The tech developments that currently assist sales designers and contractors will have broader applications, making any task a machine handles faster with each innovation.
The consolidation of tasks is a daunting perspective for many positions in every tech industry. However, there are aspects to selling and designing kitchens and baths that remain profitable for humans.
Machines cannot replace empathy. People will always want to interact with others to receive consultation and make investments. The nuances that come from decades of experience and make masters of professionals, regardless of the field, will continue to draw emotion and inspire those seeking it.
—SEN Design Group
Contact us to learn how to master strategic planning, sell more product into every job, leverage industry-specific tech developments, Good-Better-Best selling, and other smart kitchen and bath design implementations at one of SEN University’s esteemed in-person schools and online business courses.
