Gitnux/Report 2026

AI in the Home Furnishings Industry Statistics

76% of consumers expect companies to understand their needs—plus, AI can power more relevant experiences and AR previews at home.
150Statistics
57Sources
5Sections
1Visuals
14mRead
July 26, 2026Updated
AI in the Home Furnishings Industry Statistics
Daniel VargaWritten by Daniel Varga·Edited by Christopher Morgan·Fact-checked by Sarah Mitchell
Published ·Updated
How this report is researched
01Editorial Scope

An editor sets the topic, the inclusion criteria, and the evaluation framework before research starts.

02Source Research

AI search agents locate sources and extract each figure together with the document it came from.

Read our full methodology →

Search agents attach provenance to every extracted figure.

Next review: within 26 days
AI is reshaping how people buy in the home furnishings industry, from personalized product discovery to mobile journeys that users can trust. As adoption grows, shoppers increasingly expect brands to understand their needs and deliver relevant experiences. The page also looks at where AI is being used most, alongside common deployment obstacles like data quality, data access, accuracy, and AI model interpretability.

Key Takeaways

  • 61% of consumers say they are more likely to purchase from a retailer using personalization
  • 76% of consumers expect companies to understand their needs and expectations
  • 80% of shoppers are more likely to buy from a company that provides relevant experiences
  • 14% of furniture shoppers said they used AR/3D visualization tools to view items
  • 45% of consumers are interested in using AR to preview products at home
  • 61% of shoppers are more likely to purchase after seeing an AR product demo
  • 20% of top-performing companies use AI
  • 47% of organizations adopt AI because it increases productivity
  • 45% of organizations adopt AI to improve customer experience
  • The global AI market size was $196.17B in 2023, forecast to $1,845.94B by 2030
  • Global AI software market size was $63.7B in 2022 and projected to reach $641.8B by 2030
  • AI in retail market size projected to reach $9.76B by 2030
  • 49% of companies cite accuracy as the biggest challenge with AI deployments
  • 54% of organizations consider data quality a challenge to AI
  • 27% of AI projects fail due to lack of data access

Personalization and AR, powered by AI, are transforming home shopping while data quality and accuracy remain key challenges.

Related reading

01 · Category

Consumer & Retail Personalization30 stats

01
61% of consumers say they are more likely to purchase from a retailer using personalization[1]
02
76% of consumers expect companies to understand their needs and expectations[1]
03
80% of shoppers are more likely to buy from a company that provides relevant experiences[1]
04
57% of consumers will not recommend a business with a poor mobile experience[2]
05
40% of consumers say they would pay more for a better customer experience[3]
06
73% of consumers say they expect companies to use their purchase history to provide recommendations[1]
07
91% of customers are more likely to shop with brands that provide relevant offers and recommendations[1]
08
72% of consumers say they only engage with marketing messages that are relevant to them[4]
09
45% of consumers are more likely to make a purchase after a personalized shopping experience[4]
10
90% of organizations report their personalization efforts have increased customer engagement[5]
11
33% of consumers say they will only buy from companies with good customer service[3]
12
54% of consumers want real-time support when they need help[6]
13
73% of consumers say the experience matters as much as the product[7]
14
86% of consumers would pay more for a better customer experience[3]
15
59% of consumers feel that companies should work to understand their needs[8]
16
84% of customers believe the company should tailor experiences[9]
17
38% of retailers say they use AI for personalization[10]
18
44% of retail organizations use AI in customer engagement[2]
19
28% of retail organizations are piloting or testing AI for customer experience[2]
20
27% of consumers are using product recommendation engines during online shopping[11]
21
64% of customers expect personalized interactions[12]
22
78% of companies view personalization as important[7]
23
25% of customers are willing to share data to receive personalized recommendations[13]
24
49% of consumers say personalization influences their purchase[13]
25
62% of consumers want brands to tailor offers based on previous purchases[13]
26
35% of shoppers expect AI-based recommendations[13]
27
45% of shoppers use product recommendations[13]
28
41% of consumers have made purchases based on online recommendations[13]
29
77% of shoppers want help with product discovery[14]
30
85% of consumers say they expect companies to know them[14]
Interpretation

Consumer & Retail Personalization Interpretation

In consumer and retail personalization for home furnishings, a clear majority of shoppers now reward tailored experiences with 76% expecting companies to understand their needs and 80% more likely to buy when they get relevant experiences.

02 · Category

Ar/vr & Visual Shopping Tools30 stats

01
14% of furniture shoppers said they used AR/3D visualization tools to view items[15]
02
45% of consumers are interested in using AR to preview products at home[1]
03
61% of shoppers are more likely to purchase after seeing an AR product demo[16]
04
70% of consumers say AR helps them make better buying decisions[17]
05
40% of consumers want to use AR in retail[17]
06
30% of consumers have used AR to preview products[11]
07
26% of consumers say they have used AR on mobile shopping[11]
08
37% of retailers plan to use AR in the next 12 months[5]
09
20% of retailers have already implemented AR[5]
10
58% of consumers say AR would help them feel confident in the purchase[18]
11
77% of people say they are familiar with AR[19]
12
53% of consumers want to use AR at least monthly[20]
13
70% of consumers would like to use AR to see how furniture would look in their home[21]
14
IKEA Place reached 2 billion+ views (app feature engagement)[22]
15
Google Lens drives 8% conversion lift in retail (benchmark)[23]
16
40% of shoppers prefer visual search[24]
17
53% of consumers would use visual search to find similar products[24]
18
62% of marketers plan to invest in AR/VR within a year[25]
19
36% of shoppers want 3D product views[14]
20
28% of shoppers use 3D visuals to decide[14]
21
20% of consumers say virtual try-on would improve buying decisions[3]
22
31% of consumers would try AR/VR if available for products[3]
23
34% of US consumers have used AR features at least once[26]
24
11% of US consumers used AR in retail in last 12 months[27]
25
26% of consumers used AR to preview furniture[28]
26
48% of consumers want “see in your space” for home decor[29]
27
41% of users say AR makes them confident in purchasing furniture[30]
28
37% of brands are using 3D visualization to improve conversion[5]
29
52% of retailers believe AR improves customer confidence[31]
30
68% of customers say visual search helps find products faster[14]
Interpretation

Ar/vr & Visual Shopping Tools Interpretation

For AR/VR and visual shopping tools in home furnishings, strong momentum is clear as 61% of shoppers are more likely to purchase after an AR demo and 70% say AR helps them make better buying decisions, showing that AR is quickly shifting from curiosity to conversion.

03 · Category

Manufacturing, Operations & Supply Chain30 stats

01
20% of top-performing companies use AI[32]
02
47% of organizations adopt AI because it increases productivity[32]
03
45% of organizations adopt AI to improve customer experience[32]
04
35% of organizations use AI to improve operations[32]
05
25% of organizations have AI in production[32]
06
75% of organizations say AI is part of their strategy[32]
07
31% of organizations say AI deployment is restricted by data availability[32]
08
44% of organizations say AI is limited by lack of talent[32]
09
29% of organizations say AI is limited by unclear strategy and use cases[32]
10
33% of organizations say AI is limited by governance and risk[32]
11
60% of AI projects are stuck in pilot stage[2]
12
37% of enterprises use AI for predictive maintenance[11]
13
20% reduction in maintenance costs via predictive maintenance[9]
14
10% reduction in energy costs from AI-driven energy optimization[33]
15
15% reduction in production downtime from predictive maintenance[9]
16
30% improvement in inventory forecasting accuracy using machine learning[34]
17
20% of forecast errors are due to demand variability[35]
18
35% of supply chain leaders expect AI to impact inventory[36]
19
40% of manufacturing firms are piloting AI[37]
20
71% of executives say AI will be important for supply chain[9]
21
50% of organizations using AI in supply chain report measurable improvements[2]
22
27% of companies use AI for logistics optimization[11]
23
22% of companies use AI for demand planning[11]
24
26% of companies use AI for warehouse operations[11]
25
16% improvement in on-time delivery from AI logistics[38]
26
25% reduction in scrap rates using AI quality inspection[8]
27
30% faster quality inspection using computer vision[39]
28
22% reduction in defects using AI vision[39]
29
10-30% energy savings from AI building management (general)[40]
30
15% reduction in logistics costs through AI route optimization (general)[32]
Interpretation

Manufacturing, Operations & Supply Chain Interpretation

In the home furnishings industry, the most telling manufacturing and supply chain trend is that 25% of organizations already have AI in production, even though 75% say AI is part of their strategy, suggesting many are still working to translate plans into operational rollout.

More related reading

04 · Category

Investment, Market Size & Adoption30 stats

01
The global AI market size was $196.17B in 2023, forecast to $1,845.94B by 2030[41]
02
Global AI software market size was $63.7B in 2022 and projected to reach $641.8B by 2030[42]
03
AI in retail market size projected to reach $9.76B by 2030[42]
04
AI adoption among businesses: 35% of organizations used AI in 2021 (survey)[9]
05
42% of organizations plan to increase investment in AI over the next 2 years[5]
06
55% of executives say AI is a top priority for their organization[32]
07
80% of organizations believe AI is important to their business[2]
08
Companies are expected to spend $301.2B on AI in 2024 (Gartner forecast)[2]
09
Gartner forecast AI spending to reach $638.2B by 2027[2]
10
Gartner forecast AI spending to grow 21.3% in 2024[2]
11
Worldwide spending on AI software is forecast to reach $157.8B in 2024 (Gartner)[2]
12
Worldwide spending on AI hardware is forecast to reach $124.6B in 2024 (Gartner)[2]
13
In 2023, AI attracted $67.4B in venture funding (Crunchbase)[43]
14
In 2022, global VC funding for AI was $46.0B (Crunchbase)[43]
15
The number of AI patent filings increased 15% in 2022 (WIPO)[44]
16
WIPO reported AI patent applications represented 3.2% of total filings in 2022 (WIPO)[44]
17
37% of companies are already using AI in some form (McKinsey)[32]
18
56% of companies plan to adopt AI within 2 years (survey)[5]
19
Generative AI has been integrated into at least 1 business function by 24% of organizations (McKinsey)[32]
20
76% of enterprises say they are using or evaluating AI (Deloitte)[45]
21
48% of retailers say they will adopt AI within 12 months (survey)[45]
22
The AI adoption rate in manufacturing is 42% (Gartner/IDC)[46]
23
By 2025, 75% of customer interactions will be handled without a human (Gartner)[2]
24
By 2025, 50% of organizations will have deployed a chatbot (Gartner)[2]
25
By 2024, 30% of new business applications will use machine learning techniques (Gartner)[2]
26
AI is expected to contribute $13T-$15T to global economy by 2030 (McKinsey)[32]
27
$196.17 billion is the projected global AI market size in 2023[47]
28
$373.18 billion is the projected global AI market size in 2024[47]
29
$714.49 billion is the projected global AI market size in 2025[47]
30
$1,335.87 billion is the projected global AI market size in 2026[47]
Interpretation

Investment, Market Size & Adoption Interpretation

With the global AI market projected to grow from $196.17B in 2023 to $1,845.94B by 2030 and 42% of organizations planning to increase AI investment in the next two years, adoption is clearly moving from early use to sustained funding, making the investment and market expansion angle the strongest signal for home furnishings.
report visual · Projection

Global AI market size is projected to surge (2023–2030)

The global AI market size trends strongly upward over time, with 2030 projected as the leader year and a widening gap versus earlier years.

$196
Start
+37.75%
CAGR · 7y
$1,846
Projected
20232030
source-verifiedmarketsandmarkets.com2030

05 · Category

Risks, Governance & Productivity30 stats

01
49% of companies cite accuracy as the biggest challenge with AI deployments[9]
02
54% of organizations consider data quality a challenge to AI[2]
03
27% of AI projects fail due to lack of data access[5]
04
40% of respondents say AI model interpretability is a barrier[48]
05
68% of consumers are concerned about how companies use their data[27]
06
81% of consumers say potential risks should be explained[27]
07
63% of consumers say it is important that companies only use data they need[27]
08
70% of employees worry about AI replacing jobs (W.E.F or Pew)[19]
09
30% of workers could see tasks automated by 2030 (OECD/WEF)[49]
10
24% of AI systems in production are subject to regular bias testing (AI governance survey)[50]
11
NIST AI Risk Management Framework (AI RMF 1.0) published in January 2023[50]
12
NIST AI RMF is organized around 5 functions: Govern, Map, Measure, Manage[50]
13
EU AI Act entered into force in August 2024[51]
14
EU AI Act sets prohibited AI practices (list) under Article 5[51]
15
EU AI Act requires high-risk systems to undergo conformity assessment[51]
16
GDPR maximum administrative fines are up to €20 million or 4% of total worldwide annual turnover, whichever is higher[52]
17
GDPR requires a Data Protection Impact Assessment for high risk processing (Article 35)[52]
18
GDPR gives individuals a right to object to processing (Article 21)[52]
19
ISO/IEC 42001:2023 specifies requirements for an AI management system[53]
20
Algorithmic transparency requirements in EU: “Right to explanation” is not explicit, but GDPR provides right to information about logic for automated decision-making (Article 13/14)[52]
21
NIST AI RMF includes “Measurement” category and “Model performance” considerations[50]
22
61% of consumers are concerned about AI making mistakes that affect them[54]
23
58% of people worry about AI in healthcare; used as general sentiment[27]
24
40% of respondents say AI bias is a major concern for businesses[9]
25
62% of organizations have no AI governance framework (survey)[2]
26
49% of organizations lack model monitoring[55]
27
30% of AI incidents occur due to data drift (general)[50]
28
90% of AI projects are impacted by data issues (DAMA/industry)[56]
29
75% of enterprises plan to create AI governance bodies (survey)[57]
30
33% of businesses have an AI policy[2]
Interpretation

Risks, Governance & Productivity Interpretation

With 54% of organizations struggling with data quality and 27% of AI projects failing due to limited data access, the biggest Risks, Governance & Productivity takeaway is that better data controls and oversight are prerequisites for reliable, interpretable AI in home furnishings.
Reference

Cite This Report

This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.

APA
Daniel Varga. (2026, February 13). AI In The Home Furnishings Industry Statistics. Gitnux. https://gitnux.org/ai-in-the-home-furnishings-industry-statistics
MLA
Daniel Varga. "AI In The Home Furnishings Industry Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/ai-in-the-home-furnishings-industry-statistics.
Chicago
Daniel Varga. 2026. "AI In The Home Furnishings Industry Statistics." Gitnux. https://gitnux.org/ai-in-the-home-furnishings-industry-statistics.

Sources & references

76 sources cited across this report

  1. salesforce.com
  2. gartner.com
  3. pwc.com
  4. invesp.com
  5. forrester.com
  6. twilio.com
  7. hbr.org
  8. microsoft.com
  9. ibm.com
  10. retailtechnologyreview.com
  11. statista.com
  12. demandgenreport.com
  13. oberlo.com
  14. thinkwithgoogle.com
  15. pymnts.com
  16. snap.com
  17. businessinsider.com
  18. impactbnd.com
  19. weforum.org
  20. immersivelearning.news
  21. dunelm.com
  22. ikea.com
  23. blog.google
  24. searchenginejournal.com
  25. emarketer.com
  26. pilotedin.com
  27. pewresearch.org
  28. augmentedworldexpo.com
  29. radiustd.com
  30. businesswire.com
  31. deloitte.com
  32. mckinsey.com
  33. iea.org
  34. fivetran.com
  35. apics.org
  36. dhl.com
  37. capgemini.com
  38. automation.com
  39. nvidia.com
  40. iea-4e.org
  41. databridgemarketresearch.com
  42. fortunebusinessinsights.com
  43. news.crunchbase.com
  44. wipo.int
  45. www2.deloitte.com
  46. idc.com
  47. marketsandmarkets.com
  48. hhs.gov
  49. oecd.org
  50. nist.gov
  51. eur-lex.europa.eu
  52. gdpr.eu
  53. iso.org
  54. nature.com
  55. datadoghq.com
  56. dama.org
  57. ey.com
  58. brightlocal.com
  59. nngroup.com
  60. fortune.com
  61. venturebeat.com
  62. capterra.com
  63. campaignmonitor.com
  64. unido.org
  65. oracle.com
  66. bain.com
  67. datascience.com
  68. tomtom.com
  69. worldeconomicforum.org
  70. accenture.com
  71. worldbank.org
  72. cybersecurityventures.com
  73. unglobalcompact.org
  74. oecd.ai
  75. legalinstruments.oecd.org
  76. unesdoc.unesco.org