As driven as suppliers might be to use artificial intelligence, consumer and user reactions are more complicated. As always, the usefulness of the innovation has to be grasped to be embraced.
Perhaps one measure of product success is its ability to move from conception, research and development to production and then measurable sales success. Some researchers estimate that up to 95 percent of new products fail. Others dispute the notion, arguing that failure rates are closer to 60 percent.
Some of the variance is caused by how we define “success” and “failure.” Estimates can vary wildly based on whether we set low or moderate targets for sales volume or market share.
Study Title | Date | Publisher | Key Estimate |
"The Product Development Process: From Idea to Introduction" | 1986 | Cooper & Kleinschmidt | 40% of new products reach the market. |
"The Innovator's Dilemma" | 1997 | Clayton Christensen | High failure rates for disruptive technologies. |
"New Products: Management, Development, and Implementation" | 2003 | Griffin & Hauser | Failure rates vary significantly by industry. |
"The Myths About New Product Failure Rates" | 2017 | McKinsey Global Institute | 25-45% failure rate across industries. |
Why 95% of New Products Miss the Mark (and How Yours Can Avoid the Same Fate) | 2020 | MIT Professional Education | Reports that nearly 30,000 new products are introduced each year, with 95% of them failing, according to Clayton Christensen of Harvard Business School. MIT Professional Education |
Market View: New Product Success Rate Higher Than Most Believe | 2014 | Food Processing | Suggests that, contrary to popular belief, 66% of new products are successful, challenging the commonly cited 70-90% failure rate. |
20+ Product Launch Statistics You Should Know in 2024 | 2024 | G2 Learning Hub | Indicates that only 40% of developed products reach the market, and among those, only 60% generate revenue. |
How to Ensure Your Innovation Doesn't Fail After Launch | 2023 | Kantar | Finds that 16% of even the most successful first-year new products end up dead or dying by their fourth year. |
Success and Failure Rates of New Food and Non-Food Products Introduced on the Market | 2022 | ResearchGate | Argues that the common claim of 80–90% new product failure is a myth, stating that empirical studies do not confirm this belief. |
How Common Is New Product Failure | 2020 | Ehrenberg-Bass Institute | 40% failure rate on average; 41% failure rate for new SKUs two years post-launch |
Trends and Drivers of Success in NPD Practices | 2009 | Journal of Product Innovation Management | 41% failure rate |
Product Development Institute Study | 2010 | Stage-Gate International | 38% failure rate for top performers, 55% for bottom performers |
PDMA Best Practices Study | 2004 | Product Development & Management Association | 41% average failure rate across industries; 35% for healthcare, 45% for consumer goods |
Consumer Packaged Goods and Retail Products Study | 2024 | Business Dasher | 75% of products fail to earn $7.5 million in their first year |
Harvard Business School Study | Not specified | Harvard Business School | 95% of new products fail |
We will likely find that such product acceptance rates will affect AI use cases, features and apps as well. Not every AI use case will prove to provide so much value that “everyone” uses it.
But consumers might be more comfortable with generative AI, for example, than providers expect. Students appear to be widely using it for purposes of writing essays, for example. But most consumers arguably already experience--and “use”--various forms of AI more passively, as when editing photos, using speech-to-text or searching for products to buy.
Title | Date | Publisher | Key Findings |
"2024 Consumer Study: Revolutionize Retail with AI Everywhere" | 2024 | IBM | Explores how AI can enhance retail experiences, particularly in inventory management and demand forecasting. Highlights the necessity of real-time data integration for building intelligent supply chains that meet specific customer needs. |
"Consumer Perception and Use of Generative AI" | 2024 | Parks Associates | Quantifies consumer familiarity with and usage of generative AI applications. Indicates that these applications are often consumers' first direct interactions with AI, prompting new discussions about AI's capabilities and limitations. |
"Consumers Know More About AI Than Business Leaders Think" | 2024 | Boston Consulting Group | Reveals that consumers possess a higher level of knowledge and excitement about AI than business leaders anticipate. Suggests that businesses should not underestimate consumer awareness and should engage more transparently regarding AI implementations. |
"Consumers Open to AI in Marketing, But Data Privacy Matters" | 2024 | CDP.com | Reports that 81% of consumers are receptive to AI being used in marketing for personalized recommendations, provided that data privacy concerns are adequately addressed. Emphasizes the importance of balancing personalization with privacy. |
"What Drives the Acceptance of AI Technology?: The Role of Expectations and Experiences" | 2023 | arXiv.org | Investigates factors influencing AI acceptance, finding that both direct experiences with AI and prior ICT experiences significantly impact acceptance intentions. Highlights the importance of managing user experiences to foster realistic expectations of AI technology. |
"Consumer Acceptance of the Use of Artificial Intelligence in Online Shopping: Evidence from Hungary" | 2022 | arXiv.org | Examines consumer acceptance of AI in online retail, identifying trust and perceived usefulness as key factors. Suggests that enhancing content quality and automation can improve consumer attitudes toward AI-powered webshops. |
"AI Is Ruining Your Laptops Now" | 2024 | Lifewire | Discusses consumer skepticism towards AI features in laptops, noting that such additions are often seen as unnecessary and resource-consuming, potentially deterring purchases. Highlights a disconnect between tech companies' promotion of AI and actual consumer preferences. |
"Artificial Intelligence Marketing" | 2024 | Wikipedia | Describes how AI enables hyper-personalized advertisements by analyzing consumer data and patterns. Notes that while AI-driven personalization can enhance customer engagement, it also raises concerns about data privacy and the potential for intrusive marketing practices. |
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