The Coming AI Tsunami in New Product Development – Are You Ready?

Dr. Robert Cooper

kHub Post Date: December 12, 2024

Read Time: 7 Minutes

AI’s Dramatic Results in NPD

Early adopters of AI for new product development (NPD) report dramatic performance results and are now accelerating their investment in AI [1],[2],[3]. Companies like Siemens, GE, Nestlé, and Pfizer have experienced reductions in development times of 50% or more, better optimization of product designs, and breakthrough discoveries [4]. While businesses have adopted AI for productivity improvements and cost reductions, the top benefit realized is increased innovation [5]. 

Despite the promise that AI offers, by early 2024, only 23% of firms globally had adopted AI for NPD [6]. More specifically, our 2024 AI adoption investigation found that this adoption rate for NPD applications was 31% in Germany but only 18% in the US [7]!

The AI Wave Is Coming Fast

The AI revolution in business and in NPD is approaching rapidly, and its impact is expected to be transformative. The First Industrial Revolution, characterized by steam power and mechanization, took approximately 85 years for widespread adoption. 

By contrast, the Information Age, starting about 1975, had a significantly shorter adoption period of just 28 years—see Figure 1. A plot of adoption windows versus revolution start dates yields a strong relationship and predicts a 22-year window for this current Industry 4.0 wave led by AI.

Figure 1. The duration of the Adoption Window for successive industrial revolutions—an ever-shorter but very predictable time period (figure created with help from Evan C. Thomas)

Recent data shows the adoption rate of AI for NPD moving from 13% in early 2023 to 23% in 2024—an increase of 10% in just one year 6! This new data plus, the predicted adoption window of 22 years, permits the construction of the adoption curve for AI in NPD in Figure 2, peaking around 2028. 

Our bell-shaped AI adoption curve in Figure 2 is based on Rogers’ famous “diffusion of innovation curve” [8]. The inflection point likely transpired in early 2022 [9]; and the 13% and 23% adoption rates uncovered for early 2023 and 2024 also help to anchor the curve.

Figure 2. The estimated adoption curve for AI for NPD, using the Adoption Window duration from Figure 1 plus other data points (dates are approximate)

Not only is the AI peak not far away, but the intensity of adoption (the slope of the AI adoption curve) in Figure 1 is much higher than for previous technology revolutions. The AI wave is coming on like a tsunami!

FOMO—Fear of Missing Out

The impact of AI on NPD will be significant. A McKinsey global study concluded that 27% of AI adopters for NPD saw a 6–10% increase in sales revenue from innovation due to AI [10]. A survey of 361 Chinese firms found that the use of Big Data Analytics and AI combined with strong IT capabilities yielded major impacts on NPD process efficiency—it accelerated time to market and improved product quality, enhancing customer satisfaction, loyalty, and business growth) [11]. 

The evidence mounts: A recent major financial economics analysis of a large sample of firms across many industries revealed “increased growth for AI-investing firms, along with increased product innovation” [12]. The study concludes that “AI facilitates product innovation and creates new business opportunities by enabling firms to learn better and faster from big data.” 

Figure 3. Improvement realized by using AI for NPD across 5 performance metrics 14

Finally, our study of AI adoption and its impact on NPD (recently reported in kHUB) reveals major performance impacts across five NPD KPIs—see Figure 3—averaging a 34% improvement [13]. Some AI applications, in particular, had pronounced impacts on accelerated development and enhanced decision-making: AI for automated product testing; AI for product design; and AI for prototyping (automatic translation of drawings into prototypes).

Three Elephants in the Room

1. Companies in the West are behind—what about your company? While hard evidence is lacking, the general opinion is that Asian companies have moved faster in adopting AI for business and NPD. An IBM survey report in late 2023 reveals that India leads the world with 59% of firms deploying AI, followed by China at 50% 3—see Table 1.

By comparison, Germany is at 43% and the US at 33%. These AI adoption rates for the entire business suggest that Indian and Chinese firms have a 37% and 32% adoption rate for AI for NPD respectively, somewhat higher than Germany at 31%, and much higher than the US at 18%

2. Many barriers to adopting AI for NPD do exist, slowing down adoption. Here are the most important barriers our research identified [14]:

• Low demonstrated business value to date.
• Lack of leadership commitment.
• Lack of trust by management at all levels.
• High infrastructure and adoption costs.
• Risks and ethical Issues, regulatory, IP protection, cybersecurity, and low success rates. 

These are not permanent roadblocks, however, so don’t let them stop the AI journey. Once the barriers are identified and understood, the mitigating strategies are evident—see [14] for example strategies.

3. AI acquisition projects have very high failure rates, estimated to be as high as 80%—almost double the failure rate of IT projects a decade ago [15]. AI projects fail for many reasons, most of them “dumb reasons”, according to a Havard Business Review article [16]. 

Failure reasons include a lack of understanding of users’ needs; technical issues (the product did not work); poor data quality; and having an AI-only project team [17]. These reasons parallel traditional failure reasons in NPD. As in the field of NPD, these pitfalls can be averted by implementing best practices such as VoB and VoP (voice of the business and process), better front-end homework, using an iterative approach (build-and-test, with multiple feedback loops), and fielding a cross-functional project team.

The perceived barriers to adoption can be overcome, and the reasons for AI project failure can be avoided, as leading and successful early adopters have demonstrated. But it takes time, thus the importance of starting soon. An effective AI acquisition and deployment process helps, since too many firms have moved ahead with AI with no clear strategy and no process or map to provide direction—and the results are predictable. 

One message is to begin with senior management commitment, complete with a vision and goals for AI deployment in the business and especially in NPD. Then, much as is done in NPD or technology development projects, adopt a rigorous process model to guide the execution of the AI projects, stage-by-stage from “building the business case” through to “pilots” and then “scale up”, as shown in the RAPID model in Figure 4 and featured in a recent kHUB article [18].

Figure 4. The RAPID technology acquisition and deployment process map for AI projects for NPD [18]

It’s Time to Begin Your AI Journey in NPD

The pace of AI adoption in NPD presents both opportunities and challenges for businesses. As a Forbes article warns, however, “The ramifications for non-action will be swift: You either jump on board, or prepare to eat the dust of the other AI first-movers” [19]. 

If your firm already has an AI Initiative and plan in place, so much the better. While some pundits recommend an organization-wide deployment of AI, others suggest taking it a step at a time. Product innovation is an ideal place to focus: The benefits of AI in NPD are numerous and now partially proven; many potential applications exist for AI in NPD; and ethical issues, such as job losses caused by AI, are minimal in the NPD area. 

One of the first action steps is to get ahead of the coming tsunami wave! Bring yourself and others up to speed on AI and its likely role in NPD in your business. Becoming AI literate may help convince senior management, many of whom lack understanding of this new technology [20].  

Now is the time for action. History has shown that those who have hesitated too long when technological revolutions occur do not fare well. And AI is the most significant innovation of our lifetime, perhaps of all time.

ABOUT THE AUTHOR

Dr. Robert Cooper, Professor Emeritus, McMaster University, Canada ISBM Distinguished Research Fellow at Penn State University A world expert in the field of management of new-product development and product innovation, Dr. Cooper has written 10 books on the topic and more than 170 articles. Bob is the creator of the globally-employed Stage-Gate (trademarked) process used to drive new products to market; a Fellow of the Product Development & Management Association; ISBM Distinguished Research Fellow at Penn State University. He is a noted consultant and advisor to Fortune 500 firms, and also gives public and in-house seminars globally.

LinkedIn: Dr. Robert G. Cooper
Website: www.bobcooper.ca

References

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