February 2018 saw a surprising twist in the auto industry: Ford’s reputation hit the brakes with a 4.7% toll on its stock after it announced its plans to develop autonomous delivery vehicles. Fast forward to October, and it's a different story for rival General Motors (GM) – the auto giant cruised to success, its stock revving up by 4.6% after announcing the imminent launch of its self-driving cars.

The tale of two car giants with similar announcements concerning AI-based new product innovations (AI-NPIs) resulted in wildly dissimilar market reactions prompting the question: Under what circumstances and for what reasons do investors react positively to companies' AI-NPIs?

The AI Gold Rush

AI is revolutionising industries globally, from the fast-paced world of automotive to the critical realms of healthcare. Non-software companies are not mere spectators but also active participants, increasingly weaving AI into the fabric of their product offerings.

For example, Siemens Healthineers incorporated AI into its medical imaging and diagnostic devices to help interpret medical images (1) while agricultural equipment maker John Deere is employing AI to develop autonomous tractors, pesticide-spraying drones and weed scanners (2).

Danish shipping company A.P. Møller implemented AI solutions to predict demand, identify fraud, provide real-time supply chain monitoring, and automate warehouses (3).

A June 2023 McKinsey study concluded that generative AI has the potential to significantly boost global economic value, adding around USD 2.6-4.4 trillion annually across 63 analysed use cases—comparable to or exceeding the United Kingdom’s 2021 GDP (4).

The McKinsey report further noted that banking, high tech, and life sciences are poised to reap substantial benefits, as banking may gain around USD 200–USD 340 billion annually. Retail and consumer packaged goods could also see a significant annual increase of USD 400-660 billion from fully implemented use cases.

AI could also help monitor carbon emissions and could result in USD 1.3-2.6 trillion in revenue and savings by 2030, according to Boston Consulting Group. Recently, the UK government started a GBP 1.5 million project to explore AI's role in cutting the nation's carbon emissions (5).

Thus, it can be safely concluded that AI is not only reshaping diverse industries by integrating into non-software companies' products, but also stands to significantly elevate global economic value, marking an era of unprecedented technological and economic transformation.

However, the rising anticipation of a surge in business spending on AI solutions, projected to soar beyond USD 97.7 billion, casts a shadow over a conspicuous void - the scant academic research on the strategic implications of AI in spearheading new product innovations. This gap beckons a closer examination and a strategic response.

Decoding Investor Sentiment

In a first of its kind research, Manjunath Padigar, Faculty of Economics and Business, University of Groningen; Ljubomir Pupovac; UNSW Business School; Ashish Sinha, University of Technology Sydney; and Rajendra Srivastava, Novartis Professor of Marketing Strategy and Innovation, and Executive Director - Centre for Business Innovation (CBI), EFPM, Indian School of Business, analysed 341 AI-NPI announcements by firms listed in the S&P 500 over a decade (2009-2018) which showed the impact of marketing departments on the stock market reactions to these innovations.

While the average response to these announcements does not significantly deviate from zero, a clear pattern was observed. Positive investor responses were more likely when the announcements came from firms with strong marketing departments, with the effect being further influenced by the specific characteristics of the innovation.

The study advocates that a well-oiled marketing department is not just about brand promotion or customer engagement; it's about cultivating and safeguarding valuable market-based assets such as brands, partnerships, and customer relationships.

Discerning investors are now more attuned to a company’s marketing strengths and are studying the department’s prowess as a critical factor integral to the market’s reception of AI-NPIs.

The study hypothesised the impact of the marketing department in its capability to collect and interpret real-time data, anticipate, and meet customer needs swiftly, and provide personalised, emotionally engaging experiences.

Mastering AI Marketing

Marketing departments play a crucial role in managing privacy concerns, ensuring customer satisfaction, and strengthening brand relationships through effective use of AI technologies. They also identify and leverage opportunities for customers to delegate tasks to AI solutions, ensuring these technologies are both efficient and aligned with customer needs.

Prof Srivastava and team studied several areas where AI-NPIs intersect with customer engagement and market strategy.

AI-NPIs improve a company's “listening capability” to understand real-time customer data, helping create better strategies, with marketing playing a key role in utilising these insights and managing privacy issues.

For example, GM's "Marketplace" uses customer interactions to gather insights. In another AI-led real-world application, the cities of Seattle, Jakarta, Rio de Janeiro, and Hamburg are using real-time driving data from Google Maps to optimise traffic signals. They are looking to manage pollution by reducing emissions from idling vehicles. The project uses AI algorithms to analyse the data and has adjusted timings at 70 intersections, leading to up to 30 percent fewer stops and 10 percent lower emissions for 30 million cars monthly (6).

AI-NPIs, like Walmart's Polaris search engine, allow companies to “predict and respond to customer needs,” with marketing ensuring this technology boosts customer satisfaction and loyalty.

Similarly, packaging company Amcor is using AI, addressing challenges in forecasting and adapting to changing demand in food and healthcare packaging (7). The company is analysing years of data to predict changes in demand and supply, leading to more accurate stocking and pricing strategies. Amcor said the early results are promising, indicating a significant improvement in forecasting abilities, a key area where AI outperforms traditional methods.

AI-NPIs are also transforming customer-brand interactions by “providing social experiences,” with marketing leading the use of technologies like social robots to enhance these relationships.

For example, Royal Bank of Canada's AI-enabled assistant, NOMI, acts like a personal financial planner by giving customers customised budgets, tips on boosting savings and providing digital money management (8). Post-launch statistics show that NOMI users spent 93% more time on financial accounts and showed a 2% attrition rate compared to 8% for non-users.

Certain AI-NPIs allow companies to deploy the “delegation experience,” where customers rely on AI solutions for tasks.

A 2023 study showed that AI models that delegate tasks to humans based on each party's capabilities can enhance performance and satisfaction in human-AI teams (9). The 196 participants-study revealed that both task performance and satisfaction improved with AI delegation, regardless of whether the participants were aware of the AI's involvement, due to increased human self-efficacy, suggesting a promising avenue for AI in management roles.

Steering Through AI Integration

A robust marketing department is crucial for companies integrating AI, as it understands market trends, manages customer relationships, and uses AI for competitive advantage.

Prof Srivastava hypothesised that according to Resource Dependence Theory, the importance of marketing resources increases in later stages of innovation because of its low substitutability – this is seen especially in the development and commercialisation stages.

This increase is driven by the growing need to manage negative customer perceptions and market uncertainties associated with AI.

An October 2020 Marketing Science Institute study noted that consumers understand that data capture enables AI to offer personalised services, yet the lack of transparency in AI often leaves them feeling exploited (10). This sense of exploitation stems from a loss of personal control, leading to psychological impacts such as negative affect, demotivation, and helplessness.

The ISB study also noted that importance of marketing resources increases when firms integrate external assets into inhouse innovations, either through acquisition or strategic partnerships, versus assets developed inhouse. 

A June 2000 study published in the Journal of Management, citing other research, said that in the biotechnology industry the rate of new product development in a firm is influenced by the number of strategic alliances it maintains (11). Similarly, research indicated a positive correlation between sales growth and the adoption of R&D collaborative arrangements in new high-technology ventures. It was also observed that the stock market tends to respond more positively to announcements of technological alliances compared to marketing alliances.

As a result, a strong marketing department, capable of leveraging these resources effectively, becomes more influential and valued in scenarios involving external innovation routes. Prof Srivastava’s research noted that in the GM/Ford example, the companies’ 2017 annual proxy statements showed that GM’s top management team included 17% marketing executives, whereas Ford reported none at that management seniority.

Innovation complexity or the technical intricacies of a product, indicated by the number of components, interfaces, and subsystems in its architecture, elevates uncertainty and risks for both firms and customers, potentially hindering market adoption of the new product. From an external perspective, the complexity increases product-related uncertainty for customers and can disrupt market adoption.

For example, in 1964, AT&T introduced the Picturephone at the New York World Fair, a pioneering videophone technology (12). Despite favourable reviews and a noted desire from around half of the surveyed individuals for home use, the innovation failed to gain traction in the consumer market and later in the business sector, leading to its discontinuation by the mid-1970s. This example is not unique; a Synovate report indicated that 91% of variance in purchase behaviour is not explained by initial purchase intent, highlighting the discrepancy between consumer interest and actual product adoption across various sectors.

However, the same complexity positively moderates the impact of marketing department power on investor responses to AI-NPI announcements, according to Prof. Srivastava’s hypothesis.

Specifically, complex innovations like product-platform AI or autonomous AI require more significant marketing resources and competencies, increasing the marketing department's influence and necessity. As complexity introduces higher uncertainty and market adoption risks, a powerful marketing department becomes crucial in navigating these challenges and effectively leveraging brand assets and market orientation to facilitate successful innovation adoption.

Marketing's Impact on AI-NPI Success

The 341 AI-NPI announcements analysed by Prof Srivastava and his team revealed an increasing trend by non-software firms, especially between 2016 and 2018, with a significant 78% contribution from the manufacturing sector.

The power of the marketing department has a statistically significant positive effect on investor responses, thus supporting the team’s first hypothesis that a robust marketing department is the backbone to a successful AI-NPI launch.

This effect varies across innovation stages, with a stronger significance in the commercialisation stage, the findings showed. The route to innovation also impacts investor perception, as seen with ally and buy announcements, which show a more substantial positive effect compared to internal developments.

The adoption scope and AI type further interact with marketing power, with product-platform level adoption and autonomous AI showing positive effects, indicating nuanced investor expectations based on AI complexity and marketing influence.

These results are supported by robust checks confirming the stability of these findings across different conditions. Overall, the data underscores the varied and disparate nature of investor responses to AI-NPIs, shaped significantly by the marketing department's influence and the specific attributes of the AI innovation.

Marketing: The Bridge Between AI-NPI and Investors

For leaders of non-software enterprises diving into AI integration, Prof Srivastava and his team’s research sheds light on probable stock market reactions to AI innovation announcements.

Despite the substantial investment and strategic importance of AI adoption, merely announcing these innovations may not sufficiently inform or reassure investors, as evidenced by only just over half of such announcements in the study’s sample eliciting positive market responses. This underscored the need for managers to be strategic and circumspect in their communication, as misguided announcements can inadvertently devalue the firm.

For example, the Volkswagen Phaeton's launch is a classic example of how critical marketing alignment is to the success of a new product (13). Despite being an engineering marvel with exceptional luxury and performance capabilities, the Phaeton's market failure was largely attributed to a marketing misalignment. Bearing the Volkswagen badge, it contradicted the brand's image of affordability, failing to attract the high-end consumers it targeted. The Phaeton's design and features did not justify its luxury price tag in the eyes of consumers expecting exclusivity from a premium vehicle. Poor branding and market positioning overshadowed its technical achievements, leading to its commercial downfall.

Investor scepticism often revolved around uncertainties in a firm's capability to effectively implement and gain from innovative technologies. In such scenarios, investors preferred to check beyond the surface and scrutinise a company's underlying resources and assets critical for the successful commercialisation of innovations.

Predominantly intangible, these assets — like customer intelligence management, customer-connections, market-oriented culture — are embodied within the firm's marketing department. The strength and reputation of the marketing department, therefore, acted as a barometer of these intangible assets.

Firms should therefore strategically position their marketing department at the forefront of their innovation announcements, illustrating a commitment to harnessing and capitalizing on these assets, which could lead to substantial economic benefits. For example, firms with more influential marketing departments witness a predicted returns increase of about 0.72%, equating to an average USD 790 million boost in market capitalisation, Prof Srivastava noted.

However, it's not enough to recognise the value of a strong marketing department; managers must also be acutely aware of how the external market perceives their announcements of costly and risky innovations.

This involves a nuanced understanding of the additional context and information investors require to evaluate the firm's innovation trajectory. Several factors related to the innovation itself—like the timing of the announcement, the strategy employed to manage innovation assets (be it internal development, acquisition, or alliance), and the inherent complexity of the innovation—can significantly sway the relationship between the power of the marketing department and investor reactions.

Therefore, firms are encouraged to align their announcements with periods when the innovation is closer to market readiness, to strategically consider external partnerships or acquisitions for innovation assets, and to tackle more sophisticated innovations such as those involving platform-based or autonomous AI technologies. In doing so, firms not only enhance the perceived credibility and potential of their innovative endeavours but also position themselves favourably in the eyes of investors and the wider market.

1. https://www.siemens-healthineers.com/en-us/infrastructure-it/artificial-intelligence

2. https://www.deere.co.uk/en/agriculture/future-of-farming/

3. https://www.maersk.com/insights/integrated-logistics/cloud-and-artificial-intelligence-logistics

4. https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier#introduction

5. https://www.theguardian.com/technology/2023/feb/18/from-retail-to-transport-how-ai-is-changing-every-corner-of-the-economy

6. https://www.wired.com/story/googles-ai-traffic-lights-driving-annoying/

7. https://www.cio.com/article/651294/what-ai-already-does-well-in-supply-chain-management.html

8. https://hbr.org/2023/08/using-ai-to-build-stronger-connections-with-customers

9. https://publikationen.bibliothek.kit.edu/1000156992

10. https://journals.sagepub.com/doi/10.1177/0022242920953847

11. https://journals.sagepub.com/doi/10.1177/014920630002600302

12. https://doi.org/10.1016/j.ijresmar.2010.11.002

13. https://www.hotcars.com/why-vw-phaeton-flopped/