Adapting the Innovation Formula
If the speed, growth and productivity benefits are more readily apparent through the use of AI, there are also benefits to the innovation team and the experimentative culture that should permeate the corporate organization. In essence, it moves companies from reactive to proactive, to a more precise focus on customer-centric development, all while empowering smaller, cross-functional teams.
In BCG’s “The Role of AI in Reshaping Product Innovation,” the consulting firm points out that while many companies are justifying the use of AI for cost-cutting or efficiency tactics, it is potentially still untapped when it comes to innovation for consumer packaged goods brands.
The timing may be right for CPG to tap into AI for product innovation. Currently, BCG notes that, “Growth is hard to come by for CPG firms in many major markets at present: Inflationary pressures are limiting the scope for premiumization, and more agile challenger brands continue to outpace larger competitors.”
This is where insights for innovation come into play. AI can quickly spot trends and identify future buyer signals, with a pulse on what might arrive next in terms of new products and hot market trends. “The real opportunity is using AI to unearth meaningful insights about customer behavior and preferences from multiple sources of unstructured data—and then structuring those in a meaningful way, such as in line with consumer segments,” observes BCG.
Using AI can accelerate the innovation cycle by up to 30%, the consultant firm suggests. Those tactics can include:
Identifying market trends by distilling multiple sources of unstructured data at speed.
Using computer simulations to quickly and cheaply test virtual product iterations.
Helping formulate, reformulate, and then recommend optimal formulae for ingredient combinations.
Writing product descriptions, and regulatory documents where needed.
Generating marketing materials and automated content for launch packs.
Testing performance and providing real-time feedback from multiple sources to aid with post-launch modifications and iteration.
Igniting Innovation with AI
During FEI25, the session “Igniting Always-On AI Innovation” was presented by Lauren Collier, Chief Experience Officer from Finch Brands, and John Ferreira, Chief Insights Officer, Finch Brands. The session featured “Charlie,” an AI-powered innovation engine that transforms traditional innovation processes into an always-on, adaptive system that leverages both proprietary and public data.
The speakers opened the session by emphasizing the need for innovation adaptation in today’s rapidly changing business environment. They highlighted that customer needs are changing up to 50 times faster than before, with no industry being immune to this acceleration. Speed is no longer a disadvantage to innovation but a necessity, regardless of company size.
The speakers outlined five principles for innovation adaptation, emphasizing the need for cumulative knowledge, outside-in thinking, cross-functional collaboration, holistic product experiences, and AI-human partnerships. Charlie demonstrates how AI can accelerate innovation by synthesizing insights, detecting trends, generating concepts, and creating testable assets in minutes rather than months.
Expanding the Scope of Innovation
The article from BCG and the session from FEI25 both emphasize the always-on nature of AI as a way to help fuel the innovation team’s initiatives. The collective knowledge has always been there in terms of the team and the history of the company’s investments into innovation and research. Now with AI, the scope is broadening, from one-time projects to building on past successes and failures to cross-functional innovation and a more holistic product experience. Both knowledge and tools are evolving from human-only approaches to human-plus-AI partnerships that catalyze innovation adaptation.
BCG recommends several steps to hone the long-term vision of leveraging AI for product innovation:
Target transformation rather than point solutions. Success requires an end-to-end overhaul of processes along the value chain rather than focusing on a series of specialized tools for specific use cases. While each point solution may save some time, they will not collectively deliver a broad reshaping of the innovation cycle. The starting point for such a transformation is assessing where most time and effort is expended and mapping that against the best AI tools to accelerate the work.
Prioritize people. The most challenging work is often not in identifying and developing the right technology, but rather in upskilling people and the way they work. Integrating AI into the innovation cycle will change the type of tasks workers undertake, the talent companies need, and the ways teams interact. As such, most effort should be directed toward people-centered strategies. BCG suggests that 10% of a company’s efforts should be focused on algorithms, 20% on technology and data, and 70% on people and processes.
Look one step ahead. While focusing on the potential of AI to reshape functions in the here and now, it’s also important to be mindful about future AI capabilities. This includes the potential of AI to invent breakthrough concepts. It’s also important to think about potential uses of GenAI to enhance the broader product offering including services that increase personalization and improve the customer experience.
