Innovation Acceleration: How Subsets of AI Can Inspire New Products and Strategies
CPGs are investing in AI, and product innovation is a major reason. Consider a recent EY report that said 76% of consumer goods brands are relying on AI for innovation, and nearly 50% said data, AI and analytics are a top priority over the next three years.
From large language models (LLMs) to generative AI to agentic AI, uses of the technology are evolving, and CPGs are seeking a variety of ways to put it to the test. Companies can leverage different elements of AI to develop new product ideas, experiment with packaging concepts, navigate compliance issues, and analyze pricing and demand strategies for new items.
But first, CPGs need to understand how the different subsets of AI work and what’s needed to properly feed them so that brands can accelerate innovation.
Where AI Inspires CPG Innovation
AI empowers brands to test new ideas without committing extensive resources into the development of a new product, package, formula and more. It saves brand teams both time and money. And now, with how AI is evolving, CPGs can leverage the technology end-to-end — uncovering strategic insights, generating copy and images, and autonomously executing defined tasks.
Essentially, various sources of AI can support innovation throughout the journey of a new product or innovation strategy:
Machine learning provides product analysis. As a company, such as a national soda brand, begins to identify gaps in its portfolio or where it can spark new sales, machine learning and analytical AI can review data prompts and help brand teams find areas to explore. The soda brand may uncover an opportunity for a prebiotic soda offering and leverage predictive analytics to find specific stores and regions to target. ML models can also study consumer sentiment on a product idea, looking at customer reviews and social media, and forecast demand before a brand gets too far into designing.
Generative AI creates concepts. If the soda company feels good about introducing a prebiotic soda, brand teams can leverage Gen AI capabilities to create digital ads featuring the innovative product, further supported by brand copy that builds compelling marketing around it. The company can test what a rollout might look like for the soda — and when the time comes to sell it, leverage Gen AI to produce attribute copy and online images of the soda in the hands of diverse models for a personalized experience.
Agentic AI accelerates speed to market. A new frontier of AI, agentic AI can orchestrate a new product’s journey, incorporating ML, Gen AI and advanced automation. In the case of the soda brand, if the business teams are aligned and have produced the prebiotic product, agentic AI can greatly accelerate that soda’s speed to market. AI agents can be ordered to analyze a market for prebiotic sodas. The agents also leverage reasoning and collaborate with other agents to identify a position in the market for the product. Furthermore, agents adapt to consumer behavior, supply chain or market shifts in real time, updating a rollout, suggesting pricing and promotions, and autonomously rewriting copy as needed.
Of course, even after a product launches, AI can help monitor sales and recommend adjustments to optimize sales and production. Beyond new items, the same principles apply for business teams to innovate with new packaging sizes or styles and identify items that might not perform so well in the market.
What Brands Need to Power AI Innovation
To leverage a full complement of AI solutions, brands must have some technical and cultural requirements in place. For instance, for AI to feed brands insights and generate product attribution for e-commerce, it’s mandatory for an organization to harness and streamline data sources into one centralized location.
Brands want data cleaned and enriched as it flows to one single source of truth, where teams across the organization can access it and have AI work with them on innovative ideas. Companies also need a flexible IT architecture to manage the data and develop a company culture around AI.
CTOs need to invest in modular infrastructure but also build internal teams with multi-disciplinary expertise to manage the technology and AI. Specifically with the power of agentic AI, a company needs to rethink workflows and how AI orchestrates collaboration between business teams, systems and AI agents.
How Brands Will Grow With AI
Understandably, to unlock innovation with AI, consumer goods brands need technical pieces and expertise in place. Enriched data is the fuel to supply brand teams with the insights they need for new ideas — powerful and supported AI agents and Gen AI capabilities can help deliver.
When done right, diverse AI capabilities can help brands fill new product gaps, get items to market faster and adjust in real time to optimize performance. The possibilities are endless, but AI doesn’t just highlight them, it helps brands act on the right ones.
Lori Schafer serves as CEO of Digital Wave Technology, a software solutions company that transforms retail, healthcare and consumer goods business processes through AI, workflow, and automation. Schafer is a senior software executive and entrepreneur with more than 30 years of experience in analytics (predictive, AI, generative AI), e-commerce, consumer products branding, and retail merchandising and marketing.
Lori Schafer was recently recognized within CGT’s inaugural class of Data Leadership Award Winners. Read her profile here.