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Artificial intelligence promises unmatched productivity gains, improved operational efficiency, real-time consumer insights, hyper-personalized experiences, and large-scale predictive decision-making capabilities that can revolutionize the consumer products industry. The road to successful AI adoption, however, is paved with obstacles for many organizations, ranging from algorithmic biases and resource limitations to data privacy issues and the possibility of job displacement. 

Consumer products companies need to take a strategic stance, establish a strong foundation, and create a clear roadmap that tackles these issues head-on if they want to realize AI's full potential and outcompete in the market.


The economic imperative: Leveraging AI drives productivity 

AI adoption makes a lot of economic sense. The Stanford Institute for Human-Centered Artificial Intelligence's AI Index 2024 Annual Report estimates that by 2030, productivity gains and broad industry adoption of AI could boost global GDP by an astounding $15–20 trillion. With applications like customized e-commerce and efficient supply chains, the retail and consumer products industries alone stand to gain between $2–3 trillion in value. Businesses that have successfully scaled AI implementations include Procter & Gamble and Unilever, which have reported remarkable productivity gains of 20–35% across key functions like supply chain forecasting, marketing personalization, and customer service automation.

But how do you shift from AI experimentation to AI at scale?

Organizations that successfully transition from scattered pilots to enterprise-scale AI share five key traits:
 

Overcoming AI adoption obstacles

Implementing AI at scale is not without its challenges. Data silos, skill gaps, and legacy processes and systems still plague many consumer products companies. These practical recommendations can help you get started on or accelerate your AI journey: 

  • Self-assess or seek outside experts to determine your organization’s biggest areas of opportunity and gaps (e.g., skills, systems, data, budget) as well as the top areas to solve for to become AI-ready. 
  • Develop a clear roadmap for AI implementation, including specific steps and dependencies, timing to pilot AI, and enterprise-wide rollout initiatives.
  • Establish a framework for measuring the ROI of AI initiatives by setting realistic expectations for the timeline and resources required to achieve your desired outcomes.
  • Encourage a culture of AI adoption and focus on upskilling existing employees to support AI initiatives.
  • Address ethical considerations surrounding AI, such as data privacy, transparency, and fairness, and ensure responsible AI deployment.
     

Seizing the AI opportunity

The time to act is now. By preparing your company’s data, building the necessary infrastructure, and establishing robust governance procedures, consumer products companies can leverage AI to gain a competitive edge in today’s dynamic and uncertain economy. To support this journey, consider:

  • Exploring and learning from industry-specific case studies (such as these AlixPartners examples with leading consumer products and food services companies) that showcase successful AI implementations and results.
  • Utilizing AI readiness assessment tools to evaluate your organization's current state and identify areas of opportunity.
  • Participating in workshops and industry forums to learn from experts and peers.
  • Partnering with experienced AI vendors and solution providers that specialize in the consumer products industry.

The AI revolution is here—will your organization be at the forefront? Our experts can help—reach out to learn more.
 

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