Consumer AI: Start, Evolve, Succeed

Over the last 18 months, the buzz around generative AI and its potential opportunities for the consumer industry has its leaders both excited and anxious. While it’s clear that AI presents a massive opportunity for growth and efficiency, it will only be realized when organizations have the right talent in-house to implement and leverage AI solutions.

In response, we gathered insights from our AI Leadership Labs¹ roundtable series, our fifth annual CEO Perspectives on Talent series², and our Global Leadership Monitor³ to help consumer leaders understand the industry’s overall progress, share what best-in-class organizations are doing to embrace AI, and RRA’s comprehensive view on leading organizations through this transformation.

What are consumer organizations doing about AI?

Consumer companies have been using AI precursors like machine learning for many years. As with most technology innovations, they started implementing local pilots before integrating AI tools throughout their value chain to enhance productivity and create new revenue streams.

For example, Carlsberg started by leveraging AI to improve product quality and drive sustainability. It uses AI-powered sensors to analyze beer samples during brewing, ensuring consistent quality and enabling flavor innovation. Additionally, AI-driven analytics support Carlsberg's sustainability efforts by optimizing water and energy usage. AI plays a crucial role in analyzing consumer data, allowing the company to tailor marketing strategies, develop new products, and enhance customer engagement, thereby driving growth.⁴

To set up the right infrastructure for AI, many consumer organizations are also prioritizing data and analytics, creating internal teams dedicated to e-commerce, metaverse, innovation and customer experience, which leverage data from internal sources like CRM, credit card, and digital transactions when available.

For example, L'Oréal is leveraging AI with tools like virtual try-ons, skin diagnostics, and personalized beauty recommendations to its customers.⁵ Additionally, AI-powered chatbots on L'Oréal's e-commerce platforms assist customers, improving the overall shopping experience.⁶

Another example comes from Hugo Boss, which integrated a “Lead in Digital” pillar intended to create 24/7 premium brand experiences, furthering their growth strategy. In 2022, they introduced an AI-powered chatbot, which is currently running in 12 countries and 6 languages. The chatbot delivers immediate and precise responses to frequently asked questions about products, orders, tracking, and returns.

Generative AI gives e-Commerce providers the possibility to edit responses from multiple data sources in real-time and give customers recommendations in a natural language. Thanks to this technology, the retailer can advise buyers better with their purchase decisions by suggesting products that match their preferences and interests.⁷

What’s keeping consumer leaders up at night?

According to participants from our AI Leadership Labs, AI implementation also represents a complete business model transformation for consumer organizations with significant implications for talent, culture, and organizational structure. At our AI CEO roundtables, we heard consumer leaders express AI implementation challenges around four key areas:

• Identifying value
• Unprecedented pace of transformation
• Managing change and culture evolution
• New leadership requirements

Identifying value

To fully unlock the potential of AI, consumer companies must first identify the areas where they can deliver the most immediate value. Key opportunities for AI-driven value creation include product ideation, pricing optimization, and trade spend analysis. Effective AI implementation involves identifying high-impact key use cases, launching pilot projects, and then scaling those that demonstrate success.

Retailers including LVMH, Inditex, C&A, and H&M Group are employing AI to enhance customer experience, deploying AI-driven recommendation systems that offer personalized shopping. They are also leveraging AI for cost-savings operations, including supply chain optimization, enhancing inventory management, and reducing waste through data-driven demand predictions across their brands. Additionally, they use AI to analyze in-store data and customer behavior to improve store layouts, forecast trends, and generate design insights.

Unprecedented pace of transformation

From our Al Labs roundtables, we heard consumer leaders say that, when it comes to AI, they should not question whether they have time to learn and transform, as they have no choice. The speed and rate of change is moving too fast. Instead, the they felt that the question should be: "What steps can we take today to ensure we are preparing our organization and the people within it for the challenges of tomorrow?"

Per our Monitor, the majority of consumer leaders are making moves around GenAI, but few have actually implemented the technologies extensively. Two-thirds (66%) have taken a step towards embracing GenAI in their function or team’s workflow. Conversely, 34% have taken no action (Figure 1).

Within the 66% of leaders who have taken action, 32% are in the initial investigation phase, making this the most common stage globally. A similar proportion of leaders (29%) are in the developing (7%) and piloting (22%) phases. Only 6% of leaders are using GenAI in their day-to-day workflows (Figure 1).

Figure 1: GenAI implementation progress in consumer organizations

_{Source: Russell Reynolds Associates´ H1 2024 Global Leadership Monitor, n=200 Consumer CEO, C-level, next generation leaders, and board directors.}

In terms of implementation progress, the consumer industry is in the back half of the pack—slightly ahead of the industrial industry, slightly behind its financial services and healthcare counterparts, yet farther behind the technology industry (Figure 2).

Figure 2: Leaders´ response to development actions in Gen AI (H1 2024)

Development of AI by industry
% of leaders who have implemented or piloted generative AI

_{Source: Russell Reynolds Associates´ H1 2024 Global Leadership Monitor, n=1, 153 CEO, C-level, next generation leaders, and board directors.}

The data highlights that—while the majority of leaders have taken an least an initial step towards implementing AI—leaders across industries are simultaneously weighing the long-term impacts of their organization’s AI decisions against the immense pressure to move with speed.

Managing change and culture evolution

Transforming to keep pace with the AI revolution requires a culture of innovation, with a try-fast/fail-fast mentality. But getting to that point will not be easy. As one CEO in our Lab sessions stated: “Change is 30% technology, 70% culture and transformation.”

Leadership Labs participants noted that leaders should prepare for an element of “shame”—both from employees who do not yet understand the technology or opportunities, as well as from those hiding their AI skills. Trust will also be key. Without trust, employees won’t support the transformation goals, as they may fear they’re training their AI replacements.

Finally, this change will require constant upskilling and reskilling around AI. The continually accelerating pace of change will mean that employees will have to learn more quickly and frequently than ever before.

New leadership requirements

Management must understand AI's applications, opportunities, and risks while ensuring strategic alignment and data security. Yet while 78% of consumer leaders globally agree that “a strong understanding of generative AI will be a required skill for future C-suite members,” our Monitor finds that only 34% are confident in their own ability to implement AI in their organizations today.

The leadership profile and remit across all functions, at every level, will soon start to look very different. The speed with which decisions need to be made will require leaders to demonstrate change management, systems thinking, adaptability, rapid learning, and resilience. Additionally, the leadership team must continue to build an enterprise mindset, collaborating and supporting each other’s goals, focusing on the success of the organization and its mission, rather than of the individual.

How can consumer leaders effectively tackle what’s next? A systems view for AI leadership transformation

Through learnings from our AI Leadership Labs series, we have created RRA Systems View on AI Leadership Transformation (Figure 4).

While many past technology advancements required time and tech experts to implement and integrate across complex organizations, much of the GenAI opportunity is already within reach. The most powerful approach to AI transformation equips the entire organization with the tools and leadership to drive change across the business at every level.

1. Re-imagine the business

Upgrading the edges of the business will not be enough to meet the AI transformation—organizations need to fully re-imagine themselves. There are several examples of businesses which only upgraded parts of themselves and failed to transform. Take Blockbuster, a famed loser of technology change. Blockbuster did not adapt to the shift towards online streaming and digital rentals and suffered for it. Conversely, Netflix transitioned from a DVD rental service to a streaming giant by investing in data analytics to personalize recommendations.

We advise leaders to scenario plan for how AI connects to their broader business transformation, and use that to imagine an AI-enabled future over a long term horizon with radical product innovation.

2. CEO enablement

CEOs looking to get smart on AI have created a “cabinet” of AI advisors around them, either informally or via a formal advisory board. Members of this AI advisory cabinet may include transformation experts (AI experts, general managers, and consultants); those who bring technical or visionary experience (entrepreneurs, technologists, and academics); or even strategists specializing in acquisition. This makes it easier to incorporate AI into strategic and operating discussions across the board and leadership team.

A great example of a successful AI cabinet occurred at the GenAI powerhouse Microsoft, where CEO Satya Nadella has surrounded himself with AI experts, partnering with OpenAI and proselytizing a “learn-it-all,” (rather than “know-it-all”) culture.⁸ Another is within Amazon’s consumer business, where leaders established an internal AI council composed of senior leaders from various departments, including engineering, data science, and product management, which guides the company’s AI strategy, ensuring alignment across business units and driving innovation.

3. C-suite redesign

Core to AI enablement is an ‘enterprise mindset’ across the C-suite, in which leaders focus on the success of the team and the company, rather than on their specific function’s prowess.

First, leaders must design a future-facing success profile for every function and role. Then, assess current capabilities against the leadership needs of the future. Following this, encourage each function to support other functions in their missions, and underpin them all with technology/digital capabilities.

Consumer organizations are already redesigning their C-suites. Unilever created a new chief data officer (CDO) position to accelerate its digital transformation and AI adoption. This leader is tasked with overseeing the company’s digital strategy, harnessing data and AI to drive innovation and efficiency across its brands. The CDO works alongside the chief information officer and chief marketing officer to integrate AI into marketing, supply chain management, and product development.⁹

4. Board composition

The last decade has seen a dramatic increase in technical board directors, from CEO and GM technology talent, to strategy and M&A advisors, and now increasingly to technology officer talent. Organizations have appointed AI advisors with relevant industry context, while also accelerating upskilling for existing board members around AI. Boards should aim for strategic and technological balance, not over-indexing on tech visionaries who can’t also bring business experience.

There are countless good examples of successful organizations appointing strong digital board talent, often not stopping at one or two technology experts. Walmart, for example, has appointed board members with experience from PayPal, AT&T, Univision Communications, Nextdoor Holdings, and Google.

5. AI and data enablement

Good data is the bedrock of functional AI. But currently, many organizations’ data are disconnected, with functions and business units picking from it as needed. For AI to be effective, organizations need a central data store, with silos being left to the last possible moment of analysis.

Consumer organizations need to upgrade and centralize their data infrastructure, while also elevating their data governance. Then, they need to innovate around use cases, which thereafter will maximize a partnership with AI platform organizations to dramatically increase capability, but most importantly, scale.

6. Rethink culture and approach to learning

Develop a culture of innovation, free from shame or a fear of failure. This can be achieved by giving all employees the tools needed to get to a basic understanding of AI and the opportunities it provides. Find champions of AI in the organization and make them more visible. These can include senior leadership, who themselves must demonstrate commitment to AI by leveraging tools at the top.

A successful AI and digital transformation strategy must be holistic, integrating technology with cultural and learning initiatives to build a resilient and innovative workforce. In our Lab series, we spoke to several leaders who had instituted mandatory AI training across the organization, from the board of directors down to the shop floor. For example, consumer giant Nike created “Innovation Labs,” a program which encourages collaboration and experimentation not only with new materials, performance, and designs, but also technologies. The Nike Digital Innovation Lab is focused on enhancing Nike’s digital ecosystem via digital experiences, app development, digital fitness solutions, and advanced customer engagement technologies.

Looking towards an AI-enabled future in consumer

During our Leadership Labs and Consumer Perspectives on Talent series, CPG, retail and leisure & hospitality CEOs shared their thoughts about the overwhelming scale of the AI challenge. And with so many other pressing topics competing for air-time, it’s easy to see how decision paralysis can arise. The reality is that leaders need to start somewhere, let AI initiatives evolve over time, and reserve the right to change as they learn.

Consumer organizations are tackling the AI transformation incrementally, starting by supporting the CEO in leading the AI conversation, then integrating AI into all strategic discussions. This is then supplemented by bringing in innovation-savvy leadership who can inspire and motivate by publicly championing and showcasing their success.

While the battle for talent is real, one fact bears repeating: consumer companies have been using AI precursors for many years. What has changed is the complexity of the new models and the speed of decision making. The ability to embrace this transformation will determine which organizations will succeed.

Authors

Fawad Bajwa leads Russell Reynolds Associates’ AI, Analytics & Data Practice globally. He is based in Toronto and New York. 
Leah Christianson is a member of Russell Reynolds Associates’ Center for Leadership Insight. She is based in San Francisco.
George Head leads Russell Reynolds Associates’ Technology Knowledge team. He is based in London.
David Torres leads Russell Reynolds Associates’ Consumer Knowledge team. He is based in London.

Footnotes

_{¹ AI Leadership Labs is Russell Reynolds Associates’ dedicated innovation hub, where we explore the new frontiers of leadership through advanced analytics, cutting-edge research, and real-world thinking from leading visionaries.
² The Annual Consumer CEO Perspectives Review is Russell Reynolds Associates’ flagship annual analysis of the challenges and opportunities across sectors within the Consumer industry and what this means for future leadership.
³ The Global Leadership Monitor is Russell Reynolds Associates’ bi-annual survey of global business leaders, tracking key threats to organizational health and leaders’ preparedness to face them.
⁴ “Carlsberg saves time, improves employee experience, boosts efficiency and security” , Microsoft Customer Stories, June 2024.
⁵ L’Oreal Research and Innovation, L'Oréal and ModiFace: An Artificial Intelligence-powered Skin Diagnostic, loreal.com, 2020
⁶ Consumer Electronics Show (CES) & L’Oreal Research and Innovation L’Oréal at CES 2024, loreal.com, January 2024
⁷ Bert Rösch, Serie: Chat GPT in der Kundenbetreuung: Hugo Boss, "Chatbots bieten permanent Raum für Verbesserungen", TextilWirtschaft, September 2024; (behind firewall).
⁸ Chloe Berger, "Microsoft CEO says the key to success is continuing to learn and change", Fortune Magazine, May 2024.
⁹ Simge Şenses, “Q&A: Unilever’s data, digital and AI journey; Chief Data Officer, Andy Hill, on AI, data, talent and success”, MediaCat Magazine, 6th February 2024.}