Re-engineering FMCG for the AI era

Every so often, a shift comes along that doesn’t announce itself loudly but ends up redefining the rules of the game. We’ve seen it with the rise of the internet, then email, then mobile. AI is that moment now—subtle in its arrival, but profound in its impact. 

For leaders, this is a cue to rethink the system. AI changes the speed and quality of decision-making, turning data into direction almost instantly. If D2C compressed the journey from idea to action, AI compresses the journey from information to intelligence. The future will not belong to the largest players, but to those who can combine the discipline of scale with the surgical precision of machine intelligence. 

AI as a Force Multiplier of Productivity 

As Leon C. Megginson, reflecting on Charles Darwin’s ideas, famously noted, “It is not the strongest of the species that survives, nor the most intelligent that survives. It is the one that is most adaptable to change.” 

In the modern FMCG landscape, this adaptability is no longer about reacting to trends, but about anticipating them through high-speed, high-quality decisions. AI serves as the ultimate catalyst for this evolutionary leap. 

The AI narrative often swings between hype and fear. But, for those of us in the consumer sector, its true value lies in a more grounded reality. It is the shift from broad assumptions to precise decisions, turning technology into real productivity and predictive insight. According to recent research by Goldman Sachs, Generative AI is expected to add $1.2-1.5 trillion to India’s GDP by 2030. 

AI is best understood not as a replacement for human creativity, but as an amplifier of it. Its influence spans the digital value chain—from content and design to deeper, more nuanced consumer insights that can help take the transactional off human hands and enable sharper, more transformational thinking. 

Take the traditional A/B testing of packaging design for instance. Historically, this was a linear, time-consuming process. Today, through AI-enabled tools, we can typically generate 30 distinct packaging options in a fraction of the time, allowing us to test and iterate at a speed that was previously unimaginable. This shift moves innovation from being episodic to being always-on. The same intelligence is now strengthening supply chain efficiency and enabling smarter selling by anticipating demand and aligning execution more closely with real consumer needs. 

The New Frontiers of Decision-making 

For consumer goods companies, AI is fundamentally altering the playbook across the value chain. In a market of micro-needs and immense linguistic diversity, it is sharply accelerating how consumer insight is gathered and acted upon. At the retail end, where last-mile reach has long been a blind spot, AI is bringing much-needed precision to assisted selling, using store-level data and past trends to guide frontline teams on what to push, when, and with which complementary products. At the same time, it is strengthening the backbone of operations, with predictive analytics helping anticipate maintenance, optimise production cycles, and build resilience into manufacturing systems. 

The Capabilities That Will Separate Leaders from Laggards 

According to Deloitte’s 2025 survey, 85% of organisations increased their investment in 2025, and 91% plan to increase it again this year. But capital alone is not a strategy. To unlock true value, CEOs must focus on three core pillars: 

The first is trust anchored in transparency. As consumers become more informed, they expect greater clarity on sourcing, quality, and values. Trust is earned through consistency, and AI can help ensure that quality frameworks remain robust even as we scale. 

The second is coherence across touchpoints. The consumer journey today resembles a braided river rather than a linear path. Influence may begin digitally, but reassurance is often sought offline. AI helps bridge this divide, aligning digital signals with in-store execution so that the brand experience feels continuous rather than fragmented. 

The third is agility in adaptation. The shift from predicting demand to responding to it with precision is the hallmark of a digital-native mindset. This requires moving from static planning cycles to systems that learn continuously, enabling faster course correction as consumer behaviour evolves. 

Responsible Exploration with AI is key 

The most enduring impact of the AI wave will not be found in the software we buy, but in the mindset we cultivate. Leadership in this new era requires a delicate balance. On one hand, leaders must embrace the speed and experimentation of digital-native brands. AI thrives in environments where teams are empowered to explore, where decisions are data-informed, and where progress is driven by learning rather than perfection. The leaders who succeed will be those who create space for responsible experimentation, encourage intelligent risk-taking, and treat innovation as a continuous practice rather than an occasional initiative. 

On the other hand, the anchor must be in the values of quality, trust, and purpose. In an AI-led world of infinite content and limited attention, trust will be the true differentiator. 

The responsibility of leadership is to ensure that as AI scales output, it doesn’t dilute standards. 

The CEO’s Mandate 

The future does not belong exclusively to the tech giants or the legacy incumbents. It belongs to those who can combine speed with discipline, and insight with scale, embracing what is new, while protecting what matters most. 

For today’s CEOs, the playbook is no longer a static set of rules but a dynamic algorithm. We must use AI to sharpen our reading of micro-needs, shorten our innovation cycles, and empower our people to make smarter decisions. The D2C wave taught us the importance of agility; the AI wave is now providing the tools to institutionalise that agility across the entire enterprise. AI is not a substitute for human judgment or creativity, it is an ally that amplifies both, freeing people to focus on higher-order thinking, empathy, and innovation. 

Technology may change, but principles do not. The goal is not to use AI for the sake of disruption, but to use it to serve the consumer better. If we stay close to consumer intent and move at the pace they demand, the strategic value of AI will move from the balance sheet to the hearts of our consumers. We are not just building smarter businesses; we are building more responsive and resonant ones. 

(The author is MD & CEO, Marico Limited. Views are personal.)