Revenue growth management for consumer brands: 4 predictions for the AI era

<h2><span class="h6">Revenue growth management is evolving from a periodic planning discipline into a continuous commercial capability. Here’s what that means for consumer brands.</span></h2>

<p>Traditional revenue growth management (RGM) was built for a bygone era. Annual planning cycles, periodic elasticity models and spreadsheet-based simulations were effective when markets moved predictably. Today, prices, competitors and consumer behavior can shift rapidly, demanding a more dynamic approach to commercial decision-making.</p> <p>As a result, revenue growth management must evolve from a periodic planning discipline into a continuous commercial capability. That shift requires a new generation of technology that can connect pricing, promotions and assortment decisions into a single, dynamic workflow.</p> <p>While research suggests this transformation is still in process—only <a></a><a rel="noopener noreferrer" href="https://www.kearney.com/documents/291362523/310485598/Revenue-Growth-Management-Brief-2025-NEW-PDF.pdf/7b9dc864-6f45-5616-3f8b-ee958e2a89a1?t=1762972032000" target="_blank">one in 10 organizations</a>&nbsp;report systematic and scaled rollouts across markets, and just <a></a><a rel="noopener noreferrer" href="https://www.kearney.com/documents/291362523/310485598/Revenue-Growth-Management-Brief-2025-NEW-PDF.pdf/7b9dc864-6f45-5616-3f8b-ee958e2a89a1?t=1762972032000" target="_blank">one-third of RGM leads</a>&nbsp;feel equipped to perform at full potential—AI is poised to play a defining role in the industry’s future.</p> <p>The real question now is what will happen next?</p> <p>In an industry that’s always changing, guided by technology that becomes more powerful and intelligent by the day, what does the future hold, and how can brands get ahead of it? Here are four predictions about where I think RGM is heading and what it means for consumer brands.</p> <h4><b><span class="h5"><span class="text-bold-italic">1.&nbsp;</span> &nbsp; Agentic AI will reshape revenue growth management for CPG, but full autonomy is not the goal.</span></b></h4> <p>Agentic AI is the next stage of pricing and promotion maturity—and in many industries, it’s already here. Amazon, Uber and countless travel and hospitality brands have all rolled out AI-powered systems that both recommend and execute dynamic pricing decisions.</p> <p>And yet, while that autonomous capability exists today, it may not be right for consumer brands. Unlike e-commerce or airlines, CPG manufacturers operate within complex wholesaler retailer ecosystems where pricing decisions affect trade agreements, channel strategy and commercial relationships. Fully autonomous or highly dynamic pricing could disrupt those relationships and create channel conflict.</p> <p>For consumer brands, the near-term opportunity is not autonomous pricing. It is AI-assisted decisioning: surfacing recommendations, trade-offs and likely outcomes so commercial leaders can act faster and with greater confidence.<br> </p> <p>This is why the most compelling CPG use cases are emerging around decision support and retailer collaboration, not unchecked automation. <a></a><a rel="noopener noreferrer" href="https://consumergoods.com/5-consumer-goods-companies-harnessing-next-gen-rgm" target="_blank">Kraft Heinz</a>&nbsp;illustrates this approach in practice. The company implemented AI and real-time analytics to optimize pricing, promotions and assortment, driving a 5% compound annual improvement in promotional ROI since 2019.</p> <p>More recently, the brand expanded its use of shared data with retail partners such as Dollar General to tailor product assortments and replenishment at the store level. Rather than allowing AI to make pricing decisions autonomously, the technology provides recommendations that strengthen collaboration with retail partners while leaving commercial decisions in human hands.</p> <h4><span class="h5"><span class="text-bold-italic">2.&nbsp;</span> &nbsp;&nbsp;<b>Trusted data will determine how much value AI can create.</b></span></h4> <p>AI capabilities have matured to the point where they can support continuous commercial decision-making at scale. The struggle for many brands isn’t the technology but the quality and accessibility of enterprise data.</p> <p>Many organizations still rely on fragmented data spread across multiple systems, with commercial teams stitching together Excel extracts rather than working from a unified source of truth. Until data is harmonized and connected, even the most advanced AI will fall short of its potential.</p> <p>In our work with one global consumer goods manufacturer, our team helped the company establish a unified trade promotion management (TPM) data foundation to improve data quality, consistency and processing across commercial workflows. That common data layer enabled more accurate planning, budgeting, order management and performance measurement, <a rel="noopener noreferrer" href="/content/dam/connectedassets/cognizant-global-marketing/marketing-channels/cognizant-dotcom/en_us/field-marketing/documents/cmp-008037/TPM-AI-powered-RGM-frameworks.pdf" target="_blank">reducing data processing time by 70%</a> and increasing overall operational efficiency by the same amount.</p> <p>But building that unified data foundation isn't just about integration—it also requires trust. Commercial teams need confidence that AI-generated recommendations and KPIs are accurate. When AI outputs differ from the numbers that people are accustomed to seeing in spreadsheets or legacy reports, they often question the tool rather than the underlying data. Establishing trust in the data and metrics is therefore a prerequisite for AI adoption and, by extension, value creation.</p> <h4><b><span class="h5"><span class="text-bold-italic">3.</span>&nbsp; &nbsp; AI won’t replace commercial teams, but it will change the way they work.</span></b></h4> <p>The biggest challenge in revenue growth management has never been lack of data—it's speed of insights and action. Many commercial teams struggle to align across functions, often working toward different KPIs while trying to navigate an overwhelming volume of reports and dashboards.</p> <p>This is where generative and agentic AI will have the greatest impact. Rather than asking commercial teams to search for answers for days and weeks, agentic AI will identify emerging issues, explain what's driving them and recommend actions through a more natural, conversational experience. They can also help streamline KPIs to ensure different teams are working toward the same goals.</p> <p>For example, rather than waiting for a monthly performance review to identify declining sales, agentic AI can detect emerging trends, determine whether pricing, promotions or assortment are the likely drivers, and notify the relevant commercial teams with recommended actions. By giving every function access to the same insights and performance metrics, AI also helps align teams around common KPIs, enabling faster, more coordinated decisions that connect to business priorities.</p> <h4><b><span class="h5"><span class="text-bold-italic">4.&nbsp;</span> &nbsp; Mid-market brands may be sitting on a big opportunity.</span></b></h4> <p>While many large CPG companies have already embedded AI into their revenue growth management capabilities, substantial untapped value remains within the mid-market segment.</p> <p>Mid-sized brands often face fewer legacy system and process constraints, enabling them to adopt AI-powered planning, pricing, promotion and insights capabilities more rapidly than larger competitors. This agility creates a unique opportunity to accelerate RGM maturity, improve commercial decision-making and deliver measurable revenue and margin growth.</p> <p>Historically, building sophisticated revenue growth management capabilities required years of investment in data, analytics and specialist teams. Today, AI is lowering that barrier. Rather than progressing incrementally through multiple stages of maturity, mid-sized organizations can leapfrog traditional development cycles by embedding AI into decision-making from the outset.</p> <p>For organizations that have yet to fully modernize their RGM capabilities, this represents a rare opportunity to catch up and potentially close the gap with much larger competitors.</p> <h4><b><span class="h4">Four actions to take for AI-enabled revenue growth management</span></b></h4> <p>The next era of RGM will reward brands that can sense market changes earlier, align teams faster and translate AI-driven insights into trusted commercial action. To prepare for the next stage of revenue growth management maturity, brands should:</p> <ol> <li><b>Use AI to accelerate human decision-making.</b> Focus on AI that augments commercial teams with faster analysis, better recommendations and coordinated workflows, while keeping humans accountable for decisions.<br> <br> </li> <li><b>Build trust in the data foundation.</b> Prioritize harmonizing commercial data across pricing, promotions, assortment and finance to power AI tools and ensure trust in system recommendations.<br> <br> </li> <li><b>Modernize workflows to match new capabilities.</b> Move beyond dashboards and manual reporting toward AI-powered workflows that surface insights proactively and support faster cross-functional decision making.<br> <br> </li> <li><b>Assess your RGM maturity and close the biggest gaps first.</b> Organizations still relying on spreadsheets and manual processes have the greatest opportunity to accelerate commercial performance by adopting AI-enabled planning capabilities.</li> </ol> <h3><b><span class="h4">Get ready to lead the next stage of RGM</span></b></h3> <p>RGM is almost unrecognizable from 20 or 30 years ago, and the next decade may bring an even more profound transformation with agentic AI.</p> <p>As AI reshapes not just the tools organizations use but also how commercial decisions are made, the brands that succeed won't be those that simply adapt to change. They'll be the ones that anticipate it—building the data, capabilities and ways of working that keep them one step ahead of today’s predictions.</p> <p><i>Is your RGM strategy ready for the AI era? Cognizant can help you build the trusted data foundations, AI capabilities and commercial operating models needed to unlock the next generation of RGM. Contact our authors to start the conversation or visit our </i><a rel="noopener noreferrer" href="https://www.cognizant.com/us/en/cmp/revenue-growth-management-trade-promotions" target="_blank"><i>Revenue Growth Management page</i></a><i> to learn more.</i></p>