Agentic AI can transform trade promotion management. How will your teams build stronger partnerships and drive ROI?

Key takeaways

• Trade promotion management (TPM) is a highly complex set of processes and capabilities that would benefit greatly from applying agentic AI to routine and repetitive tasks.
• Agentic AI can seamlessly reduce risk and errors in CPG sales and TPM by helping teams enforce policies and automate oversight.
• Real-world examples show how agentic AI can proactively resolve issues in fund allocation, customer interactions, and deduction management.
• Agentic AI frees teams to focus on growth and partnership, transforming CPG-retailer collaboration.  

In the world of consumer packaged goods (CPG), sales and trade promotion management (TPM) is a high-stakes, performance-driven pursuit.

The pressure to deliver results can sometimes push even the best teams to work around established systems and guardrails, which introduces risks for both businesses and customers.

Delivering successful trade promotions requires emotional intelligence, sharp business instincts, and adaptability. But with so many moving parts, even small missteps can snowball into big consequences.

How can you use technology to prevent the most common human pitfalls in CPG sales and TPM?

The introduction of agentic AI’s intelligent, autonomous systems could offer support and help salespeople thrive in a new landscape of AI-enabled success. Beyond automation, agentic AI can embed intelligent controls and facilitate direct, dynamic interactions between teams, systems, and customers. By shifting routine oversight to AI agents, people are freed to focus on strategy, relationships, and growth, while autonomous systems proactively safeguard against errors and risks.

How agentic AI could transform TPM

Traditionally, customer teams have relied on institutional knowledge and historical data for account planning and promotions, often reacting to customer feedback and market shifts in real time.

Agentic AI changes the game by integrating real-time data, enforcing policies, and automating routine tasks. Unlike traditional automation, agentic AI agents go beyond executing tasks. They interact, adapt, and monitor controls in real time, creating a more resilient and responsive TPM environment.

Consider the following real-world examples and imagine how a sales force supported by agentic AI might have identified risks earlier or acted differently.

Misallocation of trade funds across brands

Contrary to company policy, a key account manager diverted surplus trade funds from Brand A to support Brand B’s promotions. This indirectly reduced Brand A’s margin and inflated Brand B’s sales. When the brands were ultimately divested in separate transactions, Brand A was undervalued due to lower margins (from unnecessarily high trade accruals), while Brand B was overvalued because its revenue was artificially boosted by cross-spent trade funds.

The agentic AI solution: Instead of passively flagging issues, agentic AI autonomously enforces fund allocation policies, interacts with account managers to validate and approve transfers, and provides real-time, transparent reporting to ensure visibility and traceability at every step.

Missed deductions and post-audit risk

A key customer consistently under-deducted promotional claims due to an error in its systems, allowing the sales team to use the surplus for extra in-year promotions. This inflated revenue and margin for the year. The next year, the customer realized its error and reclaimed the funds through post-audit deductions, forcing repayment from current budgets and reducing in-year promotional funding, which negatively impacted financial performance against an inflated prior-year base.

The agentic AI solution: Agentic AI continuously reconciles claims using predictive analytics to spot unusual patterns and engages directly with sales and finance teams when issues are detected. By automating audit trails and prompting teams to resolve discrepancies proactively, the agent reduces the risk of future post-audit deductions.

Paying for unrealized growth

To drive above-market growth in Q4, a customer team launched an incentive program tied to incremental promotional execution and in-store displays. Lower-than-expected sell-through left them obligated to pay lump-sum incentives without sufficient trade accruals to cover the commitment. This created a financial shortfall when market conditions shifted, and replenishment lagged expectations.

The agentic AI solution: Agentic AI proactively engages with customer teams and finance, modelling market scenarios and tracking sell-through in real time. When it detects a gap between incentives and actual performance, the agent initiates communication to recommend or automatically adjust payouts, ensuring trade obligations are managed collaboratively and transparently as market conditions evolve.

End-user rebate payments

A leading food manufacturer was concerned that independent restaurant operators were not receiving accurate end user rebate payments by making claims through group purchasing organizations (GPOs). The alternative was to use manual processes to collect purchase data and issue rebate cheques via field sales, creating inefficiencies and the risk of double payments.

The agentic AI solution: Agentic AI seamlessly aggregates purchase data across distributors and GPOs, automatically reconciling operator identities from distributor velocity reports to flag potential double-dipping. The agent streamlines rebate payments, ensuring each operator receives only one rebate payment per qualifying purchase, while delivering actionable insights to refine program rules and prevent future post-audit claims.

Volume validation gap

A category leader saw declining effectiveness in trade investments aimed at driving profitable volume growth. Upon reviewing historical deductions, it was found there were consistent discrepancies between the volume claimed and what was sold through at the point of sale. This difference was primarily the result of trade offers being based on shipped volume into stores (i.e., as a billback) compared to what was sold to shoppers.

The agentic AI solution: Agentic AI actively monitors and interacts with both sales teams and customers in real time. It autonomously compares shipped versus sold-through volumes and initiates direct inquiries when discrepancies arise. It validates deductions collaboratively with stakeholders and alerts teams before any gaps impact profitability for either party or create future inventory issues at the store level.

How agentic AI can deliver results

When building AI agents for use in sales and trade promotion management, several key prerequisites must be in place to ensure effectiveness, compliance, and value creation.

In addition to the standard data and technology requirements needed to set your AI agents up for success, the most important prerequisites include:

• Defined business objectives and use cases
  Clear goals and boundaries for AI agents, with KPIs aligned to growth, ROI, compliance, and customer satisfaction.
  
• Domain-specific knowledge bases
  Along with quality data from your trade promotion management tool (TPM), customer relationship management (CRM), enterprise resource planning (ERP), and syndicated sources.
• Integrated sales and finance workflows
  Well-mapped processes for promotion planning, fund allocation, claim validation, and customer communication.
• Human oversight and governance
  Mechanisms for review, approval, and override of AI recommendations aligned with compliance and internal controls.
• Change management and training
  Stakeholder engagement, tailored training, and clear communication to ensure adoption and build trust.

With these foundational elements in place, your organization will be well-positioned to unlock the full potential of agentic AI-driven trade promotion management.

Building stronger connections between CPG and retailers

Agentic AI can be a partner in governance, risk mitigation, and performance optimization for trade promotion management, resulting in stronger ROI and net revenue growth.

Beyond these commercial benefits, it can also be a game changer for how CPG companies and their customers work together. By automating the routine tasks and making data more transparent, agentic AI frees teams to focus on what really matters: building stronger partnerships and finding smarter ways to grow together. Instead of spending time untangling post-audits or chasing errors, sales and finance can collaborate directly with partners, using real-time insights to make better decisions about where to invest trade funds for maximum impact.

How Deloitte can help

Our Consumer Products leaders are deeply engaged in exploring how emerging technologies like agentic AI can benefit everyone involved in CPG sales and trade promotion management.

As customers adopt AI agents of their own, it’s up to CPG sales leaders to act boldly, leveraging AI to augment the human side of selling.

The future is coming fast. Are you ready to lead the way? Let’s chat about how we can help.