Artificial intelligence has been applied within the CPG industry for some time in the form of predictive and prescriptive modeling and revenue growth management.  While there is broad adoption of AI in forecasting and analytics, agentic AI is changing the landscape.  Traditional AI models passively analyze data, but agents offer strategic advantage in both retrieving information and insights as well as performing specific trade management tasks.  Learn more about AI and its impact on TPx here.

According to the survey report from Vertesia, “58% of respondents said that the ROI of AI exceeded their expectations, 92% said the return met or exceeded expectations." Companies that can successfully integrate agentic AI into their sales operations will gain a competitive edge—from more effective and efficient retail trade spend management to the alleviation of time-intensive tasks that distract your sales team from their core function of selling. However, this integration requires a thoughtful preparation of sales teams, as many may view AI with a mixture of curiosity and apprehension.  This blog will help you craft a plan to prepare your sales team, with a practical strategy for implementation, training, and change management.

The State of AI in CPG Sales Today

The CPG industry has been leveraging AI in various capacities, though often in limited and siloed applications. Current implementations typically include:

• Trade optimization solutions that enable teams to quickly understand the most efficient trade plans to meet their goals
• Demand forecasting tools that predict inventory needs based on historical data and recommend optimal assortment mix
• Price optimization algorithms that suggest ideal price points for maximizing margins
• Customer segmentation systems that categorize retail partners and consumers
• Trade promotion effectiveness tools that analyze the ROI of promotional activities

The gap between available AI technology and actual implementation remains substantial, with McKinsey estimating that less than 30% of CPG companies are utilizing AI at scale across their organizations.  Learn more about TPO and why your business needs it here.

Understanding Agentic AI: A Primer for Sales Leaders

Agentic AI represents a fundamental shift in how artificial intelligence operates within a business context. Unlike traditional AI systems that function primarily as responsive tools, agentic AI systems act as semi-autonomous entities capable of:

1. Making decisions within defined parameters without constant human supervision
2. Learning continuously from interactions with humans, systems, and environments
3. Taking initiative to address opportunities or problems before they're explicitly identified
4. Collaborating with humans and other AI systems to achieve broader objectives

For CPG sales teams, the distinction becomes clearer when we compare traditional and agentic approaches, let’s use a trade management example:

Traditional AI approach: A sales analytics tool identifies promotions that perform well from a sales and profit standpoint and predicts the volume that various combinations of price points and tactics will generate.

Agentic AI approach: An AI Agent responds rapidly to natural language commands, thus saving the sales person all the key strokes to generate and analyze different scenarios. The Agent can then respond to tasks and activate those scenarios on command.

The latter represents a collaborative partner rather than a passive tool—a critical evolution that changes how sales professionals work with technology.

Challenges and Concerns from the Sales Team Perspective

With processes changing and increasingly autonomous AI, members of the sales team may be concerned about job displacement.  Research and experience suggest a different outcome: AI tends to transform rather than eliminate sales positions. The most likely scenario involves a transition from transactional activities to more strategic, relationship-building work.  Framing AI as augmentation instead of replacement is critical to assuage this concern. 

The sales team may also be concerned that the learning curve will be high.  Make sure to implement graduated training programs so that everyone can slowly become more comfortable and confident in working with the agents. 

Ethics and the oversight of AI agents may be a concern.  Make sure to set clear boundaries and steps for human oversight in the processes implemented by your organization. 

It’s also critical to have the sales team build trust in the agents.  Start by using them for smaller tasks so that the confidence in their abilities can grow - remember Agents need to learn so they will also get better with this approach. 

Skills Assessment and Gap Analysis

Begin by mapping current capabilities against future requirements. Critical skills for the AI-augmented sales professional include:

• Technical literacy: Understanding AI capabilities, limitations, and interaction methods
• Security awareness: Teams need to use agent in a way that doesn’t jeopardize company data and intellectual property
• Data interpretation: Ability to evaluate AI recommendations critically
• AI collaboration: Skills for effective human-AI teamwork and task division
• Strategic thinking: Focusing on higher-level objectives while delegating routine tasks
• Relationship intelligence: Enhanced human connection skills that differentiate from AI capabilities

Assess your team's current proficiency in these areas to identify training priorities.

Training Program Development

Based on identified gaps, develop a comprehensive training program that includes:

• Technical foundations: Basic AI concepts, terminology, and interaction methods
• Collaborative workflows: Processes for effective human-AI teamwork
• Critical evaluation: Methods for assessing AI recommendations
• Feedback mechanisms: Techniques for improving AI performance through feedback
• Strategic elevation: Approaches for focusing human effort on high-value activities
• Corporate policy: Ensure that the team is fluent in all corporate rules regarding AI usage

Create a certification program that recognizes progressive levels of AI collaboration proficiency, providing a clear development path for team members.

Pilot Program Design and Implementation

Before full-scale deployment, design targeted pilot programs that:

• Focus on specific high-value use cases
• Include diverse team members with varying technical comfort levels
• Establish clear metrics for success
• Include regular reflection and adjustment periods
• Document both quantitative outcomes and qualitative experiences
• Provide a safe environment (such as a designated sandbox) for experimentation with agents

Successful pilots provide both proof of concept and valuable implementation insights while creating internal case studies that demonstrate value.

Make sure to implement metrics to evaluate how helpful the agents were to the sales team.  Track KPIs like time saved, account expansion, response time, and customer satisfaction. Capture down-stream impacts as well, if the team saved time, what did they generate with that time? These metrics should balance efficiency gains with effectiveness improvements and relationship quality.

Steps to Get Started

For CPG companies beginning their agentic AI journey, consider this phased approach:

Phase 1: Assessment and Foundation (1-3 months)

• Conduct AI readiness assessment
• Evaluate data infrastructure and quality
• Identify high-potential use cases
• Develop initial governance framework
• Select technology partners with CPG expertise

Phase 2: Pilot Implementation (3-6 months)

• Launch targeted pilots in 2-3 sales applications
• Implement initial training programs
• Establish feedback mechanisms
• Document baseline metrics
• Identify and develop internal champions

Phase 3: Expand and Optimize (6-12 months)

• Scale successful pilots to broader team
• Refine training based on pilot learnings
• Implement performance metrics for AI collaboration
• Develop advanced use cases
• Create knowledge-sharing mechanisms

Phase 4: Transform and Integrate (12+ months)

• Reimagine sales processes around AI capabilities
• Integrate AI across sales workflow
• Establish advanced human-AI collaboration models
• Evolve organizational structure to maximize AI value
• Develop ongoing learning program for continuous improvement

The integration of agentic AI into CPG sales represents not merely a technological upgrade but a fundamental transformation in how sales organizations operate. Companies that approach this transition strategically—preparing their teams, establishing clear governance, and focusing on high-value applications—will gain significant advantages in an increasingly competitive marketplace.  

PSignite is bringing Agentic AI trade management with cpgvision v6.  TPXperts are autonomous, goal-oriented AI agents that execute custom trade tasks. They work as chatbots or behind the scenes, always respecting Salesforce’s secure access controls.