AI in FMCG: Moving Beyond Experimentation to Practical Business Impact
In our discussions with clients Artificial Intelligence has become one of the most common topics discussed across the FMCG industry.
Whether you work in sales, category management, marketing, eCommerce, supply chain or leadership, AI is now appearing in almost every business conversation. Retailers are investing heavily. Suppliers are exploring use cases. Teams are experimenting with new tools. Yet for many organisations, one question remains:
How do we move from experimentation to meaningful business value?
That was the focus of our recent MindPick Talk, where we brought together AI strategist Kingston Lee-Young Mavens AI, FMCG AI coach Janine Chamley Pitchfork and FMCG GM Alex Boden to discuss the practical realities of AI adoption.
The session attracted our largest audience to date, highlighting just how important this topic has become across the industry.
Rather than focusing on futuristic predictions, the discussion centred on practical applications, real-world examples and how FMCG professionals can start using AI today.
AI is not one product. It is an entire industry
One of the most useful frameworks shared during the session came from Kingston Lee-Young.
Many people talk about AI as though it is a single technology. In reality, AI is an entire ecosystem made up of foundation models, software platforms, applications and specialised tools.
Kingston compared AI to the automotive industry.
The large foundation models such as OpenAI, Anthropic and Google are the engine manufacturers. Applications such as ChatGPT, Claude and Gemini are the vehicles built around those engines. Highlighting different tools are designed for different jobs.
This distinction matters because many businesses are still trying to determine which platform they should use. The answer is often less important than people think.
The real competitive advantage comes from understanding how to use AI effectively rather than endlessly comparing tools.
As Janine highlighted during the session, organisations should focus on mastering one platform deeply before worrying about every new release or feature. The fundamentals of prompting, thinking and workflow design matter far more than chasing the latest tool.
AI is Best Viewed as a New Team Member
One of the strongest themes from the session was that AI is not google and should not be treated as a search engine.
Instead, it should be treated as a new team member.
Janine shared a simple framework:
- Think with me
- Write with me
- Organise with me
- Build with me
This perspective changes how people engage with AI. Instead of asking it to simply find information, users can work alongside it to brainstorm ideas, challenge assumptions, structure thinking, create first drafts and build repeatable systems.
For many FMCG professionals, this is where the biggest opportunity exists.
AI is becoming a thinking partner rather than just a productivity tool.
The Three Levels Of AI Adoption
A key takeaway from Kingston’s presentation was that AI adoption happens across three distinct levels.
Level 1: Task Automation
This is where most businesses are today. At this level, AI helps individuals complete existing tasks faster.
Examples include:
- Summarising meetings
- Drafting emails
- Analysing documents
- Creating presentations
- Taking meeting notes
- Producing first drafts
The task itself does not fundamentally change. The process simply becomes faster and more efficient. For many FMCG teams, this level alone can create significant productivity gains.
Level 2: Workflow Transformation
The next stage moves beyond individual productivity. AI becomes embedded across multiple steps, systems and people.
Examples include:
- Automatically summarising meetings
- Generating action lists
- Scheduling follow-up meetings
- Creating stakeholder updates
- Producing reports from multiple data sources
At this level, businesses begin removing friction from processes rather than simply improving individual tasks.
Level 3: Business Reinvention
The most advanced stage involves rethinking how work happens altogether.
Kingston used a simple example. Many organisations use AI to summarise meetings. Some use it to create action lists and automate follow-up tasks. But the bigger question is:
Do we actually need the meeting at all?
If AI can gather information, distribute updates and provide recommendations beforehand, perhaps the meeting becomes shorter, involves fewer people, or focuses purely on decision making.
This shift in thinking represents the true opportunity of AI. Not simply doing the same things faster. Doing better things altogether.
Practical AI Use Cases For FMCG Teams
One of the most valuable parts of the session was Janine’s focus on practical applications. Rather than theoretical discussions, she shared examples that FMCG professionals can begin using immediately.
Category Management And Insights:
AI can help category teams move faster from data to insight.
Applications include:
- Turning sales data into category stories
- Automating weekly reporting
- Identifying growth opportunities
- Finding patterns in retailer performance
- Creating dashboards from multiple spreadsheets
Rather than spending hours preparing reports, category managers can spend more time interpreting results and influencing decisions.
Retailer And Buyer Preparation:
Preparing for retailer meetings often involves gathering information from multiple sources.
AI can help by:
- Comparing retailer strategies
- Reviewing contracts
- Creating retailer-specific presentations
- Building launch plans
- Generating briefing documents
- Identifying potential buyer objections
Importantly, AI can also help teams challenge their own assumptions before entering customer conversations.
Shelf And Planogram Analysis:
One particularly interesting example involved using AI to analyse shelf images.
By uploading photos, teams can:
- Assess share of shelf
- Identify white space opportunities
- Compare retailer executions
- Evaluate planogram compliance
- Generate ranging recommendations
For category and shopper teams, this creates opportunities to analyse stores at scale in ways that were previously difficult or time-consuming.
Strategic Thinking and Planning:
Perhaps the most powerful use case discussed was using AI as a strategic thinking partner.
Rather than asking for answers, users can ask AI to:
- Play the role of a retailer buyer
- Challenge assumptions
- Conduct pre-mortems
- Stress-test plans
- Surface risks
- Explore alternative approaches
This approach helps improve decision quality rather than simply increasing productivity.
The Human Still Matters Most
A recurring theme throughout the session was that AI is not replacing judgment. It is enhancing it.
Kingston made the point that AI is increasingly effective at gathering knowledge, synthesising information and generating recommendations.
However, it still lacks human judgment which is a critical distinction.
Commercial decisions still require:
- Context
- Experience
- Leadership
- Stakeholder management
- Relationship building
- Risk assessment
These remain fundamentally human capabilities. The organisations creating the most value from AI are not removing people from decisions. They are enabling people to spend less time on administration and more time on judgment.
Common Barriers To AI Adoption
The session also explored why many AI initiatives struggle to scale. Some of the most common challenges include:
Inconsistent Results
Many people try AI once or twice and become frustrated. Often this comes down to poor prompting, limited context or using the wrong tool for the task. Like any skill, capability improves with practice.
Lack Of Process Clarity
Before businesses can automate workflows, they must first understand how those workflows operate.
Many organisations discover that processes are undocumented, inconsistent or dependent on individual knowledge. AI often exposes process issues rather than creating them.
Data Challenges
High-quality outputs depend on high-quality inputs. Poor data quality remains one of the biggest barriers to successful AI implementation.
Governance And Security
As adoption increases, businesses must establish clear policies around:
- Data security
- Confidential information
- Usage guidelines
- Governance frameworks
- Human accountability
These conversations are becoming increasingly important as AI becomes embedded within daily work.
What FMCG Leaders Should Focus On Now
The discussion concluded with a simple message. Most FMCG organisations do not need an AI revolution tomorrow. They need consistent progress today.
For leaders, that means:
- Encouraging experimentation
- Building AI capability across teams
- Sharing best practices
- Creating governance frameworks
- Identifying high-value workflows
- Focusing on business outcomes rather than technology
The goal is not to implement AI for the sake of AI.
The goal is to improve decision making, increase productivity and create better outcomes for customers, teams and businesses.
Final Thoughts
The FMCG industry has always evolved through innovation and AI represents the next major shift.
However, the businesses creating value are not necessarily the ones using the most advanced tools. They are the ones asking better questions. They are identifying repetitive tasks that can be automated. They are redesigning workflows. They are creating more space for strategic thinking and they are helping their people develop the skills needed to thrive alongside AI.
The future of AI in FMCG is unlikely to be about replacing people. It is far more likely to be about helping people do their best work.
That journey has already started. The question is no longer whether AI will impact FMCG. The question is how quickly organisations learn to use it effectively.
At MindPick, we believe some of the best learning happens through shared experience, practical discussion and exposure to different perspectives.
That’s why our Growth Pods, Mentoring and MindPick Talks bring FMCG professionals together to discuss the challenges shaping our industry today.
If you’re interested in developing your capability, expanding your network and learning from experienced FMCG leaders, explore our Growth Pods, upcoming Talks and Advisory services to learn more.
Read about our other MindPick Talk Lessons in Growth
