Future-proofing RGM with AI

Overview: Future-proofing RGM with AI > Module 02: How AI is changing RGM

How AI is Changing RGM

Discover why an AI-first strategy leads the way and how you can shift from asking “What happened?”  to confidently answering “What if…?”

Hear from senior leaders at Unilever and Ajinomoto on how AI is already reshaping RGM. They’ll share their experiences with its impact, and how they anticipate this evolution continuing to drive smarter, faster decisions.

This module sets the foundation for what comes next: understanding how to apply AI strategically when shaping your RGM strategy and leading your organization through lasting transformation.

• As AI reshapes how leading organizations make commercial decisions, Revenue Growth Management is entering a new era, one that is proactive, based on data-driven decisions and AI-powered simulations. RGM leaders must become strategic orchestrators: aligning the organization to reach revenue targets, driving innovation, and anticipating change.
• In this module, the course host, Ivan Tretyakov, introduces the key AI-driven shifts transforming RGM and the evolving role of the Revenue Leader at its center. 
• You’ll also hear from senior leaders at Unilever and Ajinomoto on how AI is already reshaping RGM. 

• AI technology empowers RGM leaders to shift from reactive decision-making to proactive, insight-led strategy planning.

• Winning teams embed AI into their planning, collaboration, and delivery of impact. (We dive deeper into this in future lessons.)

• To kick off your AI transformation, start by evaluating your current toolset and data quality. Drive the conversations with other functions about shared AI use cases.

Overview: Future-proofing RGM with AI > Module 03: Choosing the Right Type of AI for RGM

Choosing the Right Type of GenAI for RGM

Unpack the four interconnected layers of GenAI: data preparation, predictive modeling, offer optimization, and decision-making interfaces. Explore the role each layer plays, when to use it, and how combining them enables faster, more confident, and more strategic decisions.

Generative AI, Agentic AI, and Agent-Based Modeling Explained

Tim Schneider, Head of Sales Engineering & Partnerships at Buynomics, walks through the three types of AI that dominate today's RGM discussion: generative AI, agentic AI, and agent-based modeling.

Not all AI is created equal, and not all of it delivers strategic value for RGM. The right AI approach isn’t just about efficiency; it’s about enabling scenario testing, anticipating competitive moves, and market conditions to make confident decisions at speed. Choosing the wrong AI type risks wasting investment and missing revenue. 

In this module, Dr. Ingo Reinhardt, Co-Founder and Managing Director of Buynomics, draws on over a decade of pricing and RGM experience to unpack the actual capabilities of GenAI, how they work, and why simulation-based approaches are uniquely positioned to transform decision-making in RGM.

Plus, understand the three types of AI shaping the RGM conversation today (generative AI, agentic AI, and agent-based modeling), and explain why agent-based modeling is the right choice for RGM.

• Generative AI can process vast, complex datasets and uncover patterns far beyond the reach of traditional statistical tools.
• Legacy methods alone, like linear regression and price elasticity tables, are too limited to capture today’s market complexity.
• Simulation-based, integrated AI approaches scale with data growth, enabling more precise, forward-looking RGM decisions.
• There are four layers when using GenAI in RGM: 

• Generative AI, agentic AI, and agent-based modeling are not interchangeable. Each is designed for a different job, and matching the right AI type to the right RGM question is the difference between a pilot that scales and one that quietly fails.
• Agent-based modeling simulates millions of individual agents, each with its own preferences and rules, to reveal how entire markets behave when prices, portfolios, or promotions change.

In the next module, we’ll explore how to integrate AI into your RGM tech stack and decision processes in a way that builds trust, avoids common pitfalls, and ensures long-term adoption.

Overview: Future-proofing RGM with AI > Module 04: Integrating AI into Your Tech Stack

How to Integrate AI into Your Tech Stack

Discover a six-step process for making AI integration successful. From building a strong business case to democratizing insights, you’ll see how leading organizations avoid common pitfalls and turn AI adoption into lasting impact.

Haja Deen, CIO, CTO, and Strategic Business Growth Advisor (ex-pladis), introduces his LEADERS Framework, guiding RGM leaders to truly integrate AI into their organization.

Successful integration is the difference between just experimenting with AI and actually transforming how your organization makes decisions.

This module breaks integration into clear steps: starting with your organization’s pain points, earning RGM stakeholder trust, aligning functions, and capturing early wins that prove value. You’ll learn how to proactively mitigate risks, appoint change champions, and democratize AI-driven insights to inform everyday decision-making.

When done right, integration future-proofs your RGM function, ensuring AI is not just introduced and left on the shelf, but fully embedded into how strategy and operations are run.

• Bridge high-level financial goals with day-to-day execution using an AI-powered RGM strategy
• Integration is not a one-off project or tool, but embedding AI into planning, decision-making, and execution.
• Without a deliberate change management strategy, even the most powerful AI tool will fail to deliver value
• Six steps to success
  • Build a strong business case
  • Gain trust
  • Align stakeholders
  • Capture early wins
  • Mitigate risks
  • Democratize insights.
• Avoid wasted investment: AI delivers lasting value only when trusted and used across all commercial functions.
• Introduction to the LEADERS Framework with Haja Deen

In the next module, we’ll move from integration to strategy. Discover how to embed AI into multi-year RGM planning cycles, define the metrics that matter, and ensure your organization tracks long-term success with confidence.

How to Develop and Lead Multi-Year RGM Strategies with AI

Bridge high-level financial goals with your day-to-day execution using an RGM strategy powered by AI. Discover how to build a 3-to-5-year vision for sustainable, profitable growth, embed AI-driven insights into strategic planning cycles, align all RGM levers, and define the metrics that track measurable business impact over time with a four-phase framework from Ivan Tretyakov, Innovations Director at Buynomics.

Expert Insights: Embedding RGM into Wider Business Planning

Colin McQuay, Sr. Director & Head of Strategic Revenue Management at Nestlé, shares how Nestlé integrates RGM into its broader business planning processes, an essential consideration when developing multi-year strategies. He also outlines the key KPIs they use to measure impact and align cross-functional teams around RGM goals.

Short-term fixes don’t scale in today’s volatile market. A true multi-year RGM strategy requires moving beyond reactive annual planning to embedding AI into your long-term roadmap,  bridging high-level financial goals with day-to-day execution across markets, categories, and teams.

In this module, Ivan Tretyakov, Innovations Director at Buynomics (formerly of Danone), introduces a four-phase framework for developing and executing multi-year RGM strategies rooted in AI and designed to extend beyond the Annual Operating Plan (AOP).

You’ll also hear from Nestlé’s Colin McQuay on how to embed RGM into broader business planning and which KPIs drive alignment and long-term impact. 

You’ll see how you can analyze your current data status, combine AI-powered diagnostics and simulations, and launch predictive analytics to design a 3-to-5-year vision that allows sustainable, profitable growth.

• An AI-powered RGM strategy bridges high-level financial goals with day-to-day execution
• Multi-year RGM planning requires embedding AI into strategy, not just operations
• AI shifts planning from descriptive hindsight to predictive and prescriptive foresight
• Begin with a clear-eyed view of your current data and capabilities
• Use a balanced set of KPIs to track financial and operational progress
• Embedding RGM into the wider business process is essential for success
• Set bold, measurable goals, but prioritize based on impact and feasibility
• Four-phase framework: 
  • Assess & Diagnose
  • Design & Simulate
  • Activate & Execute
  • Measure & Refine

In the next module, we’ll focus on sustaining change after implementation, ensuring your AI adoption doesn’t fade after initial wins, but continues to scale and deliver lasting transformation.

Sustaining Change After Implementation

Sustain momentum. Move from early wins to enduring, organization-wide adoption. In this module, Doug Hampshire, Head of Customer Value at Buynomics (ex-Deloitte), shows how to embed AI-driven ways of working using a practical three-part approach: Mindset → Process → Enablement, and shares success stories from industry-leading organizations.

When integrating a new AI tool, many teams celebrate a proof of concept, then stall. Sustainable impact comes from shifting mindsets, integrating AI into daily processes, and building technical confidence across functions. Doug introduces a practical, three-part approach (Mindset → Process → Enablement) and turns it into a concrete six-step path to sustained adoption that you can apply immediately.

You’ll learn how to formalize new routines, democratize insights, and measure adoption so that AI insights become operational, not optional, turning tools into long-term value creators.

You’ll also hear success stories from leading companies that have successfully sustained change after implementation, through methods such as appointing change champions and sharing tool use cases.

• Sustained change takes a three-part approach: Mindset → Process → Enablement
• Mindset first
  • Create awareness, share results, and reinforce success stories.
• Process integration
  • Map current workflows, remove bottlenecks, and embed tool checkpoints.
• Technical enablement
  • Train broadly, from onboarding to regular touchpoints, with clear ownership.
• Watch for siloed usage, weak handovers, knowledge gatekeeping, and no real integration.
• Make insights accessible to operational and management teams; track usage and business impact, turning tools into long-term value creators.
• Change mechanics that work: Tool “power users,” recurring use-case sharing, and impact-quantified business cases.

Module 06 will take the final step in the RGM Academy: moving from insight to action. You’ll learn how to turn AI-powered simulations and strategic plans into executable initiatives, ensuring decisions translate into measurable results. We’ll also explore how to evaluate and select the right tools to support sustained impact across your RGM function.

From Insight to Action

Turn insight into action. In this final module of the RGM Academy: Future-Proofing RGM with AI, Ivan Tretyakov, Innovations Director at Buynomics (ex-Danone), brings together the key learnings from across the course and shows how to transform them into measurable, organization-wide impact. 

Plus, learn the tradeoffs of the buy vs build decision when selecting the right tools to support your AI-enabled RGM journey, and take the final step from planning to performance.

Ivan Tretyakov addresses one of the most critical decisions for every RGM leader: whether to build your own AI tool in-house or buy a proven solution. You’ll gain clarity on how to assess the trade-offs, accelerate time-to-value, and ensure your investment fuels sustainable growth, not just another pilot project.

You’ll also review the complete journey of AI adoption, helping you bridge the gap between learning and taking the next step. You’ll learn how to apply Buynomics’ frameworks across teams and processes, build organization-wide alignment, and track performance with precision.

Three dimensions of turning insight into action

1. Awareness: Build understanding across functions. Share the “why” of AI-enabled RGM and align Sales, Marketing, Finance, and Supply Chain around a shared vision.
2. Embedding: Apply proven frameworks—such as the LEADERS framework, the four-phase strategic planning model, and the six-step adoption process—to integrate AI into daily work and long-term planning.
3. Measurement: Define KPIs to track adoption, alignment, and business impact. Communicate progress to sustain momentum and credibility.
   
   

Buy vs. Build: Choosing the right AI tool for your RGM strategy

• Build: Tailored and transparent, but resource-heavy, costly, and slow to scale.
• Buy: Fast, reliable, and continuously updated by experts, offering faster ROI and seamless integration.
• Key takeaway: Focus your internal resources on value creation, not software development. Proven SaaS platforms allow immediate time to value, and free up resources for other tasks, ensuring AI becomes a driver of growth.

Action matters.
You now have the frameworks, tools, and insights to lead lasting transformation. AI in RGM isn’t just about smarter models; it’s about better decisions, faster execution, and measurable results.

The RGM Academy: Future-Proofing RGM with AI certification program is now open.
Between May 18 and June 30 participants can test their knowledge of AI in RGM and earn certification, which Buynomics and RGM industry experts validate.

Certified participants will receive formal recognition as RGM professionals equipped to lead AI-driven transformation.

Take the Assessment

The Future Proofing RGM with AI certification window is open until June 30.

This certification validates that you can leverage AI to address complex RGM challenges and translate innovation into business impact.

With Buynomics’ proven expertise supporting global leaders, it signals your readiness to shape strategy, guide transformation, and lead your organization into the next era of growth.