The AI advantage in KAM

10th January 2025 |   Mark Davies and Richard Brooks

How AI can help to create ideas and boost efficiency for key account managers.

Implementing a strategic KAM plan that generates profitable growth for both the supplier and the key customer is notoriously difficult. As consultants and advisers to hundreds of key account managers working in multiple organisations and varied industries, we see talented managers struggle to be consistently effective on a daily basis. This is not a reflection on the people we work with, it is a symptom of the fact that KAM is difficult!

Why is this the case? It is often underestimated but KAM is a “shift” change from selling a core brand or product. When a supplier selects a customer as “key” they are identifying that there is potential additional growth in that customer, but it will probably need a unique offer to achieve those sales. This implies that deeper research, more creative offers, unique business cases, and strategies and engagement with different executives is required.

AI is reshaping the landscape of key account management, offering tools that revolutionise how we work and deliver value to clients.

This is a lot of additional work and “heavy lifting” for the key account manager. In an ideal world, they will have a fully supportive organisation that provides resources and cross-functional team members. But that is in an ideal world. In most supplier worlds people are busy doing their own things in their own silos. Key account managers have to do most of the work independently. If only they had a “buddy” that could help out with an endless stream of energy, information, ability to analyse and with no personal agenda. Well, with artificial intelligence (AI), that day might now be here.

This article explores three avenues to discuss how AI can create ideas and boost efficiency for KAMs. We examine what a key account manager does when developing strategies for each strategic customer. Secondly, we offer a quick review of how current AI tools can be adopted to accelerate performance. Finally, we suggest a few tips to assist in the adoption of AI in the world of KAM.

What do key account managers do?

Key account managers develop and deliver strategy: customer by customer.

One way to explore this further is to look at the planning cycle that they follow.

Figure 1 illustrates the stages that are typically followed by any key account manager as they develop business for a strategic customer. The foundation stage gathers value insights (by understanding the customer). Building on these insights, a compelling and innovative value proposition is created, and then a strategy/business model is established to deliver this new offering.

Assuming the customer buys this value proposition, the model shifts from developing and creating to value delivery, whereby the KAM ensures that value delivered to both supplier and customer is measured, tracked and communicated.

This model can be further expanded to start defining the core activities that the KAM must conduct to make each stage work and function effectively (Figure 2).

This model is really useful for a number of reasons. Firstly, it helps organisations define and specify the skills that are required from the key account managers they employ – typically they need to be general managers with additional customer-facing experience.

The model is also useful to determine the support systems and team members that are required. As you shift around the cycle, skills essentially go from researching and relationship building, to creating ideas and developing new offers, to strategising and, finally, to operationally delivering the value promised in the offer. If you have ever wondered what KAM do exactly (and why it is hard to find good talent to do these jobs), this model will help you understand.

How can artificial intelligence help?

AI is reshaping the landscape of key account management, offering tools that revolutionise how we work and deliver value to clients. Generative AI, in particular, stands out as a transformative force, empowering key account managers to create, innovate, and communicate with unmatched efficiency.

From crafting personalised client proposals to streamlining research and brainstorming sessions, generative AI provides unparalleled support for KAMs handling complex accounts. Whether it’s uncovering actionable insights, designing tailored strategies, or enhancing operational alignment, AI amplifies both the impact and productivity of KAMs across every stage of the planning cycle.

Here are some popular examples of generative AI technologies that KAMs can harness effectively:

• ChatGPT – A conversational Large Language Model (LLM) developed by OpenAI, ChatGPT excels at natural language understanding and generation, making it ideal for drafting text, brainstorming, and answering complex queries.
• Claude – Built by Anthropic with a focus on safety and reliability, Claude is a helpful assistant for summarisation, dialogue, creative writing, and problem-solving, offering a user-centric AI experience.
• Gemini – A multimodal model by Google AI, Gemini processes text, images, and audio, providing a flexible and efficient tool for general-purpose use.
• Perplexity – Designed to provide accurate, comprehensive answers, this AI actively retrieves and synthesises information from the internet, making it an excellent research assistant and source of reliable knowledge.
• NotebookLM – Developed by Google AI, NotebookLM acts as an AI-powered organisational tool, helping users manage information, generate new ideas, and create tailored content, essentially serving as an intelligent digital notebook.
• Llama – Developed by Meta, Llama (Large Language Model Meta AI) is open-source and accessible for both research and practical applications. It offers various model sizes, enabling users to tailor its implementation to specific needs, from smaller, resource-efficient deployments to larger, more capable models.

Beyond these general-purpose models, specialised AI tools are emerging for specific tasks, such as writing code, creating images and videos, and automating workflows. These specialised models offer targeted functionality, allowing professionals to makes use of AI for even more refined and efficient outcomes.

To illustrate the potential of AI in Key Account Management, let’s examine the strategic KAM planning cycle and explore how these AI models can be practically applied at each stage.

Amplifying key account management with AI

1. Value insights

In the initial phase of gathering insights, AI empowers key account managers to accelerate the research process and gain a deeper understanding of the customer’s ecosystem. This includes identifying critical details about the customer’s business, their clients, suppliers, and competitors, enabling a comprehensive and holistic view of key accounts.

AI models can also analyse historical performance data, revealing patterns and trends in customer interactions. These insights allow identification of successful strategies from the past while pinpointing areas for improvement. For example:

• Perplexity – An invaluable tool for gathering and summarising publicly available data about clients, markets, and competitive landscapes. It delivers actionable insights in a fraction of the time it would take using traditional research methods.
• NotebookLM – Ideal for processing internal data, such as emails and meeting notes. NotebookLM helps to quickly identify recurring themes, track progress, and connect insights across various conversations.

By integrating these tools into your workflows, you can transition from reactive account management to a more proactive, data-driven approach. What’s more, many of these tools are highly accessible and cost-effective, making them available to organisations of all sizes and budgets. With the ight instructions and a strategic mindset, even the simplest AI tools can significantly enhance your workflow, enabling you to deliver deeper insights, faster responses, and more tailored strategies.

This accessibility lays the foundation for building stronger, more value-focused client relationships, ultimately driving mutual success and positioning you as a trusted partner in your key accounts.

2. Value proposition

AI fosters creativity by assisting in brainstorming ideas and designing tailored solutions that address the unique challenges and opportunities of key accounts. By harnessing large-context models like ChatGPT, KAMs can process vast amounts of client-specific data, transforming this into a rich foundation for innovation.

As an example, with any modern LLM and a carefully crafted multichain prompt, KAMs might ask:

“Generate ten innovative solutions for [key account name] based on the trend of [identified trend], using insights from [data source] as the foundation.”

This process unlocks a wealth of ideas, enabling the exploration of practical, unconventional, and even playful solutions. This can transform brainstorming sessions into journeys of discovery, surfacing creative approaches that might otherwise remain hidden.

3. Value strategy

Refining and implementing strategies to deliver compelling new offers requires close alignment between supplier and customer organisations. AI-powered tools can play a role in bridging gaps, streamlining processes, and ensuring that cross-functional teams can work cohesively.

Optimise organisational resources

AI-driven tools can analyse organisational strengths and weaknesses, propose efficient resource allocation strategies, and even predict potential bottlenecks. These insights empower businesses to prepare thoroughly, scale solutions effectively, and mitigate risks before they arise.

For instance, predictive modelling platforms can:

• Assess the feasibility of a proposed solution.
• Identify gaps in resource planning.
• Recommend adjustments to align organisational capabilities with client demands.

Facilitate team alignment

Collaboration between supplier and customer teams is helpful for aligning efforts and achieving mutual goals. By integrating systems and working within shared platforms, cross functional teams can break down silos, enhance trust, and ensure that every stakeholder is aligned. AI-powered tools take this collaboration to the next level, offering features that streamline workflows, identify misalignments, and propose strategies for enhanced cooperation.

• Integrating shared systems – AI tools like Zapier and Make allow suppliers and customers to connect their disparate systems, such as CRMs, project management tools, and analytics platforms. For example, syncing a supplier’s Salesforce system with a customer’s Monday.com workspace ensures seamless data sharing, enabling both sides to work from the same real-time information.
• AI-powered collaboration features – Platforms like Miro and ClickUp now include AI functionalities that analyse project updates and task completions to highlight potential bottlenecks or areas needing more focus. AI-generated insights from these tools can suggest adjustments to workflows or priorities, ensuring that both supplier and customer teams remain in sync.
• Joint decision-making with AI – Tools like Notion AI and Microsoft Teams (with Viva) enable collaborative content creation and discussion by summarising key data points from both teams’ systems. An AI tool could automatically compile a summary of weekly performance metrics from both parties, highlighting shared wins and areas requiring attention.
• Real-time communication and analysis – AI-driven chat platforms, such as Slack with Workflow Builder, can facilitate instant messaging and automate updates across both supplier and customer systems. This ensures that everyone is informed and aligned without needing constant manual oversight.

4. Value delivery

Delivering value isn’t just about execution; it’s about making that value clear, measurable, and meaningful to all stakeholders. This requires setting clear goals, tracking progress in real-time, and communicating results in ways that resonate. AI tools can transform and streamline value delivery.

Define and track what matters

AI-powered analytics tools provide a powerful way to track metrics in real time, offering insights that help KAMs stay aligned with client objectives.

• Practical example – Predictive AI tools like Power BI or Tableau can automatically correlate metrics such as cost savings, revenue growth, or process efficiencies with client-specific goals, generating actionable insights into the value being delivered.
• AI in action – Tools like Claude can automate the summarisation of data, highlighting key performance indicators and trends that might otherwise have been overlooked.

Foster alignment and communicate value

Delivering value requires seamless collaboration and clear communication. It’s a team sport. Smart technologies enhance by aligning teams and streamlining how results are communicated.

• Collaborative platforms – Tools like Asana, Notion AI, or Slack streamline workflows, prioritise tasks, and highlight misalignments with AI-driven insights.
• System integration – Tools such as Zapier or Make sync data across supplier and client systems, ensuring everyone works from the same real-time information.
• Visualising impact – Platforms like Qlik Sense, Canva, or Visme turn complex metrics into intuitive visuals, while Gemini condenses reports into audience-specific summaries.

By aligning efforts and presenting results with clarity, AI fosters stronger partnerships and highlights the tangible impact of collaborative efforts.

Closing thoughts

We live in the age of the prompt: a time when large language models (LLMs) can compute almost anything, but their true potential lies in how effectively we communicate with them. Knowing how to “talk” to AI is the key to unlocking its transformative capabilities. Crafting clear, strategic prompts can turn this technology into a powerful partner (buddy!) in creativity, analysis, and decision-making.

The best way to embrace AI is simply to start. Dive in, experiment, and let creativity guide the way. When we teach this topic, we encourage participants to play first – whether by composing a song, writing a poem, or creating an image. This playful exploration often sparks unexpected insights, building confidence in using the tools before applying them to professional tasks.

Knowing how to “talk” to AI is the key to unlocking its transformative capabilities.

From there, transition into practical applications. Begin with small, manageable tasks – like summarising meeting notes or brainstorming ideas – and expand as you grow more comfortable. To support this journey, we’ve created The Key Account Manager’s Guide to Prompting – a resource designed to help you harness the full potential of generative AI. Email us to request a copy, and we’ll send it your way.

AI isn’t just a tool; it’s a new way of thinking. It’s an opportunity to innovate boldly, solve complex problems, and create meaningful value. Start today and discover where it takes you.