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Layering AI into your B2B Product and GTM

A framework on how to add AI in the key use cases of your current product

AI is affecting virtually every aspect of SaaS businesses but the hype is deafening. ​So, as a tech company leader:

  • ​how do you decide where to layer AI into your current roadmap?

  • ​how do your business buyers & users assess AI value?

  • ​how do you change your positioning and GTM with AI?

Recently, I had an opportunity to present my framework for "Layering AI into Your B2B Products” in a conversation with Ibrahim Bashir, VP Product Management at Amplitude.

In this video, we cover several key aspects of integrating AI into B2B products, including challenges, and practical approaches. We had a lively discussion at the end by product leaders who had attended. 

Here is a quick summary

Introduction: We kick off with a discussion of why integration of AI into B2B products is needed, highlighting the excitement and challenges of developing an AI strategy in response to increasing demands from leadership, customers, and partners.

Framework for Integrating AI: I discuss the need for a mental model that simplifies understanding where AI can be beneficial in a product and buyer journey. 

Separation of Concerns: The B2B environment typically involves buyers focused on business metrics and goals, users executing tasks, and teams collaborating on workflows. These are typically divided into three layers: users, teams, and buyers, each with distinct needs and challenges. 

Challenges with Current Frameworks: The current value frameworks across three layers often suffer from slow human intelligence feedback loops. When goals are not met, the process of identifying issues and implementing changes can be lengthy and inefficient.

AI Modes: I introduce four practical AI modes:

  1. Redundant: Eliminate tasks that no longer require human involvement.

  2. Repetitive Routine: Automate repetitive and low-risk tasks, such as email filtering and customer support triage.

  3. Real-Time: Provide real-time assistance in tasks requiring immediate responses, like live chat support.

  4. Augmentation: Support complex tasks that require human insight and reflection, such as strategic analysis.

Practical Applications Across Layers:

I apply these AI modes to each of the layers, and discuss implications

  1. User Layer: AI can improve user productivity by eliminating redundant tasks (e.g., data extraction), automating repetitive tasks (e.g., meeting scheduling), providing real-time assistance (e.g., sales calls), and enhancing performance feedback.

  2. Team Layer: AI can streamline team workflows by automating manual processes (e.g., resume screening), improving collaboration, and real-time workflow adjustments.

  3. Buyer Layer: AI can help buyers with decision-making by automating routine reports, providing predictive analytics for maintenance, and supporting strategic decisions with comprehensive data analysis.

Even if current products are enhanced with AI capabilities, there is a possibility of getting disrupted by AI-first products which follow a different value ladder based on AI feedback loops versus the current value structure of human feedback. 

AI First Value Ladder

  • The main feature of AI first value ladder is the transition from improving current tasks and workflows to directly achieving business goals.

  • The potential disruption AI can bring by starting with the goal and working backward to streamline workflows and tasks.

Go-To-Market (GTM) Implications:

  • Considerations for targeting and differentiating AI-enhanced products from existing products on one hand and AI-first products that may not be realized for a while.

  • The impact of AI on GTM strategies, including the potential need for new pricing models, packaging, and positioning.

Conclusion: We stress the importance of a strategic approach to AI integration, focusing on enhancing value across user productivity, team collaboration, and buyer decision-making. We also highlight the potential for AI to disrupt traditional frameworks, urging businesses to prepare for the evolving landscape.

I would love to get feedback on the framework and discussion. 

Growth Matters
Growth Matters Podcast
Growth Matters podcast and newsletter is for tech leaders seeking to scale their business. Anurag Wadehra explores patterns that drive growth, achieve product market fit and build a sustainable brand
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Anurag Wadehra
Ibrahim Bashir