From Training to Readiness: The Evolving Role of AI in Sales Enablement

Sales Enablement is Changing

Sales enablement is increasingly being shaped by a simple but profound challenge: traditional training models are no longer keeping pace with the realities of modern sales. As products grow more complex, buying groups expand, and customers arrive better informed than ever, sales teams can no longer rely on knowledge acquired weeks or months in advance. Instead, enablement is shifting toward real-time readiness: support that helps sellers prepare for specific customer conversations in the moments leading up to them. 

This shift reflects a broader move away from scheduled, one-size-fits-all training toward learning that is situational, contextual, and delivered on demand. The goal is no longer to push more content, but to make the right knowledge accessible when it can be applied. AI has emerged as a powerful accelerator of this transition, reshaping how sales teams personalise their preparation and translate learning into action. Drawing on his experience leading sales enablement across the Greater Asia region at Zscaler, Gilbert Ngu offers a practical lens on this transformation. His perspective reflects a wider change in how organisations are rethinking learning, preparation, and performance as enablement moves closer to the point of action.

From Training Rooms to the “Battlefield”: Rethinking Sales Learning

One of the most persistent challenges in sales enablement is not the quality of training itself, but the distance between learning environments and real customer conversations. What sellers absorb in workshops or training sessions often unfolds very differently once they are in front of a customer, navigating discussions under real-time pressure. Ngu likens this gap to the difference between planning on paper and operating on a battlefield; while training can prepare sellers conceptually, customer conversations remain dynamic, unpredictable, and deeply human. The result is a familiar problem across organisations: even well-trained sellers can struggle to recall or apply what they have learned when it matters most. 

To address this, many enablement teams are shifting away from static programmes toward learning models that more closely resemble the realities of selling. Role plays, gamified exercises, and scenario-based simulations are designed around specific customer contexts, shifting learning away from rehearsed messaging toward situational judgement and real-time communication. Crucial to Ngu is that this learning is increasingly delivered on-demand, giving sellers the opportunity to prepare in the final stages before a customer meeting. 

AI as a Catalyst for Sales Readiness 

“In the past, it would take me 20 hours or more to research a customer. Today, with AI, we can generate that customer-specific information in seconds.” - Gilbert Ngu, ZScaler

Across enterprise sales organisations, AI is increasingly shaping this shift toward preparation rather than performance. Its most immediate impact lies in reducing the time and effort required to understand a customer’s context before a conversation takes place. As Ngu notes, preparing for executive conversations has traditionally required extensive manual research, often taking many hours to synthesise information about a customer’s priorities, challenges, and industry landscape.

AI changes this dynamic by making relevant context available far more quickly, sometimes minutes before a meeting. In enterprise environments, this level of relevance is no longer optional; it has become the baseline expectation. As a result, sales conversations can begin from a place of shared understanding rather than discovery, allowing sellers to focus on the right solution for the customer and the quality of the interaction itself. 

Constraints, Trust, and Responsible Use

As AI becomes more embedded in sales enablement, the primary challenge organisations face is less about technical capability and more about trust. Particularly in enterprise and cybersecurity contexts, concerns around data sensitivity, accuracy, and governance play a central role in shaping adoption. 

Across organisations, there is growing recognition that AI-generated insights cannot be treated as final outputs. Human verification, whether filtering information, validating relevance, or checking accuracy, remains highly essential before insights are brought into customer conversations. Ngu illustrates this with an example where AI surfaced information that was several years out of date, reinforcing the need for oversight. Clear boundaries around what data can be accessed and how insights are applied help teams engage with AI confidently, without undermining trust internally or with customers. Within such usage, AI accelerates preparation, but responsibility remains firmly with the seller. 

The Future of Sales Enablement 

Looking ahead, one of the most persistent challenges for sales enablement remains measurement. While enablement plays a critical role in seller success, its impact has traditionally been difficult to quantify, given the number of variables that influence performance. Ngu sees AI as an opportunity to bring greater clarity to the direct impact of enablement initiatives. By identifying patterns across learning and outcomes, AI has the potential to help organisations better understand how enablement directly contributes to performance. 

At the same time, enablement is moving toward increasingly individualised learning models. As sales teams become more diverse in experience and capability, enablement must move away from uniform programmes toward paths tailored toward learning styles and specific skills. AI enables this shift by helping teams identify where each seller excels and where targeted support can have the greatest impact. 

Ultimately, Ngu sees the future of sales enablement as one defined by relevance and speed. The goal is not more content, but better-timed, on-demand support that is delivered when it matters most and aligned closely with customer needs.  

Leading Sales Enablement Through Change

For leaders navigating this transition, the fundamentals remain critical. Effective sales enablement still begins with training-led programmes, but emphasises the transition to real-time readiness. As sales cycles grow more complex and enterprise deals involve higher stakes, Ngu urges enablement leaders to operate as strategic partners. This means aligning learning initiatives with executive priorities and organisational outcomes, rather than treating enablement as a standalone function. 

What Ngu’s perspective makes clear is that sales enablement is no longer organised around training events, but around moments of use. As learning moves closer to live customer conversations, AI increasingly supports preparation and context-setting, while judgement, trust, and decision-making remain human responsibilities. The future of sales enablement is therefore not about scaling information, but about scaling judgment: designing learning systems that prepare sellers to think and adapt with confidence in the moments that matter most.

About the Author

Claudia Underhill was a Strategy Intern at Noodle Factory, where she supported AI-focused initiatives across Learning and Development, contributing to research, executive interviews, pitch materials, and article writing.

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