How to Improve Discovery with AI?

To kick off 2025, we forecasted the three key success factors for sales-led GTM this year. Non-surprisingly, you should adopt AI to handle a significant portion of your sales process. Since then, the GTM Club has published an article about how AI is impacting qualification. Now we will explore another crucial part of the sales process, discovery.

From AI-powered call preparation and stakeholder mapping to real-time coaching and automated CRM updates, modern sales tools are transforming the discovery process. These AI tools and features help sales reps conduct more effective discovery by analysing customer data, providing live meeting assistance, and capturing key insights automatically.

Here, we list five ways companies can implement AI in their discovery stage.

AI-Driven Discovery Call Preparation

AI tools have revolutionised pre-call preparation by processing vast amounts of data to create more informed and targeted discovery conversations. These tools analyse various data sources, including CRM records, emails, LinkedIn profiles, and industry news, to generate predictive pain hypotheses and suggest tailored discovery questions. AI can break down company objectives and identify likely pain points, while also flagging contextual triggers, such as new executive hires, that may indicate specific needs.

AI can break down company objectives and identify likely pain points.

The impact of AI-assisted preparation is significant, particularly in reducing preparation time while enhancing the quality of meetings. It is now easier for sales representatives to enter discovery calls with personalised question lists and a deep understanding of the prospect's context, without spending a notable amount of time on research. Thanks to AI, there is no excuse to ask Level 1 discovery questions. This leads to more focused conversations, where real needs are uncovered more quickly, and buyers are even impressed by the demonstrated preparation. Having an AI as a research assistant ensures comprehensive preparation for every meeting.

While researching an account with AI can be started with a reasonably simple prompt to ChatGPT, more specialised options are available. For account research, check out Vainu and or Research agent from Outreach.

Call Transcription and Intelligence

One of the key AI applications in discovery is making data available through call transcripts and their analysis. AI systems transcribe meetings, generate summaries, flag key details such as pain points, identify patterns, and interpret customer needs. For CRM data capture, the AI can automatically extract key information from conversations, auto-fill structured fields, write meeting notes, and create follow-up tasks.

AI can automatically extract key information from conversations.

These AI tools dramatically improve discovery effectiveness by allowing sellers to focus entirely on conversations while AI handles note-taking. Sales teams can easily save 15-20 minutes per discovery call by eliminating the time spent on manual note-taking after each call. While AI is not (yet) a perfect assistant, call transcripts usually improve CRM records' quality.

Many tools combine both transcription and intelligence capabilities, for example, check out Gong and Fireflies.ai.

Real-Time Discovery Call Assistance

AI systems can actively analyse multiple aspects of the interaction during sales conversations, providing immediate assistance. AI can track changes in prospects' sentiment, response patterns, hesitations, recurring themes or concerns, and alignment with successful past conversations. Based on AI's observations, it can provide live, in-call support by surfacing relevant information, battle cards, and objection-handling tips when needed or specific topics arise.

AI can provide live, in-call support by surfacing relevant information, battle cards, and objection-handling tips.

First, AI can alert reps if they've missed essential questions or if customer concerns remain unaddressed, effectively providing real-time coaching. Second, through sentiment analysis, AI monitors conversation tone and engagement levels, detecting when prospects are losing interest or when specific topics cause adverse reactions. This allows reps to adjust their approach in real-time, such as asking re-engaging questions.

Many different vendors offer real-time call assistance. To mention a couple, both Pepsales AI and Clari have made on-call Copilots available to their customers.

Decision-Making Unit Mapping

A critical yet often overlooked aspect of the sales process is identifying and engaging the complete decision-making unit. AI is transforming this challenge by leveraging data sources to identify key stakeholders within a prospect's organisation. Through integrations with company datasets, AI tools can visualise complex buying groups, showing organisational hierarchies, departmental involvement, and engagement levels. The technology can proactively flag when important decision-makers are missing from the current engagement and suggest additional stakeholders to include.

AI can visualise complex buying groups, showing organisational hierarchies, departmental involvement, and engagement levels.

This capability significantly reduces the risk of single-threaded deals, where sales teams discover too late that key decision-makers weren't involved early enough. By enabling proactive engagement with all stakeholders during the discovery phase, AI helps create smoother consensus-building and reduces the likelihood of last-minute objections. This is particularly valuable for both enterprise sales teams closing large deals and SMEs selling to mid-market clients, as it helps identify technical evaluators and budget holders upfront, leading to more effective discovery calls and faster sales cycles.

The decision-making unit, or buying committee, can be mapped within various sales tools. Different AI-powered support is available, for example, from ZoomInfo and Humantic.ai.

Call Scoring & Coaching

AI-powered coaching systems are revolutionising sales discovery calls by evaluating call quality and providing actionable feedback. These systems utilise AI-driven scoring models to assess whether or not key discovery elements were covered, such as business pain, budget discussions, and decision-making processes, and analyse metrics like talk-to-listen ratios.

Sales reps receive personalised coaching on specific areas for improvement.

The impact of this technology is significant for both the performance of sales teams and individual sellers. Teams benefit from best practices and benchmark data made available to them. At the same time, sales reps receive personalised coaching on specific areas for improvement, such as asking more open-ended questions or articulating better value. Companies implementing AI coaching can gain notable improvements in win rates, with representatives able to refine their techniques within just a few calls, rather than requiring months of traditional training.

Several leading platforms offer these AI coaching capabilities. This is where Gong made a name for itself, while others, like Salesloft, have expanded into this space.

AI Maximises Value from Discovery Insights

After the discovery data is labelled correctly in the CRM, companies can leverage AI for personalised automation in several ways. AI tools can help tailor all future communications based on personality insights and preferences. For example, if AI analysis shows a decision-maker prefers big-picture discussions over technical details, future communications can be automatically adjusted to focus on outcomes rather than specifications.

In short, AI first makes discovered insights available and accessible in the CRM. Then, AI helps modern sales teams to leverage that same data through the sales process and the customer journey.

Have we overlooked any AI-powered tools or innovative applications of AI? Share your thoughts and experiences in the comments below.

Note: The GTM Club has no affiliation with the vendors mentioned in this article.