Editorial
Research Report
The AI Transformation 100: Concrete Ideas for Fixing How We Work
Key Takeaways
- Sales teams already have valuable competency data, but much of it sits unused.
- Unused assessment data eventually shows up as irrelevant pitches, weak discovery and stalled deals.
- AI helps frontline leaders spot patterns faster so they can spend more time coaching behavior.
- Competency-based coaching becomes more scalable when development is tailored around each rep’s actual skill gaps.
The next major shift in sales will not come from automation. It will come from clarity.
For years the conversation around artificial intelligence in sales has focused on replacing tasks. Automating prospecting. Drafting emails. Writing follow ups. But the more profound impact is happening somewhere less visible: AI is finally making it possible to understand how workforce capability actually shapes the buyer experience.
Sales Has the Data — It Just Isn’t Using It
Most sales organizations are already sitting on the data that reveals exactly where their teams are breaking down. They're just not using it.
Across enterprise sales teams, competency assessments are run constantly. They are used during hiring, during onboarding and sometimes after large training initiatives. Reports are generated. Scores are logged. Dashboards populate somewhere inside HR systems or learning platforms.
Then the organization moves on. The problem is not the data. The problem is translation.
Managers rarely convert assessment insights into coaching actions. Most frontline leaders were never trained to move from a competency score to a specific development conversation. Without that bridge, managers default to instinct-driven coaching based on pipeline reviews and anecdotal deal feedback.
That gap between what the data shows and what managers actually coach quietly undermines both sales performance and customer experience.
Related Article: AI Has Changed Sales Prep — And Your Pitch Needs to Catch Up
When Coaching Gaps Become Customer Friction
Research from MHI Global and CSO Insights found that only about 21% of sales managers consistently use assessment data in their coaching conversations. The majority generate insight and then leave it unused.
From an operational perspective, that is inefficient. From a customer perspective, it is much more serious. Every competency gap inside a sales team eventually surfaces in the buying experience.
Weak discovery leads to irrelevant pitches. Poor stakeholder mapping leads to confused internal buying groups. Lack of executive presence leads to stalled deals and delayed decisions. What appears internally as a sales execution issue often shows up externally as friction in the customer journey.
Research from McKinsey & Company shows that modern B2B buyers expect the same level of contextual understanding and personalization they receive in consumer experiences. When sellers fail to demonstrate that understanding, trust erodes quickly. Deals stall not because buyers lack interest but because the buying process becomes unnecessarily difficult.
The irony is that organizations often already have the data explaining why this friction occurs.
The Real Problem Usually Starts Earlier in the Deal
Well-designed sales assessments measure competencies directly tied to deal progression. Not personality traits or vague leadership qualities, but specific capabilities that influence how deals move forward. Discovery discipline, stakeholder engagement, objection navigation, value articulation and qualification rigor all show up clearly in competency models.
When a rep consistently loses deals late in the sales cycle, most organizations assume the issue is closing technique. In reality, the problem usually started much earlier. Weak qualifications create fragile opportunities that survive early pipeline reviews but collapse when real decision making begins.
Competency assessments frequently reveal this long before revenue reports do. They show gaps in discovery behavior or stakeholder alignment that predict the eventual loss. Managers who understand how to read that signal coach discovery and deal strategy. Managers who ignore it often run another closing workshop that does little to address the root cause.
Research from Korn Ferry shows that sales professionals who receive coaching aligned with competency assessment results improve quota attainment nearly 30% faster than those receiving generalized feedback. The insight exists. The challenge has always been operationalizing it at scale.
This is where artificial intelligence is beginning to change the equation.
Related Article: Who Should Be Building Agentic AI Inside Your Organization?
AI Connects the Dots Sales Teams Keep Missing
For the first time, AI is connecting three streams of data that historically lived in separate systems:
- Competency assessments
- Deal analytics
- Conversation intelligence
When those signals are integrated, organizations can finally see how workforce capabilities translate into customer interactions in real time.
Conversation intelligence platforms such as Gong and ZoomInfo’s Chorus analyze recorded sales conversations to identify patterns in discovery questions, objection handling and stakeholder engagement. Revenue intelligence platforms like Clari and Salesforce’s Einstein track how deals move through the pipeline and where they stall.
When competency assessment data is layered into this environment, something powerful happens. Skill gaps that were once abstract suddenly become visible inside real customer conversations. A rep who scores low in discovery discipline shows calls where key qualification questions never appear. A rep with weaker executive communication skills remains stuck engaging mid level contacts instead of decision makers.
The system surfaces the pattern automatically. The manager’s role changes from interpreting data to coaching behavior.
AI Makes Competency-Driven Coaching Scalable
Research from Brandon Hall Group indicates that organizations integrating AI-driven coaching with competency data see dramatically faster ramp times for new sales hires and improved retention across their sales workforce. AI does not replace the human manager. It removes the analytical friction that previously made competency driven coaching impractical.
The Hidden Cost of Fragmented Customer Communication
Register
How Modern Marketing Is Exposing the Limits of Legacy CMS
Register
Why Some Dealers Are Pulling Ahead With AI
Register
Content Leaders Collective: Proving Content’s Business Impact
Register
This shift is reshaping how leading organizations approach workforce development.
Companies that treat assessment data as strategic intelligence apply it across the entire employee lifecycle. Hiring profiles are calibrated based on competencies exhibited by top performers rather than generic job descriptions. Platforms like HireVue and Pymetrics increasingly help organizations identify behavioral attributes that correlate with success before a candidate ever starts the job.
During onboarding, the same data informs personalized ramp paths rather than one-size-fits-all training programs. AI-driven enablement platforms such as Mindtickle and Allego can dynamically adjust learning modules based on the competency signals each rep displays.
Once those employees enter the field, the data becomes a coaching anchor. High-performing managers treat competency indicators the way physicians treat medical charts. They monitor specific signals over time, intervene when performance patterns change and adjust development plans based on evidence rather than instinct.
Team-Wide Skill Gaps Become Impossible to Miss
At the team level the insights become even more powerful. Aggregated competency data quickly reveals patterns that would otherwise remain invisible. If a majority of reps struggle with executive conversations, the issue is not individual performance. It is a training gap in leadership communication. If discovery discipline is weak across a region, the organization likely has a structural methodology issue rather than a talent issue.
What once looked like scattered performance problems becomes a clear workforce development roadmap. This is the deeper impact of AI in the sales workforce. It is not simply automating tasks. It is illuminating capability.
Sales leaders have always known skill gaps existed. What they lacked was the diagnostic precision to address those gaps efficiently. Artificial intelligence reduces that ambiguity. It allows organizations to see how workforce capability shapes the buyer experience with unprecedented visibility.
Research from Gartner suggests that companies integrating AI into sales enablement and coaching programs are already seeing measurable gains in both revenue productivity and customer satisfaction. When sellers improve, buyers notice.
Related Article: The Most Valuable AI Skill Is Restraint. Here's What That Looks Like
The New Sales Manager Needs More Than Instinct
Sales management is entering a more complex operating environment. Buying groups are larger. Decision processes involve more stakeholders. Customers expect deeper contextual understanding earlier in the relationship.
The managers who thrive in this environment will not be the ones who rely solely on instinct. They will be the ones who treat workforce intelligence the same way elite sellers treat customer intelligence.
Systematically. Strategically. As a competitive advantage.
Assessment data is not administrative paperwork. It is a diagnostic map of exactly where your team’s customer conversations are breaking down and what it would take to improve them.
For years that map existed but was difficult to read. AI is finally turning the lights on. The organizations that learn to use it will build smarter sales teams, stronger customer experiences and more resilient revenue engines. The rest will keep running pipeline reviews and wondering why the same problems show up every quarter.
Learn how you can join our contributor community.