Make It Happen Mondays Podcast · July 20, 2026
Agentic CRM is not a feature upgrade. It is a rethinking of what CRM is supposed to do for sellers, and why so many implementations have failed them instead. Ryan Braastad, product marketing leader at Microsoft across Dynamics 365 and Microsoft 365, has spent years at Forrester, Yammer, Salesforce, and his own startup watching CRM drift away from where sellers actually work. He and John break down what agentic CRM actually means, why AI adoption should start with one specific use case, and how moving CRM into the flow of work changes the revenue-per-seller equation.
About Ryan
Ryan Braastad is a customer-obsessed product marketing leader at Microsoft, where he works on product strategy across Dynamics 365 and Microsoft 365 to help shape the future of agentic CRM and AI-powered productivity tools for sales teams. His background spans Forrester, Yammer, Salesforce, and a self-founded fitness startup, giving him a cross-functional view of why enterprise software so often struggles to gain rep adoption and what it takes to change that.
Connect with Ryan: LinkedIn
What you’ll learn
- Why CRM is shifting from a system of record to a system of action
- How AI can support sellers inside the tools they already use every day
- Why CRM adoption has so often failed to give reps a clear benefit
- How sales leaders should think about revenue per seller as AI becomes part of the workflow
- Why AI adoption should start with one specific use case rather than a company-wide rollout
- What agentic CRM actually means and how it differs from bolting AI onto existing software
Why CRM became a system reps had to feed, not a tool that helped them sell
For decades, CRM has been designed around what leadership needs rather than what sellers need. Leaders want pipeline visibility. Finance wants forecast accuracy. Operations wants consistent data. Reps get a system that asks them to log calls, update stages, and fill in fields after every conversation, with very little in return. That is the core of the adoption problem: the value of CRM has flowed upward, not back to the people doing the entering.
Ryan’s experience across Forrester, Salesforce, and Yammer gave him a front-row seat to this failure pattern. The more fields a system requires, the less accurately they get filled in. Reps find shortcuts. Data quality degrades. And leaders end up with dashboards full of numbers that don’t reflect what’s actually happening in deals. The system of record became a system of burden.
The consequence for sales organizations is real. When reps don’t trust or use CRM, leaders can’t coach effectively, forecast accurately, or identify where deals are stalling. The tool designed to give leaders visibility ends up obscuring it.
What agentic CRM actually means
Agentic CRM is the shift from asking sellers to update the system to having the system do the work automatically, inside the tools sellers already use. Instead of logging a call from memory after a meeting, the call gets captured and summarized. Instead of manually updating opportunity stages, the system infers progress from email threads and meeting transcripts. The rep’s job becomes reviewing and correcting, not entering.
The “agentic” part matters because it implies action, not just analysis. A traditional AI bolted onto CRM can surface insights, but the rep still has to go somewhere to act on them. An agentic system takes actions on behalf of the seller inside Teams, Outlook, or whatever collaboration tool the team already lives in. The CRM comes to where the seller is, rather than requiring the seller to go to the CRM.
Ryan’s work at Microsoft focuses on building this into Dynamics 365 and Microsoft 365 together, so the boundary between communication tool and CRM begins to disappear. A seller preparing for a call doesn’t have to switch between tabs. The context is already there.
Why AI adoption in sales should start with one use case
One of the clearest points Ryan makes is that company-wide AI adoption rollouts rarely work. When every function is trying to use AI for everything at once, no one learns how to use it well, and the teams that needed it most end up with another underutilized tool. The better approach is to pick one high-friction workflow, solve it completely, and build from there.
For most sales teams, the highest-friction workflow is post-call admin: updating notes, logging activity, capturing next steps. This is where sellers lose the most time and where data quality breaks down most visibly. Starting with AI-assisted call capture and summarization gives reps something they immediately value, gives leadership better data without demanding manual entry, and builds the trust that makes broader adoption possible.
The alternative, a platform-wide mandate with no clear starting point, tends to produce the same results as every previous CRM rollout: adoption theater where reps click through the system without changing how they work.
Revenue per seller and what it means as AI takes on admin work
Sales leaders have always cared about revenue per rep, but the metric is becoming more important as AI changes the cost structure of a sales team. If AI handles a meaningful portion of the admin work a rep does today, that time theoretically goes back to selling. But it only goes back to selling if leaders are actively building the habits and skills that fill the freed-up capacity.
Ryan’s framing is useful here: AI adoption in sales is not just a technology question. It is a management question. Are managers using the better data CRM now produces to coach more specifically? Are reps using the time they get back to have better conversations, or are they using it to get off the phone faster? The tools can improve the inputs. Leaders have to make sure the outputs actually improve.
This is where investment in fundamentals matters. Reps who know how to ask better questions, run tighter discovery, and qualify honestly have something productive to do with the time AI frees up. Without the skills, the productivity gains don’t show up in revenue.
Frequently asked questions
What is agentic CRM?
Agentic CRM is a model where CRM software takes automated actions on behalf of sellers, rather than requiring them to manually enter data after every interaction. Instead of logging calls, updating pipeline stages, and writing notes by hand, the system captures and processes this information from meetings, emails, and calls automatically, inside the tools sellers already use. The goal is to make CRM something that works for reps rather than something reps work for.
Why has CRM adoption failed so often for sales reps?
CRM adoption has failed because most systems were designed around leadership’s need for data visibility, not around making sellers’ jobs easier. Reps are asked to enter information they often don’t benefit from, in systems that sit outside their normal workflow. Over time this creates shortcuts, degraded data quality, and dashboards that don’t reflect what’s actually happening in deals. Agentic CRM addresses this by making data capture automatic and by surfacing relevant information where sellers already work.
How should sales leaders approach AI adoption without losing control?
The most effective approach is to start with one specific, high-friction workflow rather than deploying AI across every function at once. Post-call admin, including note-taking, activity logging, and next-step capture, is typically the best starting point because it reduces burden on reps immediately and improves data quality for leaders simultaneously. Once one use case is working and the team has built trust in the tool, broader adoption becomes significantly easier.
What is the difference between a system of record and a system of action in CRM?
A system of record is where data is stored and reported on. Traditional CRM has been this: a database that captures what happened, after it happened, manually. A system of action participates in the workflow, surfaces information at the right moment, takes actions automatically, and helps sellers prepare for and execute conversations. The shift from record to action is what agentic CRM is designed to accomplish.
How does agentic CRM affect revenue per seller?
If AI handles a meaningful portion of the admin work sellers currently do, the time freed up theoretically goes back to customer-facing activity. But that productivity gain only materializes if reps have the skills and habits to use the extra time effectively, and if leaders are using the better data CRM now produces to coach more specifically. Agentic CRM changes the inputs. Leaders have to make sure the outputs, including actual revenue per seller, improve in response.
John Barrows helps sales leaders decide whether to replace or rebuild their teams for the AI era. For 25+ years he has worked with the world’s most demanding sales organizations, including Salesforce, LinkedIn, Google, Amazon, and Okta, building the frameworks that became Filling the Funnel and Driving to Close. He is the host of Make It Happen Mondays, author of I Want to Be in Sales When I Grow Up, and an LP at GTMfund.
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