The CRO Club
CRO Says Revenue Leaders Must Gut Their Playbooks On A Quarterly Basis To Keep Up With AI

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Key Takeaways
Impactful AI: AI can transform industries and improve lives, driving both business and societal advancements.
Lean Organization: Imubit employs a lean, ambitious team structure for expansive global growth in complex industries.
AI in Revenue: AI enhances pipeline scoring and insights, improving lead generation and revenue performance.
Human Decisions: Human oversight is crucial in AI-augmented operations, emphasizing context and accountability.
AI Adoption: Dive into AI workflows for better business visibility, but maintain scrutiny on AI output.
Tim Yandel - The CRO of Imubit
Tim Yandel is the CRO of Imubit, where he helps industrial companies navigate AI transformation. His career spans enterprise software, AI, computer vision, climate tech, and industrial AI, and he has played a role in helping numerous companies grow through significant market changes.
We caught up with him to hear how he's using AI to strengthen revenue motion. Here's what he had to say.
AI Can Be An Enabler Of Purposeful Impact
I’m a revenue leader who has spent over 20 years helping companies grow through significant market changes. My career spans enterprise software, AI, computer vision, climate tech, and now industrial AI, but purpose has always been the common thread. I’ve been drawn to businesses that challenge customers to think and operate differently, and trust a better way forward.
I am driven by the opportunity to make a real impact in the world and leave it better than I found it. I see disruptive AI as a powerful enabler of that impact, not just by transforming businesses, but by reshaping industries and improving the lives of the people and communities that depend on them.
A Lean And Ambitious Revenue Organization
Imubit, where I lead the revenue organization, is a growth-stage industrial AI company serving large process industry customers. We offer enterprise software with deployment services, driving strong expansion as customers add more applications, more sites, and broader usage over time.
The GTM org is a lean global team across sales, marketing, and partnerships. We go direct in markets with the strongest fit and use partners to extend our reach in other regions and verticals. It’s a land-and-expand model, focusing on creating value early, reducing friction to start, and growing alongside the customer.
We operate across North America, EMEA, APAC, and LATAM, with core focus areas including refining, petrochemicals, LNG, mining and metals, and biofuels and renewables.
Overall, it’s a lean but ambitious organization that wins complex enterprise deals and scales globally. I ensure we have the right structure, rhythm, and leadership to do so effectively.
How AI Enhances Revenue Leadership
Tim Shares
I believe a CRO has to keep reinventing the playbook, and if you want change to stick, you have to lead by example and get your hands dirty.
I am especially proud of leading an AI transformation initiative across the revenue organization. Our simple goal was to make sellers more effective by removing friction from their daily work. I believe a CRO has to keep reinventing the playbook, and if you want change to stick, you have to lead by example and get your hands dirty.
We embedded AI across the commercial motion — from content strategy and outbound sequencing, to reporting cadence, leaderboards, automated MEDDPICC call scoring, and customer dossiers that helped reps prepare faster and engage more strategically.
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The result exceeded mere efficiency. We freed sellers to focus on relationships, deal quality, and execution. We also created a culture where the executive team led from the front and modeled agency in their work.
That shift helped us triple pipeline generation. For me, that’s what great AI transformation looks like: Not just better tools, but better behavior, better leadership, and measurable commercial impact.
Why Decisions Belong To The Accountable Human
AI informs much of my revenue motion today, especially scoring, pipeline prioritization, trend analysis, and call or activity insights. But it does not make decisions. Humans always remain in the loop.
I use AI to surface patterns, sharpen visibility, and reduce the manual work of finding business signals. But AI can't do everything.
Humans remain firmly in charge of forecasting, pricing, territory decisions, customer strategy, and judgment calls that require context and accountability. AI’s job is to augment leadership, not replace it. It helps me make better decisions and be a better leader, but the decision itself still belongs to the person accountable for the outcome.
And you still need relationships, dot-connectors, and sellers who strategically position next steps within an organization, approach certain conversations, and use your internal team to help sell. You also need to know when to limit technical exploration and mitigate risk to avoid losing deals to indecision.
Over-relying on AI for everything reduces your impact, and while you seem more present, you are less aware. Just like anything, don't use AI as a crutch, but as an enhancer to your daily work.
Humans remain firmly in charge of forecasting, pricing, territory decisions, customer strategy, and judgment calls that require context and accountability…Over-relying on AI for everything reduces your impact, and while you seem more present, you are less aware.
How AI Enhances Pipeline Scoring And Insights
Let's dive deeper into the AI workflows I mentioned. The setup involves Claude Clay Coefficient Otter, all connected through MCP with Slack / Salesforce.
I have several use cases, but one involves Otter recording every call, mapping call content to the MEDDPICC framework, and pushing it to SFDC via Zapier — though this may change now that SFDC's MCP to Claude is available. Claude automatically crawls it daily, scoring the quality of MEDDPICC information from the transcript. This adds the MEDDPICC score to the opportunity page, which then feeds my forecast view.
This means we're dialed in and focused on the actions and decisions we need to make — without poring over the data for 60 minutes.
But it required tweaking along the way. Even if it initially seems right, you need to carefully watch and remain fully in the loop before letting it run solo. For example, we found that AEs lost a certain intimacy with deal knowledge for forecasting if they didn't input or verify certain fields, and changed the workflow accordingly.


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Why AI Accelerates Funnel Performance And Velocity
Overall, the most marked improvements I've seen have been in top-of-funnel / mid-funnel turn rates and velocity.
You can easily repurpose your content writing strategy, especially top of funnel — and with leave-behinds — which raises the standards buyers expect from sellers. This keeps pace with your win rates and conversions; if you do not incorporate these initiatives, your turn rates decline.
Additionally, every AE now receives a one-pager brief before a discovery call with a prospect, which contains brand and use-case assumptions solved for similar companies in their vertical. It has increased Disco > Demo conversion by 60%.
How AI Positioning Can Change Revenue Motion
I also shifted our GTM motion from replacement to practitioner empowerment. Companies did not see AI as a threat, but practitioners often did. They worried AI would reduce the value of their expertise.
We changed our approach. We positioned AI to enhance their existing tech stack, not replace it. We also built a model-builder community that let this persona engage directly, learn, and thrive with the technology. This created stronger practitioner buy-in, better adoption, and a healthier revenue motion because we generated pull not just from the top down, but also from the user level.
In short, we used our product to turn potential skeptics into builders, which strengthened the entire revenue motion.
Why You Need To Scrutinize AI Output
But remember, AI is always confident in its answers, so you need to scrutinize and maintain a detail-oriented mindset to avoid missing even the most minor nuance. LLMs are great natural sellers. They also do not provide critical feedback unless you specifically prompt them; be careful of LLM compliments, as they're not real but are meant to provide a dopamine hit.
Overall: LLMs are only as good as the prompter, so set the stage correctly, feed them the right information, and correct them often.
Build To Account For Constant Disruption
You have to continually disrupt your own sales playbook. The pace of evolution is increasing. Previously, a playbook could last mostly for 1-2 years without gutting it; now you have to do this seemingly every quarter.
That requires spending more time upfront on building the strategy's foundation, so while the layers above it may evolve and change, the bedrock remains solid.
Why Redesigning Business Plans For AI Is Essential
Further, you should rearchitect your entire business plan with AI in mind. Not necessarily because AI will replace all of it, but AI will augment a good portion of it, allowing you to be more effective and present in areas you weren't able to be before.
I've now had the freedom to take on a personal quota because I can leverage AI to do a lot of the operational work I previously had no time to do. This is a reawakening of what's possible, so CROs who've had success doing things one way will need to adapt or become quickly irrelevant to their peers.
Why CROs Must Dive Into AI Now
Here's my advice: Dive in, baby!
You gotta dive in and do it yourself. Don't expect someone to do it all for you, or you will find yourself completely left behind. The best CROs think
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