{"id":316626,"date":"2025-07-29T14:49:19","date_gmt":"2025-07-29T21:49:19","guid":{"rendered":"https:\/\/www.saastr.com\/?p=316626"},"modified":"2025-07-29T09:59:58","modified_gmt":"2025-07-29T16:59:58","slug":"ai-in-gtm-efficiency-the-playbooks-from-databricks-monday-com-and-benchling","status":"publish","type":"post","link":"https:\/\/www.saastr.com\/ai-in-gtm-efficiency-the-playbooks-from-databricks-monday-com-and-benchling\/","title":{"rendered":"AI in GTM Efficiency: The Playbooks from Databricks, Monday.com and Benchling"},"content":{"rendered":"<p>AI in GTM Efficiency: The Playbooks from Databricks, Monday.com and Benchling<\/p>\n<p><em>How three high-growth companies are actually implementing AI across their revenue operations \u2014 and what it means for your AI-informed GTM strategy today.<\/em><\/p>\n<p><img data-recalc-dims=\"1\" decoding=\"async\" class=\"size-full wp-image-316627 lazyload\" data-src=\"https:\/\/i0.wp.com\/www.saastr.com\/wp-content\/uploads\/2025\/07\/convomk-scaled.jpg?resize=1000%2C587&#038;quality=70&#038;ssl=1\" alt=\"\" width=\"1000\" height=\"587\" data-srcset=\"https:\/\/www.saastr.com\/wp-content\/uploads\/2025\/07\/convomk-scaled.jpg 1000w, https:\/\/www.saastr.com\/wp-content\/uploads\/2025\/07\/convomk-980x575.jpg 980w, https:\/\/www.saastr.com\/wp-content\/uploads\/2025\/07\/convomk-480x282.jpg 480w\" data-sizes=\"(min-width: 0px) and (max-width: 480px) 480px, (min-width: 481px) and (max-width: 980px) 980px, (min-width: 981px) 1000px, 100vw\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" style=\"--smush-placeholder-width: 1000px; --smush-placeholder-aspect-ratio: 1000\/587;\" \/><noscript><img data-recalc-dims=\"1\" decoding=\"async\" class=\"size-full wp-image-316627\" src=\"https:\/\/i0.wp.com\/www.saastr.com\/wp-content\/uploads\/2025\/07\/convomk-scaled.jpg?resize=1000%2C587&#038;quality=70&#038;ssl=1\" alt=\"\" width=\"1000\" height=\"587\" srcset=\"https:\/\/www.saastr.com\/wp-content\/uploads\/2025\/07\/convomk-scaled.jpg 1000w, https:\/\/www.saastr.com\/wp-content\/uploads\/2025\/07\/convomk-980x575.jpg 980w, https:\/\/www.saastr.com\/wp-content\/uploads\/2025\/07\/convomk-480x282.jpg 480w\" sizes=\"(min-width: 0px) and (max-width: 480px) 480px, (min-width: 481px) and (max-width: 980px) 980px, (min-width: 981px) 1000px, 100vw\" \/><\/noscript><\/p>\n<p>The AI transformation in go-to-market isn&#8217;t coming \u2014 it&#8217;s here. But unlike the broad promises we&#8217;ve been hearing, the real story is in the specifics. How are actual revenue leaders at scale implementing AI today? What&#8217;s working, what isn&#8217;t, and where should you focus your limited budget?<\/p>\n<p><span style=\"text-decoration: underline;\"><strong><a href=\"http:\/\/www.saastrannual.com\">SaaStr Annual&#8217;s AI Summit<\/a><\/strong><\/span> brought together three top GTM leaders who are pushing the envelope on AI implementation across their organizations, together with one a great VC to guide the convo:<\/p>\n<ul>\n<li><span style=\"text-decoration: underline;\"><strong>Sahana Sarma, Global VP GTM Strategy and Operations at Databricks<\/strong><\/span>, brings deep expertise in scaling revenue operations at one of the fastest-growing data and AI companies. She&#8217;s been instrumental in building Databricks&#8217; &#8220;Ask Mo&#8221; internal agent and driving AI adoption across their field teams.<\/li>\n<li><span style=\"text-decoration: underline;\"><strong>Rob Schmeltzer, Head of Strategic Customer Success at Monday.com<\/strong><\/span>, oversees customer success operations for the work management platform serving over 180,000 customers. He&#8217;s leading Monday.com&#8217;s implementation of AI-powered deal desk assistance and automated engagement mapping.<\/li>\n<li><span style=\"text-decoration: underline;\"><strong>Uri Ouziel, Global Head of Deal Management at Benchling<\/strong><\/span>, manages complex deal processes for the life sciences R&amp;D platform. His team has been pioneering automated CSM engagement tracking and customer intelligence aggregation at scale.<\/li>\n<li><span style=\"text-decoration: underline;\"><strong>Itamar Novick, Founder &amp; General Partner at Recursive Ventures<\/strong><\/span>, provides the investor perspective, having backed multiple AI-enabled GTM tools and witnessed the evolution from early promise to practical implementation across his portfolio companies.<\/li>\n<\/ul>\n<p>What emerged was a practical blueprint for how tech leaders are really using AI to drive efficiency gains.<\/p>\n<p><iframe title=\"AI in GTM Efficiency: The Playbooks with Databricks, Monday.com and Benchling\" width=\"1080\" height=\"608\" data-src=\"https:\/\/www.youtube.com\/embed\/1PIjiLX3j48?feature=oembed&#038;enablejsapi=1&#038;origin=https:\/\/www.saastr.com\"  allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" class=\"lazyload\" data-load-mode=\"1\"><\/iframe><\/p>\n<h2>The Foundation: Why Point Solutions Aren&#8217;t Enough<\/h2>\n<p>The first major insight that emerged was the limitation of point AI solutions. As Databricks\u2019 Global VP GTM Strategy noted: &#8220;I feel like a lot of the point solutions you see in AI are great, but that&#8217;s where they are. There are point solutions.&#8221;<\/p>\n<p>The companies seeing the biggest wins are those building on platforms they already have \u2014 leveraging Gemini&#8217;s integration with G Suite or ChatGPT&#8217;s API capabilities to create customizable, wide-ranging tools rather than adding another vendor to their stack.<\/p>\n<p><strong>The Monday.com Approach: Building Your Deal Desk Co-Pilot<\/strong><\/p>\n<p>Monday.com&#8217;s revenue operations team spent two quarters training Gemini to become what they call a &#8220;deal desk assistant.&#8221; Here&#8217;s how it works:<\/p>\n<ul>\n<li><span style=\"text-decoration: underline;\"><strong>Deal Intelligence<\/strong><\/span>: They feed Gemini their deals, playbooks, and connect it with their CPQ system<\/li>\n<li><span style=\"text-decoration: underline;\"><strong>Optimization Engine<\/strong><\/span>: The AI suggests optimal deal structures and pricing<\/li>\n<li><span style=\"text-decoration: underline;\"><strong>Efficiency Gains<\/strong><\/span>: Significant reduction in clicks and time-to-close for complex deals<\/li>\n<\/ul>\n<p>The key insight? They didn&#8217;t buy a new tool. They used an existing, already-adopted platform to solve a specific workflow problem. &#8220;When you can do it yourself using an existing tool that is already adopted and already integrated, it&#8217;s a great win,&#8221; the Monday.com leader explained.<\/p>\n<h2>Customer Intelligence: The New Competitive Advantage<\/h2>\n<p>All three companies have made customer research and intelligence a core AI use case, but their approaches vary significantly.<\/p>\n<p><strong>Databricks: The &#8220;Ask Mo&#8221; Internal Agent<\/strong><\/p>\n<p>Databricks built their own tool called &#8220;Ask Mo&#8221; that serves as an entry point into Salesforce, allowing their field teams to:<\/p>\n<ul>\n<li>Research customer organizational changes and triggers<\/li>\n<li>Identify next-best-product opportunities by analyzing similar customer patterns<\/li>\n<li>Generate executive briefing documents by pulling data across their entire stack<\/li>\n<li>Access consistent information quickly as they scale their team<\/li>\n<\/ul>\n<p>The tool aggregates information across their entire tech stack and serves it to field teams in a conversational interface. This isn&#8217;t just about efficiency \u2014 it&#8217;s about consistency and quality of customer interactions at scale.<\/p>\n<p><strong>The Research Stack Evolution<\/strong><\/p>\n<p>Beyond internal tools, field teams are using a combination of:<\/p>\n<ul>\n<li><span style=\"text-decoration: underline;\"><strong>Gemini and ChatGPT<\/strong><\/span> for content creation and analysis<\/li>\n<li><span style=\"text-decoration: underline;\"><strong>Perplexity<\/strong><\/span> for deep customer research<\/li>\n<li><span style=\"text-decoration: underline;\"><strong>Gong<\/strong><\/span> for deal intelligence, pipeline forecasting, and coaching insights<\/li>\n<\/ul>\n<p>But here&#8217;s what&#8217;s interesting: they&#8217;re not just using these tools individually. The real value comes from synthesizing insights across multiple platforms.<\/p>\n<h2>Operations Efficiency: Where AI Shows Immediate ROI<\/h2>\n<p>The operations use cases are where AI is delivering immediate, measurable value.<\/p>\n<p><strong>Benchling&#8217;s Automated Engagement Mapping<\/strong><\/p>\n<p>Benchling implemented Salesforce&#8217;s Agent Force to automatically categorize and log CSM engagements. Previously, customer success managers had to manually log every interaction. Now:<\/p>\n<ul>\n<li><span style=\"text-decoration: underline;\"><strong>Automatic Detection<\/strong><\/span>: The system identifies calls, emails, and activities across all systems<\/li>\n<li><span style=\"text-decoration: underline;\"><strong>Smart Categorization<\/strong><\/span>: Engagements are automatically categorized by type<\/li>\n<li><span style=\"text-decoration: underline;\"><strong>Time Savings<\/strong><\/span>: CSMs focus on high-value activities instead of data entry<\/li>\n<\/ul>\n<p>&#8220;Really just an example of trying to take manual repetitive things off of our team&#8217;s plates,&#8221; their CS leader explained.<\/p>\n<p><strong>Process Documentation with Scribe<\/strong><\/p>\n<p>Multiple panelists highlighted Scribe as a game-changer for operations teams. The ability to automatically document processes and turn them into sales enablement courses is &#8220;really impactful and saves a bunch of time.&#8221;<\/p>\n<h2>Data Enrichment and Prospecting: The Clay Revolution<\/h2>\n<p>Clay emerged as a standout tool across multiple companies, but not for the reasons you might expect. It&#8217;s not just about data enrichment \u2014 it&#8217;s about building custom workflows.<\/p>\n<p>Clay works because &#8220;it is not a point solution but integrates with a bunch of point solutions and enriches data, but you can build it into your own thing.&#8221; This flexibility allows revenue teams to create custom prospecting and account research workflows without heavy engineering resources.<\/p>\n<p><strong>Touchless Prospecting: The Holy Grail<\/strong><\/p>\n<p>Multiple companies are running POCs on touchless prospecting \u2014 using AI to generate and send prospecting emails without human intervention. But there&#8217;s a crucial caveat: &#8220;You still need to have some kind of human in the loop. We&#8217;re not yet at the point where things can go out customer-facing without some level of risk and quality control.&#8221;<\/p>\n<h2>Customer Intelligence at Scale: The Interpret Case Study<\/h2>\n<p>One of the most sophisticated implementations came from a company using Interpret to analyze customer communications at scale.<\/p>\n<p><span style=\"text-decoration: underline;\"><strong>The Challenge<\/strong><\/span>: They were excellent at understanding individual customer needs but struggled to identify trends across their customer base.<\/p>\n<p><span style=\"text-decoration: underline;\"><strong>The Solution<\/strong><\/span>: Interpret analyzes all customer communications to surface trends around product usage and feature requests, segmented by customer type.<\/p>\n<p><span style=\"text-decoration: underline;\"><strong>The Impact<\/strong><\/span>: This aggregated intelligence has &#8220;really helped our conversation that I have and my team has with our product organization.&#8221; Instead of anecdotal feedback, they now provide data-driven insights to product teams.<\/p>\n<h2>The Budget Reality: AI Isn&#8217;t Free<\/h2>\n<p>Here&#8217;s where the conversation got real. As one panelist put it: &#8220;We don&#8217;t necessarily have more budget. We&#8217;re already paying for all those tools, and the AI tools are incremental. They want more money, and I don&#8217;t have a budget.&#8221;<\/p>\n<p>This budget constraint is forcing companies to make strategic choices:<\/p>\n<p><strong>Build vs. Buy Decision Framework<\/strong><\/p>\n<ol>\n<li><span style=\"text-decoration: underline;\"><strong>Leverage Existing Platforms First<\/strong><\/span>: Can you solve this with ChatGPT\/Gemini integration rather than a new vendor?<\/li>\n<li><span style=\"text-decoration: underline;\"><strong>Focus on Workflows, Not Features<\/strong><\/span>: What specific process are you trying to improve?<\/li>\n<li><span style=\"text-decoration: underline;\"><strong>Measure Integration Costs<\/strong><\/span>: How much effort will it take to get this working with your existing stack?<\/li>\n<\/ol>\n<h2>Enablement and Assessment: The Underrated AI Use Case<\/h2>\n<p>Companies are using AI-powered platforms like Udely and Uplimit for sales enablement, but the real value isn&#8217;t just in content delivery \u2014 it&#8217;s in assessment and impact measurement.<\/p>\n<p>&#8220;We are using [these tools] to actually drive enablement and allow us to better assess&#8230; how does enablement really impact success?&#8221; This data-driven approach to enablement is helping companies optimize their onboarding and ongoing training programs.<\/p>\n<h2>The Glean Factor: AI-Powered Knowledge Management<\/h2>\n<p>Glean appeared in multiple companies&#8217; stacks as a solution for fast-scaling teams. As one leader explained: &#8220;We&#8217;re growing so fast, bringing so many people in. Glean is a pretty effective way for us to get information out to our field that&#8217;s consistent, especially from a content management perspective.&#8221;<\/p>\n<p>The key insight: AI-powered search and knowledge management becomes critical as companies scale beyond the point where tribal knowledge works.<\/p>\n<h2>What This Means for Your 2025 GTM Strategy<\/h2>\n<p>Based on these real implementations, here are the key takeaways for revenue leaders:<\/p>\n<p><span style=\"text-decoration: underline;\"><strong>Start with Integration, Not Innovation<\/strong><\/span> The companies seeing the biggest wins are building on platforms they already have rather than adding new vendors. Before buying a new AI tool, ask: &#8220;Can I solve this with our existing ChatGPT or Gemini integration?&#8221;<\/p>\n<p><span style=\"text-decoration: underline;\"><strong>Focus on Process Efficiency First<\/strong><\/span> The clearest ROI is coming from automating manual, repetitive tasks. Look for processes where your team is doing data entry, research, or documentation that could be automated.<\/p>\n<p><span style=\"text-decoration: underline;\"><strong>Customer Intelligence is the New Moat<\/strong><\/span> Every company is implementing some form of AI-powered customer research and intelligence. This isn&#8217;t optional \u2014 it&#8217;s becoming table stakes for competitive sales teams.<\/p>\n<p><span style=\"text-decoration: underline;\"><strong>Budget for Integration, Not Just Licenses<\/strong><\/span> The real cost isn&#8217;t the AI tool \u2014 it&#8217;s the integration work, training, and ongoing optimization. Budget accordingly.<\/p>\n<p><span style=\"text-decoration: underline;\"><strong>Human-in-the-Loop is Still Required<\/strong><\/span> Despite the hype, no company is comfortable with fully automated customer-facing communications. Plan for human oversight and quality control.<\/p>\n<h2>The Road Ahead<\/h2>\n<p>The AI transformation in GTM is real, but it&#8217;s more tactical than transformational right now. Leaders from Databricks to Monday are seeing significant efficiency gains, better customer intelligence, and improved process automation. But they&#8217;re also being strategic about where they invest and how they implement.<\/p>\n<p>The winners won&#8217;t be the companies with the most AI tools \u2014 they&#8217;ll be the ones who thoughtfully integrate AI into their existing workflows to solve specific problems. As these implementations mature over the next 12-18 months, the competitive advantages will become even more pronounced.<\/p>\n<p>The question isn&#8217;t whether to implement AI in your GTM operations. It&#8217;s how quickly you can start, and how strategically you can scale.<\/p>\n<p><iframe title=\"AI in GTM Efficiency: The Playbooks with Databricks, Monday.com and Benchling\" width=\"1080\" height=\"608\" data-src=\"https:\/\/www.youtube.com\/embed\/1PIjiLX3j48?feature=oembed&#038;enablejsapi=1&#038;origin=https:\/\/www.saastr.com\"  allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" class=\"lazyload\" data-load-mode=\"1\"><\/iframe><\/p>\n","protected":false},"excerpt":{"rendered":"<p>AI in GTM Efficiency: The Playbooks from Databricks, Monday.com and Benchling How three high-growth companies are actually implementing AI across their revenue operations \u2014 and what it means for your AI-informed GTM strategy today. The AI transformation in go-to-market isn&#8217;t coming \u2014 it&#8217;s here. But unlike the broad promises we&#8217;ve been hearing, the real story&#8230; <br \/><a class=\"more-link fade\" href=\"https:\/\/www.saastr.com\/ai-in-gtm-efficiency-the-playbooks-from-databricks-monday-com-and-benchling\/\">Continue Reading<\/a><\/p>\n","protected":false},"author":19,"featured_media":316627,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"","_et_pb_old_content":"","_et_gb_content_width":"","om_disable_all_campaigns":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2},"_wpscp_schedule_draft_date":"","_wpscp_schedule_republish_date":"","_wpscppro_advance_schedule":false,"_wpscppro_advance_schedule_date":"","_wpscppro_custom_social_share_image":0,"_facebook_share_type":"default","_twitter_share_type":"default","_linkedin_share_type":"default","_pinterest_share_type":"default","_linkedin_share_type_page":"","_instagram_share_type":"default","_medium_share_type":"default","_threads_share_type":"","_selected_social_profile":[]},"categories":[24898,31,24987],"tags":[],"class_list":["post-316626","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai","category-blog-posts","category-saastr-ai"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"https:\/\/i0.wp.com\/www.saastr.com\/wp-content\/uploads\/2025\/07\/convomk-scaled.jpg?fit=1000%2C587&quality=70&ssl=1","jetpack_shortlink":"https:\/\/wp.me\/p5oib2-1kmS","jetpack_sharing_enabled":true,"fifu_image_url":"https:\/\/www.saastr.com\/wp-content\/uploads\/2025\/07\/convomk-scaled.jpg","_links":{"self":[{"href":"https:\/\/www.saastr.com\/wp-json\/wp\/v2\/posts\/316626","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.saastr.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.saastr.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.saastr.com\/wp-json\/wp\/v2\/users\/19"}],"replies":[{"embeddable":true,"href":"https:\/\/www.saastr.com\/wp-json\/wp\/v2\/comments?post=316626"}],"version-history":[{"count":6,"href":"https:\/\/www.saastr.com\/wp-json\/wp\/v2\/posts\/316626\/revisions"}],"predecessor-version":[{"id":316633,"href":"https:\/\/www.saastr.com\/wp-json\/wp\/v2\/posts\/316626\/revisions\/316633"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.saastr.com\/wp-json\/wp\/v2\/media\/316627"}],"wp:attachment":[{"href":"https:\/\/www.saastr.com\/wp-json\/wp\/v2\/media?parent=316626"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.saastr.com\/wp-json\/wp\/v2\/categories?post=316626"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.saastr.com\/wp-json\/wp\/v2\/tags?post=316626"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}