How to Integrate AI Into Marketing Workflows

As someone leading marketing and growth for tech driven businesses, AI isn't just a buzzword... it’s become an essential part of my workflow. From planning performance campaigns to streamlining content creation, AI tools have drastically improved my speed, accuracy, and creativity. Here’s how I’m currently using AI across my daily routine 𝗖𝗮𝗺𝗽𝗮𝗶𝗴𝗻 𝗣𝗹𝗮𝗻𝗻𝗶𝗻𝗴 & 𝗠𝗮𝗿𝗸𝗲𝘁 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 Tools like ChatGPT and Perplexity AI help me summarize market reports, extract insights from competitor ads, and validate campaign ideas. 𝘐𝘵’𝘴 𝘭𝘪𝘬𝘦 𝘩𝘢𝘷𝘪𝘯𝘨 𝘢 24𝘹7 𝘢𝘴𝘴𝘪𝘴𝘵𝘢𝘯𝘵 𝘧𝘰𝘳 𝘴𝘵𝘳𝘢𝘵𝘦𝘨𝘺 𝘴𝘶𝘱𝘱𝘰𝘳𝘵. 𝗖𝗼𝗻𝘁𝗲𝗻𝘁 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝗼𝗻 𝘄𝗶𝘁𝗵 𝗣𝘂𝗿𝗽𝗼𝘀𝗲 For ad copy, email subject lines, and landing page variants, I often start with AI-generated drafts (using ChatGPT + Jasper). 𝘉𝘶𝘵 𝘐 𝘴𝘵𝘪𝘭𝘭 𝘣𝘦𝘭𝘪𝘦𝘷𝘦: 𝘈𝘐 𝘢𝘴𝘴𝘪𝘴𝘵𝘴, 𝘯𝘰𝘵 𝘳𝘦𝘱𝘭𝘢𝘤𝘦𝘴. 𝘛𝘩𝘦 𝘧𝘪𝘯𝘢𝘭 𝘷𝘰𝘪𝘤𝘦 𝘢𝘭𝘸𝘢𝘺𝘴 𝘢𝘭𝘪𝘨𝘯𝘴 𝘸𝘪𝘵𝘩 𝘣𝘳𝘢𝘯𝘥 𝘵𝘰𝘯𝘦 𝘢𝘯𝘥 𝘩𝘶𝘮𝘢𝘯 𝘪𝘯𝘴𝘪𝘨𝘩𝘵. 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀 & 𝗔𝗱 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻 We use Looker Studio + AI driven analytics to analyze campaign performance across Meta, Google & LinkedIn. 𝘛𝘩𝘪𝘴 𝘩𝘦𝘭𝘱𝘴 𝘶𝘴 𝘱𝘳𝘰𝘢𝘤𝘵𝘪𝘷𝘦𝘭𝘺 𝘵𝘸𝘦𝘢𝘬 𝘢𝘥 𝘴𝘱𝘦𝘯𝘥𝘴 𝘣𝘢𝘴𝘦𝘥 𝘰𝘯 𝘙𝘖𝘈𝘚 𝘢𝘯𝘥 𝘈/𝘉 𝘵𝘦𝘴𝘵 𝘳𝘦𝘴𝘶𝘭𝘵𝘴. 𝗦𝗘𝗢 & 𝗔𝗦𝗢 𝗘𝗻𝗵𝗮𝗻𝗰𝗲𝗺𝗲𝗻𝘁 Tools like SurferSEO and Writesonic help refine keyword strategies and generate optimized blog structures, improving search rankings across web and app stores. 𝗦𝗼𝗰𝗶𝗮𝗹 𝗟𝗶𝘀𝘁𝗲𝗻𝗶𝗻𝗴 & 𝗘𝗻𝗴𝗮𝗴𝗲𝗺𝗲𝗻𝘁 With AI-powered tools like Sprout Social, Inc. and Brandwatch, we monitor sentiment, spot trends early, and automate responses to FAQs, especially during high-traffic campaigns. 𝘈𝘤𝘤𝘰𝘳𝘥𝘪𝘯𝘨 𝘵𝘰 McKinsey & Company’𝘴 𝘭𝘢𝘵𝘦𝘴𝘵 𝘳𝘦𝘱𝘰𝘳𝘵, 𝘮𝘢𝘳𝘬𝘦𝘵𝘪𝘯𝘨 𝘪𝘴 𝘢𝘮𝘰𝘯𝘨 𝘵𝘩𝘦 𝘵𝘰𝘱 3 𝘣𝘶𝘴𝘪𝘯𝘦𝘴𝘴 𝘧𝘶𝘯𝘤𝘵𝘪𝘰𝘯𝘴 𝘴𝘦𝘦𝘪𝘯𝘨 𝘵𝘩𝘦 𝘩𝘪𝘨𝘩𝘦𝘴𝘵 𝘷𝘢𝘭𝘶𝘦 𝘧𝘳𝘰𝘮 𝘈𝘐 𝘪𝘯𝘵𝘦𝘨𝘳𝘢𝘵𝘪𝘰𝘯. Source: https://lnkd.in/gj8fXwqP AI won’t replace marketers... but marketers who use AI will outperform those who don’t. If you’re not yet using AI to support your workflow, start small. 𝘌𝘹𝘱𝘦𝘳𝘪𝘮𝘦𝘯𝘵. 𝘓𝘦𝘢𝘳𝘯. 𝘐𝘵𝘦𝘳𝘢𝘵𝘦. #MarketingStrategy #PerformanceMarketing #DigitalMarketing #AIAutomation #Leadership #MarTech #FutureOfWork 

We rolled out AI across our team in 60 days. No chaos. No confusion. Just clear wins and real results. I've seen marketing departments jump into tools like ChatGPT and Claude without a plan, only to end up with inconsistent usage, security risks, and wasted time. So here’s a reality check: Giving your team access to AI tools is not the same as making them AI-ready. What works? A clear, structured rollout that builds confidence, protects your brand, and drives performance. Here’s the 7-step sequence I recommend getting your marketing team fully ready to use AI: 🔹 1. Leadership Alignment Before anyone writes a prompt, you need to answer this: → What are we actually trying to improve with AI? → Clarify your goals: content speed? campaign performance? lead quality? 💡Assign an internal AI Champion to lead adoption and make this someone’s job, not everyone’s maybe. 🔹 2. Create Your AI Usage Policy Yes, before the first prompt. Set ground rules: → No client data or credentials in tools → Human review before anything goes public → Approved tools only → A go-to person for AI questions 💡Keep it simple. A 1-page doc is better than a 20-page one no one reads. 🔹 3. Train the Team Don’t assume “digital native” means “AI fluent.” Run a short onboarding: → Demo real-world prompts for their roles → Share a centralized prompt library → Walk through how to use your company’s Custom GPT (if you have one) 💡Make it practical. Confidence creates momentum. 🔹 4. Start With Small Pilots Want to build trust in AI fast? Deliver small wins early. Assign 1–2 people per function to test real use cases: → AI for email writing → Content repurposing → Campaign briefs 💡Document results. Share what worked and build internal buy-in. 🔹 5. Bake AI Into Daily Workflows AI should enhance what already works. → Add AI to your content creation SOPs → Use it for meeting note summaries → Integrate it into campaign planning templates 💡The more friction you remove, the faster usage scales. 🔹 6. Build a Feedback Loop Set a bi-weekly or monthly check-in: → What’s saving time? → What’s confusing? → What should we expand next? 💡Refine as you go. This isn't a one-and-done rollout. It's a capability you're building. 🔹 7. Enable Long-Term Growth This isn’t just about productivity. It’s about transformation. → Encourage ongoing experimentation → Recognize team AI wins → Offer certifications or incentives to deepen adoption 💡You’re not just introducing a tool. You’re building a smarter, faster, more strategic team. ✅ Final Thought If you're leading a marketing team, you don’t need to rush into every AI trend. But you do need a clear path for AI readiness. Because the biggest risk today isn’t overusing AI. It’s being the last team in your category that doesn’t know how to use it well. ____________ ♻️ Repost if your network needs to see this. DM me if you need help creating an AI rollout plan for your team.

Testing and piloting AI for sales and marketing can be frustrating. That’s why Jomar Ebalida and I came up with the practical AI roadmap for marketing and GTM ops pros. This roadmap helps you figure out where to start, what to focus on, and how to scale AI initiatives in a way that’s grounded in operational reality. It’s structured in 3 phases: PREP: Evaluate your organization’s current state across data, tools, team skills, and funnel performance. PILOT: Select and test AI use cases based on your actual readiness data. (Diagram shows samples) Avoid guessing by letting the assessment drive decisions. ACTIVATE: Scale the pilots that show promise and embed them into core processes. Here are select projects worth walking through: 🔹 AI Readiness Assessment This project includes evaluating data quality, the state of your CRM, the maturity of your tech stack, and your team’s readiness to work with AI tools. It also includes a bowtie funnel analysis to help identify where your customer journey is breaking down. The outcome is a clear picture of which AI use cases are both valuable and feasible for your team to pursue. 🔹 AI SDR Agent: Outreach and Prospecting This agent is designed to support outbound sales by identifying high-potential accounts, generating personalized outreach messages, and helping SDRs scale without sacrificing relevance. It can help teams boost pipeline without overloading headcount. 🔹 AI QA and Compliance: Brand, Legal, Regulatory This workstream ensures that every piece of AI-generated content or decision logic meets the necessary internal standards. It supports brand consistency, regulatory requirements, and risk mitigation. This process should run in parallel with pilots and activations to ensure safe implementation. 🔹 AI Agents for Ops: QA Checks, Routing, and Campaign Setup This includes AI agents built to handle operational tasks such as verifying UTM links, auto-routing requests, or creating campaign templates. These agents are ideal for improving workflow speed while reducing manual errors and team bottlenecks. At the foundation of all of this is change management. Each phase of the roadmap includes a focus on enablement, training, adoption, metrics, and governance. Tools don’t generate value unless people are set up to use them properly. Which parts resonate with you? What would you change or add? PS: To learn more & access templates, subscribe for free to The Marketing Operations Leader Newsletter on Substack https://lnkd.in/g_3YC7BZ and to Jomar's newsletter at bowtiefunnel(dot)com. #marketing #martech #marketingoperations #ai #gtm

If it takes more than a week to launch, it’s not your first AI workflow. Don’t kick off a “big AI initiative.” Start with small, shippable wins and stack them. Three lanes to keep you sane: 1) Easy wins (60–90 minutes) → Form spam triage + proper routing → Waterfall lead enrichment into the CRM → Daily campaign digest to your inbox 2) Experiments (plug AI into what already works) → Classify inbound intent and trigger the next step → Automatic sales-call prep briefs sent to Slack → Press-mention monitoring with sentiment + alerts 3) Rethink the work (after you’ve earned trust) → Deal-desk approvals in Slack with clear ownership → Transcript → tasks → CRM updates (closed loop) → Closed-won signals to Slack with context for CS & Finance Build rules, then add AI: → Default to deterministic steps; use AI for extract / summarize / classify / write inside the workflow → Define the trigger, the “definition of done,” fields to update, and the owner → Ship weekly → review what moved a metric → keep what works, cut what doesn’t Month-one plan: Week 1: Form triage + routing; auto-enrichment Week 2: Call-prep briefs; meeting summary → tasks Week 3: Signal-based follow-up on high-intent actions Week 4: Deal-desk flow; closed-won → Slack with context Not flashy. Just consistent. Do this for 30–60 days and “AI in RevOps” stops being a project—it becomes how your system works. — 🔔 Follow Nathan Weill for no-fluff posts on automation, RevOps, and systems that actually ship. #RevOps #Automation #AI #GTM #SalesOps #MarketingOps #WorkflowDesign

Most companies buy AI tools and hope for transformation. A global leader in cybersecurity redesigned work itself. In less than 6 months, their marketing team trained 75 "trailblazers" and built 57 custom AI teammates (from 211 created during experimentation) now embedded into daily workflows. Now they're scaling it to more than 150 marketers. The big difference is they didn't bolt AI onto existing processes. They architected a layered "AI Network" where humans and AI collaborate by design. The results speak for themselves. The SDR team is saving 1-3 hours per day per rep with 2-3x better open rates (15% to 40%). Marketing team members are getting back 5-7 hours per week for higher-impact work. Four key insights that separated their success from companies that struggle: ➡︎ Partner with security from day one → They worked closely with their CISO to ensure every workflow was deployed safely. Security wasn't a blocker; it was foundational. ➡︎ Build infrastructure, not just use cases → GPT Tracker, AI Navigator, AI Triage System. Simple tools that prevent chaos as you scale. ➡︎ Systems beat tools → As their VP of Marketing Operations and AI transformation champion put it: "We don't just hand them an AI tool. We give them our decision tree, governance model, and proven workflows." ➡︎ Measure transformation, not just efficiency → Their SDR operations leader: "We're not just saving time. We're doing work that would never get done otherwise. That's the difference between efficiency and transformation." The company built 8 workflow layers (Foundation, Story/Campaign, Domain, Asset, QA, Human-in-the-Loop, Automation) with specialized AI teammates at each level—Audience GPT, Campaign GPT, Product GPT, SEO GPT, and more. AI tools give you short-term help. Systems give you long-term advantage. See the full breakdown in this week's newsletter below. For those who prefer audio, I've also created a 16-minute AI podcast version with two AI hosts (link in comments.) If you found this helpful, share it with other GTM leaders navigating their AI journey.

AI doesn’t replace marketers. It replaces marketing waste. Most teams are chasing AI productivity. Few are designing AI performance systems. Step 1: Map workflows, not tasks. When Coca-Cola implemented AI for creative concepting, they cut campaign cycles by 60% — but only after mapping human + machine collaboration. Step 2: Automate low-value approvals. HubSpot’s AI content ops reduced review times by 70% and freed 40% of creative bandwidth for strategy. Step 3: Use predictive insights to guide spend. Airbnb linked AI forecasting to paid media planning — boosting ROAS by 28% with fewer human inputs. Step 4: Upskill teams to manage the machine. Salesforce retrained 10,000 employees in prompt engineering to turn AI from tool into teammate. I’ve seen it firsthand — AI doesn’t scale output by working faster, but by working smarter with people. How are you using AI to multiply—not just automate—your team’s marketing performance? #AIMarketing #DigitalTransformation #Growth

If you’re starting from zero with AI, this is my step-by-step beginner’s guide to help you build a PMM AI workflow quickly, even with no tech skills: Because let's face it, while many posts here on LinkedIn are talking about advanced workflows, agents, n8n etc.... many of us are confused on where to even begin. The reality is you can start extremely simple with the right framework and create something of massive value. Here is my 4 step process: 1️⃣ Anchor to a business goal Start with strategy. Not “what can AI do?” but what does the business need right now? For example, if win rates are dropping because competitors keep undercutting you, your AI pilots should directly address bottom-of-funnel conversion. 2️⃣ Choose a focused use case Once the goal is clear, pick one workflow that maps directly to it. The mistake I see often is starting too broadly. “Product launch,” for example, isn’t a single use case; it’s five or six (research review, positioning, promo plan, enablement, content). No wonder teams get stuck. The temptation is to begin with things like positioning, the “big ticket” work. But those require the most human judgment (and a ton of stakeholder alignment). They are the easiest place for AI to fail. Start small on the left of the graphic below, prove value, then expand. 3️⃣ Define what “good” looks like Before writing a single prompt, map the structure of a high-quality output. For instance, if you are creating a competitive landing page, define the essential elements first: headline, proof point, differentiator, and CTA. Don’t rely on the tool you’re using to shape what good looks like. 4. Build in public, share, and iterate As you are building your workflow, document wins, refine prompts, and expand step by step. One client started with AI call summaries, then layered in objection handling, and only later tackled messaging. Each stage built credibility and confidence. If you want to see a complete example of this in action, read my latest newsletter in the comments. Happy AI building and DM me if you have any questions! What's an AI workflow you wanna build? #productmarketing #ai #coaching #Strategy

Most teams are excited about using AI, but no one wants another standalone app to manage. What they actually want is AI integrated into the tools they already use every day, especially HubSpot. Because that’s where the real impact shows. When a rep finishes a call and sees an instant AI summary right inside the deal record. When a marketer triggers a workflow and gets a personalized email draft without switching tabs. When the CRM updates itself instead of relying on someone’s memory at the end of a long day. Developers can build all of this today. HubSpot gives you the APIs, serverless functions, UI extensions, and workflow actions to embed AI exactly where teams need it, not as another extra step. In this week’s newsletter, we walk through how developers can build practical, AI-powered HubSpot apps that improve workflows, reduce friction, and make the CRM feel smarter with every interaction. #hubspot