Journey.ai

The future of AI in GTM, if you ask me: going from automation to true orchestration. The old GTM playbook? Too slow. Too reactive. Too human-dependent. AI is rewriting the rules, not just automating tasks but orchestrating entire revenue engines. Here’s where we’re headed: 1. GTM AI won’t just assist, it will orchestrate. Forget AI as a tool for isolated automation (like email sequencing). AI will oversee full buyer journeys, dynamically adjusting based on engagement, intent signals, and behavioral data. 2. Sales & marketing silos? Dead. AI will bridge the gaps, turning GTM into a unified motion where real-time data flows seamlessly from demand gen to deal close. No more handoff friction. 3. Buyers will drive the process, not sellers. AI-powered deal rooms will let buyers self-serve, co-create proposals, and navigate sales cycles at their own pace, with sellers stepping in when needed. 4. Cold outreach is evolving. Expect AI-driven, multi-channel GTM strategies that blend hyper-personalized messaging, predictive outreach timing, and real-time conversion insights. SDRs will spend 90 percent of their time in conversations, not chasing leads. 5 AI-powered revenue predictability. Forecasting won’t rely on gut feelings or static reports. AI will synthesize deal activity, pipeline health, and external market signals to deliver precision forecasting, helping leaders make data-backed decisions instantly. The winners in this AI-powered GTM era won’t just be the ones who “use” AI. It’ll be the ones who build AI into their GTM DNA. How is your team thinking about or using AI in your go-to-market motions?

A lot of prospects of ours think they don't have their data in order to start experimenting with AI... Companies expect AI to deliver insights, automation, and efficiency. Instead, they get conflicting numbers, duplicate contacts, and inaccurate forecasts. Why? Because every system holds its own version of the truth. Marketing’s MQLs ≠ Sales’ SQLs ≠ Customer Success’ churn risks. AI can fix this by creating a Universal Truth: 1. It pulls & unifies all data sources into a central pipeline. 2. It deduplicates and reconciles inconsistencies between systems. 3. It structures raw, unstructured data (emails, notes, calls) into meaningful insights. 4. It can transform data you have into data you think you don't have. Like product or technically-focused information to a problem-solution-impact framework. 5. It keeps data fresh with real-time updates—so reports never contradict each other. AI isn’t just about automation. It’s about data alignment. If your teams are working with multiple versions of reality, AI won’t work, until you fix the foundation. Does your company struggle with conflicting data sources? How is your data foundation?

How we build your foundation to experiment with AI? Here's how... 1. Connect all data sources: Ensure your AI assistant has access to CRM, support logs, knowledge bases, and internal documentation. 2. Create a semantic layer: Structure your data effectively to enable AI to understand context and relationships across various data points. 3. Train with company-specific data (RAG): AI is only as good as the data it learns from—customize it for your workflows and implement a Retrieval-Augmented Generation (RAG) system to ensure dynamic, context-aware responses. 4. Enable AI-powered search: Employees should be able to ‘talk to their data’ and get instant, accurate responses. 5. Implement data security measures and role-based data access: Ensure AI usage remains compliant and secure by managing access to sensitive information. Now you and the team can talk to the data. This isn’t just about streamlining workflows—it’s a perfect way to organize and structure your data first, setting the foundation for AI workflow experimentation and implementation. It also creates a strong data lake that other AI tools can pull from, ensuring they work with structured, accurate, and relevant information. A well-implemented AI assistant isn’t just a tool—it’s the starting point for AI-driven transformation in your organization. What’s the biggest challenge in making your internal data accessible? Let’s discuss AI solutions, together with my co-founder and CTO Nasir Shadravan. As a team, we bring together deep AI expertise with deep go-to-market knowledge, to help you experiment & implement AI, in your go-to-market.

When companies think about adopting AI, they often ask: “Where should we start?” But the real question is: “How can we start small and scale infinitely?” AI doesn’t deliver linear improvements. It delivers compounding, exponential gains when implemented strategically. Here’s why: 1. AI learns and improves over time → Start with a simple AI-powered lead scoring model for your sales team. → Over time, the model learns from every interaction, becoming more accurate. → Eventually, that same model can predict not just who will convert—but which behaviors drive long-term customer value. 2. AI scales across functions → Begin with AI to automate marketing content personalization. → Next, apply similar models to customer success for personalized onboarding and support. → Expand into RevOps with predictive analytics that forecast revenue trends across your pipeline. 3. AI orchestrates entire workflows → Deploy an AI assistant to answer routine questions. → Next, enable it to execute tasks like updating CRM records or triggering follow-up emails. → Over time, it becomes the intelligent command center for entire go-to-market workflows. This is the nature of AI: small seeds of automation grow into dynamic systems of intelligence. Companies that get this right start with focused experiments and then expand as results compound. The best part? You don’t need a massive upfront overhaul. Just one well-placed AI implementation can open the door to limitless optimization. Because AI isn’t a one-time transformation. It’s a continuous evolution toward more efficient, adaptive, and data-driven growth. With how fast AI is advancing, you then have that under your control - and can build further in that and completely customize every little thing, to your company and use case. Where could a small AI experiment create exponential impact for your team?

By the end of 2025, AI will deliver knowledge work at 1/40th the cost of human effort in Europe—€1–€5 per AI output hour vs. €40–€200 per human output hour. This isn’t a futuristic prediction. It’s already happening. AI isn’t replacing people—it’s eliminating repetitive, process-heavy tasks, so teams can focus on strategy, creativity, and relationships instead. ? Market Research: European analysts at €100 per hour take weeks to compile insights. AI tools scan millions of data points in seconds for under €5 per hour. ? Content Creation: A senior marketer at €80 per hour spends days crafting messaging. AI generates, personalizes, and optimizes in real-time for €3 per hour. ? Outbound Sales Prospecting: SDRs at €50 per hour manually research leads. AI qualifies leads instantly, letting reps focus on closing instead of chasing. ? Customer Support: A support rep at €40 per hour handles FAQs. AI chatbots resolve tier-1 requests instantly, improving response times and reducing costs. ? Data Analysis: Analysts at €200 per hour manually review reports. AI processes entire datasets instantly for €5 per hour. Meanwhile, your team is still stuck in manual-heavy workflows. This isn’t just about cost reduction—it’s about compounding efficiency and competitive advantage. ? AI-powered teams reduce CAC by 50%, automate 90% of research and data-driven decisions, and respond to leads in seconds, not hours. ? The companies that embrace AI-first workflows will scale exponentially, while those relying on manual processes will fall behind. The cost of human labor will never decrease. AI will only get better, faster, and cheaper. So the real question is: While you’re debating AI, your competitors are already closing deals with it. What’s your next move?

You have built incredible products with powerful features. But most customers never use them to their full potential. Why? Features get buried in complex menus. Documentation sits untouched in help centers. Onboarding stops after the first login. The result: Underutilized products, frustrated customers, and stagnant growth. That’s why more companies are embedding AI assistants directly into their products. These assistants don’t just answer questions—they guide, support, and empower users to get more value from your product. Here’s what that looks like: 1. Feature Discovery Customers ask, "What can I do with this tool?" and the assistant shows hidden capabilities they’ve never used—complete with tutorials and real-world examples. 2. Interactive Troubleshooting When someone says, "Why isn’t my workflow running?" the assistant diagnoses the issue, suggests a fix, and—if authorized—applies it automatically. 3. Actionable Insights Users ask, "How did my campaign perform last month?" and the assistant retrieves performance metrics from the data layer, without leaving the product interface. The impact goes beyond convenience. Shorter onboarding periods as customers learn by interacting, not memorizing. Higher feature adoption because guidance is embedded into the experience. Reduced support burden as routine questions get handled by AI. We spend so much time improving features. Maybe the next frontier is making those features more accessible through intelligent conversations. How easily can your customers unlock your product's full potential?

Sales used to be about volume. More calls. More emails. More meetings. But now? The winners are the ones who read the signals others miss. With AI, sales teams can: → Spot buying signals from website visits, content engagement, and competitor research → Identify at-risk deals based on sentiment shifts in conversations → Prioritize accounts showing intent signals—before they hit the pipeline But here’s the kicker, you can’t chase signals you don’t track. A workflow scan helps uncover: → Which signals you’re missing → Where data silos are costing deals → How AI can surface next-best actions automatically Sales isn’t about working harder. It’s about being smarter than the competition. What buying signals is your team overlooking today?

The AI landscape is exploding. Yet most teams haven’t even scratched the surface of what’s possible today... Here’s what we’ve found: → Sales leaders still forecasting deals based on intuition → Marketing teams missing out on in-market buyers → CS reps drowning in support tickets instead of proactively driving adoption The reality? AI can optimize these workflows today. But without a clear scan of your processes, it’s hard to know: → Where to start → What’s worth automating → Which tools will deliver real ROI When companies scan their workflows, they discover: → AI-driven ICP analysis that surfaces hidden market opportunities → Predictive revenue models that make forecasts more reliable → Customer health scores based on real-time product usage AI doesn’t replace teams. It frees them to do more. But first, you need to map the terrain. When was the last time you took a fresh look at your go-to-market workflows through the lens of AI? How are you currently implementing and operating AI in your GTW workflows today?

We could only hope for a product-market fit, less than 1 week after going public. Equally so for our strategy to bootstrap as an implementation partner to finance our MVP. What we want to build, is leaving people in awe - they love it. And how we will build it, starting as an implementation partner - can count on quite some love. You hope for it - but you can't count on it. Where people now respond to our service offering "This is exactly what we need right now". or "You're contacting us at exactly the right time". Look, folks, I'm a simple man. All I want is product-market fit, go-to-market fit, and some support with our bold vision to change the world. By allowing buyers (companies) to buy (via their stakeholders), the way they want to buy, in a B2B software setting (enterprise & mid-market) and allowing customers to create and experience their preferred buying journey - completely tailored to them (role, individual). How? That's still TOP secret - but we know how we're going to accommodate that experience and bridge with with the sales process on the seller's side. Completely putting it in the hands of a customer. Finally... Making us the only REAL buyer-led and controlled sales technology, because we start from a white page, focused on the buyer - not the seller. I don't want to destroy enterprise sales - I want to disrupt it into something it always should have been in the first place: buyer-led, controlled & focused. Thanks for buying our services as an implementation partner - it funds the development of our MVP.

AI Prompting is just barely scratching the surface... You ask a question, it gives you an answer, and that’s about it. Simple, right? But this is only the tip of the iceberg when it comes to AI's true potential. Imagine an AI system that’s custom-built for your business—not just answering questions, but integrating with ALL your tools and ALL your data sources. This isn't just about feeding it data, it’s about creating a powerhouse assistant that understands the context of your business and allows you to take action in real-time. Here’s why it’s a game changer: Total Integration: Your custom LLM connects seamlessly to your CRM, ERP, emails, databases, and so much more. It’s the central hub of your operations. Real-Time Decision Making: No more waiting around for reports or sifting through endless data. Your AI thinks in real-time, offering actionable insights, recommending next steps, and even executing tasks for you. Internal Efficiency: Teams can collaborate with the AI like a colleague—no need to dig through documents or wait for someone else to answer a question. It's like having a 24/7 expert on demand. Customer Experience Revolution: Imagine giving your customers an AI-powered platform where they can interact with the full breadth of your data—solving problems, getting personalized advice, and completing transactions without even needing a human. It’s time to stop thinking of AI as a “simple assistant” and start treating it as a strategic partner that powers your entire workflow. The future is not in just asking AI questions, but in integrating it into every aspect of your business. And the companies that get there first will have a huge competitive edge. The question is… are you ready to build the future of AI for your business? We'd love to build that for you, for internal use or for your customers to use.