The Smart AI Playbook: Balancing What You Have with What Else

Up until recently, AI for GTM professionals has been about streamlining repetitive tasks and improving efficiency within workflows. Most of us are still figuring that out, whether in our products, operational processes, or customer interactions. But today, AI is no longer just a productivity tool. It has become an intelligent backbone, seamlessly driving decision-making and execution across organisational ecosystems.

This transformation is being led by organisations like ServiceNow, Salesforce (Agentforce), and Microsoft (Copilot), which are embedding AI not just as an assistant, but as an orchestrator, making real-time decisions, automating entire workflows and fundamentally changing how businesses operate.

For GTM leaders, this shift means AI adoption is no longer about experimentation with LLMs or better prompt engineering. Instead, AI is evolving into a dynamic execution engine, powered by your own data sources, significantly increasing your ability to drive decisions and automate key processes. If it feels like your head is spinning on a 350-degree loop, you’re not alone. So, where to from here?

While the answer isn’t as simple as "use what you have", it’s certainly a smarter starting point. AI’s rapid evolution has vendors racing to integrate new capabilities, defending their market share to maintain customer retention or differentiate from AI-first competitors. This competition benefits GTM teams because it gives us the opportunity to step back from the “magpie syndrome” of chasing every shiny new AI tool and ask a more strategic question, “Are we fully leveraging the AI already embedded in our existing tech stack?”

Optimising and building upon your existing AI investments isn’t just about reducing costs, it’s a competitive advantage.

That said, this isn’t to discredit emerging AI players. Many have successfully introduced capabilities we didn’t even know we needed, pushing the boundaries of what’s possible. However, some have thrived simply because AI literacy is still developing. These businesses will likely have a short shelf life, as major SaaS vendors with deep pockets and extensive customer bases reclaim their ground.

The real shift? The vendors we’ve built our tech stack on are now taking on the burden of learning and AI adoption, allowing GTM teams to jump straight into directing and governing AI agents rather than figuring it out from scratch.

Enterprise vs SMB: A different future for GTM tech

Historically, enterprise technology stacks had a significant advantage over SMB solutions offering deeper integration, scalability, and AI-driven automation that SMBs couldn’t afford. But AI is changing that dynamic.

1. Enterprise vendors may soon offer lower-cost, non-customised AI solutions for SMBs. If AI is embedded in the core of enterprise-grade platforms, why not package and price it for smaller businesses that don’t require deep customisation?

2. SMBs now have access to AI-powered capabilities once reserved for enterprises. AI-driven automation, predictive analytics, and hyper-personalisation tools are now within reach for SMBs, allowing them to compete on equal footing.

   
   

The future of GTM technology may see a convergence where AI-powered platforms become scalable for businesses of all sizes.

Software vendors must do more than sell and users must do more than consume

One of the biggest gaps in AI adoption is enablement. While vendors are focused on recurring revenue, there is a shift happening with their customers.

Emerging AI native technologies are easy to trial, adopt and present capabilities that weren’t accessible just months ago.  This presents an opportunity for organisations with long-standing vendor relationships to engage on maximising the learning and education opportunities offered or challenging those with limited customer engagement models.

Many software vendors do invest in educating customers on how to evolve their GTM strategy with AI but that doesn’t mean the buying group (users, decision makers, influencers) know about it or are actively engaging in it.  As the noise around new AI tooling gets louder and GTM professionals are forced to consider a new approach to their own workflows, existing technology vendors then must defend their position. As a consumer of their technology, you need to play your part and truly partner – enabling your teams and your buying group to be in the best position to consider existing and new tooling.

Some vendors are getting it right:

• HubSpot: Provides free AI-powered education tools and courses to help businesses implement AI in marketing and sales.

• Salesforce (Trailhead AI Courses): Offers interactive learning paths to train users on AI-powered customer engagement.

• ServiceNow (Now Learning Platform): Educates enterprises on AI-driven workflow automation to ensure full utilisation of embedded AI features.

The opportunity for vendors and customers reflects true partnership and long-term loyalty.

GTM Quick Checklist in Assessing New AI Tools

Rather than chasing new tools, GTM leaders should take a deliberate and strategic approach:

1. Assess AI in your existing tech stack: Audit what’s already embedded in your CRM, marketing automation, and service platforms.

2. Push vendors to enable: Ask vendors not just what AI capabilities they have, but how they can help your team adopt and apply them effectively.

3. Optimise before expanding: Leverage that enablement by testing, learning and iterating.  Adoption, despite thorough enablement, will always be patchy across teams so pilot with AI adoption champions first.  Test, learn and iterate before adopting broadly.

4. Adopt a hybrid mindset: Leverage the AI you already have while staying informed about emerging capabilities that could offer a competitive edge. Easier said than done, but once you start actively using what’s already embedded in your stack, it becomes clearer which additional capabilities will genuinely add value.

5. Experiment with new: Emerging AI tools typically come with a free trial for no obligation exploration.  Integration should be a key criterion, when assessing fit beyond the core capability, so start there.  If you are leveraging these tools in isolation of your core tech stack, ask yourself if this will help you achieve your goal in the short and the long term.  It may be good for today but is not scalable if it delivers on expectations.

6. Think like an Enterprise, act like an SMB: Regardless of your company size, AI is creating a level playing field.  New tooling also requires adaptability and nimbleness and requires us to consider our data sets and how they connect.  While this can feel painful, it can deliver immeasurable benefits over the long term.

AI’s role in GTM is evolving fast. The businesses that succeed won’t be those that simply use AI, but those that embed AI strategically, leverage vendor education, and stay agile in adopting new capabilities.

Ready to explore the potential of an AI-driven G2M strategy? AI JourneyFlow is here to help you.  Whether you or your teams would benefit from Generative AI education, facilitating team workshops to identify gaps and opportunities in your G2M approach or helping you unpack a solution, AI JourneyFlow can support you.