AI Tool Selection: Top 3 Considerations for Long Term Go-to-Market Impact & Value

In my view, the surge in new Generative AI tools for sales and marketing has resulted in many offerings that, while showcasing well-crafted engineering prompts and impressive UX/UI, often fall short of delivering sustained value. Tapping into a projected $1.3 trillion market by 2032, these tools frequently capitalise on the fact that many professionals are still learning how to harness AI effectively within their workflows. As the broader use of large language models (LLMs) evolves and marketers become more adept at crafting sophisticated prompts, these tools risk obsolescence if they cannot integrate seamlessly with core data sets or enable actionable insights that translate directly into tactical execution. For those who have already adopted these types of tools, the rapid pace of change and expectation will force us to pivot again. So, what should sales and marketing leaders consider when evaluating new Generative AI tools and applications?

Recent research by McKinsey shows that the biggest increase in Generative AI adoption is seen in marketing and sales, with adoption more than doubling compared to the previous year. Yet only a small percentage of use cases are fully integrated across functions, highlighting the need for deeper integration to achieve value at scale. As marketers' understanding and use of AI continues to grow, and as this acceleration quickens, so does the expectation of what a tool can deliver. For example, marketers have long strived for—and lamented—the ability to connect different attribution sources of data to provide a confident blueprint of insights from lead to order. This allows them to measure the impact of adjusting different levers, similar to how a business looks at their financial statements. Likewise, the outputs from extensive customer journey mapping or complex customer segmentation projects, will need to plug into the tech stack to enable immediate realisation of those insights.  Generative AI companies not considering how insights and outputs can instantly move to tactical execution, will die on the vine. 

When selecting an AI tool or technology today, sales and marketers should consider the following top three factors:

1. Integration Capabilities: Does the tool integrate seamlessly with your existing CRM, customer databases, and marketing automation platforms? A key factor for success is ensuring that AI can pull from and contribute to the core data systems within your organisation.  While there is significant merit and tangible benefits to be had from Generative AI tools that are disconnected technologically from your current tech stack, this should be a short-term strategy to assist in building a larger business case for an integrated solution that will do significantly more heavy lifting and have considerably more impact on growth over the long term.  We all know integration is not easy and takes significant cross-functional collaboration to achieve.  Look to your those who have already brought the current tech stack into your organisation and work with them to bring the next iteration of tooling to life.

   
   

2. Scalability and Adaptability: Bet that AI will unlock additional scale and growth and as such, start to look to the future (which is never far away with AI) as to whether the AI tool will evolve with you.  Look for tools that are not just tailored for current needs but can also adapt to broader use cases or increasing data demands in the future. Ask Generative AI vendors what their vision for their product is, what are the most commonly asked features their customers are asking for?  Lastly, ask yourself, how your expectations will change as you begin to unlock new capability. 

   
   

3. Human-AI Collaboration: This one is about value. We are uniquely positioned to be able to translate the question "Does the AI tool enhance human capabilities rather than replace them?". The best tools focus on augmenting sales and marketing teams, enabling them to make better decisions, and improving their efficiency without diminishing the need for human insight and connection. This not only benefits us as employees but has a knock-on effect in delivering better value for our existing and future customers.

   
   

Conclusion

The next time you see an ad or recommendation for a new Generative AI tool, remember a mention is not a recommendation and it's not personalised for whatever specific gap or opportunity you are wanting to solve for.  The key to making good decisions in leveraging these tools lies in thoughtful selection and long-term strategic integration that enhance both efficiency and value. Tools that lack the ability to integrate with core data systems or that fail to adapt to the changing needs of sales and marketing professionals will inevitably fall behind. By focusing on integration capabilities, scalability, and human-AI collaboration, you can ensure you are choosing tools that deliver against your broader strategy and goals.

If you’re ready to focus your G2M strategy and use AI to drive real results, AI JourneyFlow is here to help you cut through the clutter and focus on what really matters—optimising and speeding up your Go-to-Market (G2M) strategy. AI is a powerful tool, but it’s not the goal. The real goal? Finding the gaps and opportunities to make your G2M approach smarter and more efficient.