By 2025, AI has moved from experimentation into everyday use across many organisations. What had previously been tested in pilots or isolated teams is now embedded into how work is done, including across growth, marketing, and go-to-market (GTM) teams. 

2025 is widely seen as the year AI moved from curiosity and cautious pilots into the operational fabric of businesses. While many organisations are still scaling AI, a much larger share are now using AI tools regularly. This marks a shift from early experimentation to routine use, particularly in marketing and go-to-market functions. 
(Source: McKinsey, State of AI 2025) 

Growth and marketing teams have been among the first to adopt AI to make their work more focused and reduce time spent on routine tasks such as administration, data collection, analysis, and manually pulling insights from multiple sources into useful diagnostics that advance projects. Teams are using AI to handle time-intensive tasks so human effort can stay focused on higher-value strategic work. 

McKinsey’s 2025 State of AI report found that organisations are using AI tools to automate repetitive work and support knowledge work, enabling teams to shift focus away from manual tasks toward more strategic activities. 

With this shift, teams are under pressure to move faster and do more. Timelines are shorter. Output is expected sooner. The assumption is that if AI is involved, results should come quicker. But speed and scale do not guarantee quality. 

AI can accelerate execution, but it cannot fix unclear go-to-market strategy. Expecting AI to solve problems it was never designed to solve introduces real risk. Without clear direction and thoughtful inputs, AI simply speeds up execution without improving outcomes. 

What AI Actually Does Well in Go-to-Market Execution 

PiWhen used correctly, AI is genuinely useful in GTM execution. It can: 

This is where most go-to-market teams see immediate value from AI. 

But there is a caveat. 

AI can produce content at scale, but relevance can drop without human judgement. Outputs still need validation and refinement. When content is generated quickly and in volume, inconsistencies are more likely, and flaws can become harder to spot especially when they are buried in long or generic outputs. 

This shows up in very practical ways: a positioning statement that sounds fine on the surface but does not reflect how buyers actually talk. Persona-based content that reads well but misses real buying context. Campaigns that look busy but do not move pipeline forward. 

AI-generated outputs are only as good as the inputs behind them. 

How AI Exposes Gaps in Go-to-Market Strategy 

In many organisations, AI becomes a blocker to developing high-quality, relevant go-to-market plans, not because of the technology itself, but because of gaps in GTM foundations. 

These gaps often include: 

When these gaps exist, AI does not hide them. It amplifies them. 

When AI Becomes an Accelerator, Not a Risk 

AI works best when alignment and clarity are already in place. 

Clear audiences. Shared definitions. Agreed priorities. A common view of what progress looks like. 

When these inputs are strong, AI supports focus on the right areas. Outputs feel more consistent. Content reflects not just strategy, but customer reality – their world, their challenges, and the problems they are trying to solve. 

This is also where human judgement matters most. AI does not replace thinking. It replaces time spent typing notes, copying content, pulling quotes, and doing manual administrative work. That shift frees up space for experts to think, challenge assumptions, and structure ideas in a way that actually makes sense. 

What to Consider Before Using AI in Go-to-Market Strategy 

Before expecting AI to improve GTM outcomes, teams need alignment on a few fundamentals: 

AI is not a shortcut to strategy. It is a mirror of how clear your go-to-market thinking really is. 

When focus is strong and insight is solid, AI becomes a powerful support for GTM execution. 

When they are not, it simply exposes the gaps faster. 

Summary 

AI can accelerate go-to-market execution, but it does not replace strategic clarity. It reflects how well positioning, ICPs, priorities, and success measures are defined and aligned across teams. 

With a strong GTM foundation in place, AI helps teams move faster from ideas to execution, producing outputs that are more consistent, relevant, and grounded in real customer needs. Without that foundation, AI exposes gaps rather than solving them. 

This is why clarity and alignment matter more than speed when applying AI to go-to-market strategy.