AI tools

AI tools have moved from novelty to necessity faster than most technology shifts. Growth teams that use them well get more done. Those that don't are increasingly at a disadvantage.

The challenge is cutting through the hype. Every week brings new tools claiming to revolutionise your workflow. Most are incremental improvements wrapped in breathless marketing. A few genuinely change what's possible.

This chapter focuses on AI tools that actually help growth teams. Not theoretical capabilities or demo-impressive features, but tools that make real work faster and better. Research that used to take days. Drafts that used to take hours. Analysis that used to require specialists.

The goal isn't to replace human judgment. It's to multiply human output by handling the repetitive, time-consuming parts so your team can focus on strategy, creativity, and decisions.

Research and analysis that used to take days now takes hours. Competitive analysis, market research, and customer review synthesis can be dramatically accelerated with the right prompts and tools.

First drafts of content free up time for editing and strategy. Blog posts, email sequences, ad copy, and social content can start from AI-generated drafts that you refine rather than blank pages you fill.

Data analysis and pattern recognition help you find insights in spreadsheets, survey responses, and customer feedback. AI can process volumes of text and numbers that would take humans days to review.

Brainstorming and ideation benefit from AI's ability to generate volume. When you need twenty headline options or fifty content ideas, AI produces starting points faster than any human brainstorm.

Quality of output matters more than feature count. The best AI tools produce work that needs light editing, not complete rewrites. Test with your actual use cases, not generic demos.

Context handling determines usefulness for complex tasks. Tools that remember context, accept long inputs, and understand nuance handle real work better than those limited to simple prompts.

Integration with your workflow reduces friction. AI that works inside your existing tools beats AI that requires copying and pasting between applications.

Privacy and data handling matter for business use. Understand what happens to your inputs, especially if you're working with customer data, competitive intelligence, or confidential strategy.

Start with your biggest time sinks. Where does your team spend hours on repetitive work that doesn't require deep expertise? Those are your best AI use cases.

Test with real tasks, not toy examples. AI demos are designed to impress. Run your actual workflows through the tool and see if it saves time in practice.

Consider the learning curve. Some AI tools require prompt engineering expertise to use well. Others work out of the box. Match the tool to your team's willingness to learn.

Watch for quality consistency. AI output varies. Sometimes it's excellent, sometimes it's subtly wrong. Build review processes before trusting AI for anything customer-facing or high-stakes.

ChatGPT is the default starting point. Wide capabilities, large context window, and the most third-party integrations.

Claude excels at longer documents, nuanced analysis, and tasks requiring careful reasoning.

Perplexity is best for research with sources. It searches the web and cites where information comes from.

NotebookLM is useful for working with your own documents - upload sources and ask questions about them.

Most teams end up using multiple AI tools for different tasks. That's fine.

AI tools are amplifiers. They make good marketers more productive and help teams punch above their weight. But they don't replace strategy, judgment, or creativity.

Start with one or two use cases where AI clearly saves time. Build competence and trust before expanding. The teams getting the most value from AI aren't using every tool available. They're using a few tools very well.