Turning plans into progress with AI marketing

Alex Clansey at Venture Planner suggests some innovative ways that startups can apply AI across their marketing efforts

 

AI has proved to be a reliable business partner for many startups. It steps in as a collaborator that tests ideas, uncovers opportunities, and supports decision-making, so entrepreneurs feel better equipped to succeed. Using AI to turn ideas into actionable business plans has already helped thousands of founders through practical, tailored planning tools that translate ambition into a clear path.

 

The opportunity that AI presents to fledgling startups is clear. Making the right choice of platform from the beginning will help mitigate risk over time. Opting for commercial platforms from the outset will pay off as workflows scale.

 

AI is proving to be invaluable in helping businesses take the very first steps. Structured, guided planning reduces guesswork, turns loose assumptions into numbers, and produces projections that are consistent from one section of a plan to the next. That means a founder who is unsure about financial forecasting or is writing a plan for the first time can still put together a credible model that can pressure-test scenarios and set realistic milestones.

 

The momentum continues once that initial plan is in place, because the same tools can adjust inputs and compare options to reveal how small changes can influence cash flow and runway. Confidence rises as the plan becomes something a team can follow day to day.

 

There is evidence that this shift is happening. A recent US Chamber of Commerce report found that 58 percent of small businesses now use generative AI, up from 40 percent in 2024, showing rapid mainstream adoption among the very companies that rely on planning to grow.

 

But once the business plan is put into action, how can business owners and entrepreneurs continue to utilise AI to evolve and grow their business? The judicious use of AI for marketing is likely to be critical here, especially in overcoming common challenges: from limited budgets to a lack of brand awareness.

 

 

Through the lens of marketing

Marketing is, of course, key for all fast-growing new businesses. A compelling brand story is vital because it differentiates the business and creates a strong emotional connection with customers. It communicates the startup’s mission, values, and unique qualities, making it more relatable and memorable.

 

A powerful brand story also builds trust and loyalty, encouraging customers to support and advocate for the brand. Ultimately, it helps the startup stand out in a crowded market and drives long-term success.

 

Marketing is often where the value of AI becomes most visible. In many businesses, it now underpins the creation of content across all social channels, tailoring messages to target audiences and managing all social media and paid advertising campaigns.

 

Across AI-based marketing activities, four broad applications tend to guide progress. Personalisation lifts relevance by mirroring how different customers speak and decide. A 2023 report from McKinsey highlights that “a use case in marketing is the application of generative AI to generate creative content such as personalised emails, the measurable outcomes of which potentially include reductions in the cost of generating such content and increases in revenue from the enhanced effectiveness of higher-quality content at scale.” 

 

Forecasting adds a planning layer that reads what has worked before and indicates where the next pound is likely to matter most. Automation connects the workflow, removing routine steps so teams spend more time with customers and the product. The result is a steady lift in quality and pace rather than a single big moment.

 

When it comes to choosing tools, investment tends to sit on a spectrum. Free or low-cost tools support exploration and learning. Commercial platforms add structure as collaboration, integration, and governance grow in importance. Custom elements suit situations where proprietary data or scale creates a real advantage. The trade-off is familiar: speed and flexibility on one side, control and assurance on the other. Treating the stack as a portfolio usually keeps options open while momentum builds.

 

Building that stack responsibly remains essential. Clear rules for data and privacy, human review for public content, and periodic checks for model or vendor drift help teams move quickly without unnecessary risk. Light governance supports experimentation while protecting brand and customer trust.

 

Often, the resulting progress looks incremental. Narrow scope, regular review, and measured expansion allow learning to compound while resources stay focused. As the signal strengthens, capabilities widen to more audiences, more channels, and deeper connections with existing systems.

 

Ultimately, strategy sets direction, and AI shortens the distance between plan and execution. Personalisation improves fit, targeting guides spend, forecasting informs the next move, and automation frees capacity. When these elements reinforce one another, early plans turn into operating habits, and operating habits support durable growth.

 

 

Bright prospects

Looking to the future, the potential of AI-enhanced marketing is significant. In its report, McKinsey estimated: “that generative AI could increase the productivity of the marketing function with a value between 5 and 15 percent of total marketing spending.”

 

In my view, that potential is most easily realised when a clear plan guides where AI is applied and how results are measured. With that foundation, marketing shifts from one-off campaigns to a reliable learning system that compounds over time. Businesses that maintain this rhythm tend to see steadier growth, more resilient brands, and more space to focus on what only they can do.

 

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Alex Clansey is co-founder of Venture Planner

 

Main image courtesy of iStockPhoto.com and NanoStockk