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Hannah Ajiboye is a marketing consultant who specialises in helping…
Digital marketing specialist Hannah Ajiboye explains how AI can be used to supercharge your sales and marketing function, without losing your brand personality.
Three-quarters of startups say that they are using AI. But the question is: are they really leveraging its advantage or just experimenting with it? Salesforce’s tenth State of Marketing report found that harnessing the power of AI is simultaneously the top priority and the top challenge for marketers globally. For SMEs, that tension is a competitive risk. Founders are under pressure to scale faster than ever with lean teams and AI looks like an obvious solution to this challenge. Understandably, they rush to bolt it onto everything, which misses the point.
Most are not failing at AI because they lack resources. They are failing because nobody has given them an honest, practical framework to get started, without losing what makes them human. The barriers to getting started are real, but they are not what most people think they are.
When asked about their adoption of AI, budget is often cited as a key barrier. Yet the most capable AI tools available today cost less per month than a single sponsored LinkedIn post. The real problem is that most smaller enterprises approach AI as a technology decision when it is actually a workflow design decision. Too many ‘AI newbies’ start using digital tools before they have properly defined the problem they want to solve. This approach often sees businesses simply automating chaos rather than eliminating it.
Then there is the data problem. According the research, only 26% of marketers are completely satisfied with their data unification. For startups with disconnected tools and inconsistent processes, this matters enormously. An AI system is only as intelligent as the data feeding it. Get that wrong and you do not get efficiency; you get confident errors on a significant scale. So where does AI actually earn its place in an SME’s go-to-market engine?
There are four areas where the impact of effective AI is immediate and measurable within the sales and marketing function. The first is prospect identification and lead research. AI can identify the right targets, build contextual profiles and even brief your sales team before a single conversation takes place. The result is outreach that feels considered rather than generic. In the early-stages of selling this makes the difference between a reply and silence.
Then there is sales funnel management. Most startups lose deals, not because of poor product fit, but because follow-ups slip and momentum dies. AI can monitor pipeline signals, prioritise actions, and keep deals moving without depending on manual CRM discipline that busy founders rarely maintain.
The third is content and demand generation. Salesforce’s research found that 78% of marketers need more personalised content than they can currently produce. For businesses with lean teams, AI-powered content workflows close that gap, enabling consistency without a full creative headcount. The fourth area where AI really adds value is revenue operations. Connecting data across your tools gives you a real-time picture of pipeline health, without the overhead of a dedicated revenue operations function.
The efficiency gains across all four of these areas are real. But they come with a trap that too many startups fall into, often without realising it until the damage is done. When enterprises automate too aggressively, it can strip the human judgment out of processes that actually depend on it. Outreach becomes formulaic and meaningless. Content loses its point of view. And prospects stop responding, not because the product is wrong, but because they can feel they are being processed rather than engaged.
Customers want a two-way dialogue with the brands they buy from. That desire does not disappear because you are a startup. If anything, it is heightened. Early customers are choosing you over a safer, more established option. What they are buying, at least in part, is the relationship. Great marketing is about the human touch. Technology simply makes that process more efficient. AI should be doing the heavy lifting in the background so that your people can show up more present, more prepared and more human at every customer-facing moment.
The moment AI adoption starts reducing the quality of your customer experience, you have crossed the line from efficiency into erosion. So how do you get the balance right from the start?
The simple answer is: audit before you automate. Identify where time and revenue are leaking before you reach for a tool. The problem you solve first should be the one costing you the most. Start with one workflow, not a transformation. Pick the single highest-friction process in your GTM motion and fix that. Prove the value, then build outward.
Clean your data before you connect your AI. It is the reason most AI implementations underdeliver. Your outputs will only ever be as reliable as the data behind them. Keep a human in the loop at every customer-facing touchpoint. Automate the preparation. Let people own the conversation. And finally, measure output quality, not just output volume. More content, more emails, and more outreach mean nothing if the standard is falling.
Every startup in 2026 has access to broadly the same AI tools. That access is not your competitive advantage. What you do with it is. The businesses that will win are not the ones running the most automations. They are the ones using AI to free up more time, energy and attention for the relationships and decisions that only humans can handle well.
You might say, AI handles the ‘boring stuff’, while people bring the strategy, the empathy, and the finer judgment. That combination, when it is working properly, is extraordinarily difficult to compete with. The technology is ready. The question is: are you using it properly?
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