AI: from chaos to clarity

Sean Evers at Pipedrive describes what small businesses need from AI (and what they don’t)

 

AI emerged in business consciousness extremely rapidly. ChatGPT reached 100 million monthly active users in just two months following its launch, making it the fastest-growing application to achieve that milestone at the time. This is significantly faster than the internet itself, which took about 7 years to reach 100 million users.

 

Amid this AI hype cycle, perhaps even a bubble, many SMEs feel both intrigued and overwhelmed. AI ‘boosters’ claim it offers everything to everyone, right now, or perhaps ‘soon’. A degree of scepticism is helpful, as with all new technology paradigms which often take time to deliver on early promises.

 

The fact is that there are real-world use cases where AI can tangibly improve sales productivity and other key areas for SMEs and enterprises alike. As with any innovation, it involves making careful decisions about where to apply new technologies and how to measure their performance.

 

That’s why the introduction of AI in the sales process is a neat example – sales is already a highly measured, quantified, and analysed process, allowing careful before and after comparisons.

 

 

Practical uses for emerging tech in sales

Already, not long since vendors inserted AI within their solutions, AI can greatly improve performance and show rapid value in defined areas, like lead qualification, forecasting, and follow-up automation. These are a response to need: studies, including Pipedrive’s 2024/25 State of Sales and Marketing report, show that sales professionals often waste time on leads that won’t close. Only 57% of sales professionals hit their targets last year, a five-year low.

 

That’s a use case for features like AI-powered lead scoring and predictive analytics to support firms in focusing on high-potential leads while reducing time-consuming guesswork and cognitive load. That bodes well for the efficiency and effectiveness of the AI-supported business development exec.

 

As any tech-savvy exec can intuit, AI cannot and should not be positioned as a silver bullet for every business challenge. Many firms struggle not because they lack data, but because they lack the resources and skills to translate data into decisions. AI tools are only useful when they are explainable, easy to use, and demonstrably better than the manual processes they replace.

 

If execs struggle to explain and deliver on their current processes, it’s likely that AI is only going to supercharge them into a greater pickle.

 

 

Where can leaders succeed alongside AI?

Take forecasting. Human intuition is powerful but often biased by optimism or short-term pressures. Predictive models, trained on historic conversion data, can spot faint patterns that are invisible to even experienced professionals.

 

For instance, they may detect that deals over a certain size rarely convert unless a specific number of decision-makers are engaged. That kind of insight is valuable precisely because it helps teams redirect their limited time where it matters most. But it does rely on having access to great data, meaning that smart people must feed into ‘smart’ tech and oversee its output. AI will not be a sticking plaster over an existing bad process.

 

Automation can also reduce the friction of repetitive tasks. Following up with prospects is a classic pain point. It’s necessary, but often deprioritised. AI-driven reminders, automated personalisation of outreach, and scheduling tools can ensure that opportunities are not lost simply through human bandwidth limits.

 

This does not remove the human element from good sales technique. Properly used it supports people, ensuring they spend more time in the conversations that really count, being visible and growing their rapport and trust.

 

What AI cannot do, at least not effectively, is replace the judgment, empathy and relationship-building that underpins successful selling. People in general may seem predictable to a great sales pro, but each individual is not. SMEs that view AI as a partner rather than a replacement are more likely to see tangible gains, both dealing with more people and also treating each as an individual with more quality human time at the right moment.

 

 

Start with the challenge, not the solution

The real question for leaders is not ‘how do I use AI everywhere?’, but ‘where does AI clearly outperform what we already do, and where should we continue relying on skilled people?’

 

For small businesses, the roadmap to clarity lies in starting small, testing rigorously, and scaling only what works. AI should be judged by outcomes. That’s higher conversion rates, more accurate forecasts, and better customer retention, for example. The promise of technological novelty is what some AI boosters are really promoting, and that’s not a strategic, intelligent business investment.

 

The best AI strategy is not about chasing hype, but about quietly improving the fundamentals that keep a business growing.

 

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Sean Evers is VP of Sales & Channel Partnerships at Pipedrive

 

Main image courtesy of iStockPhoto.com and metamorworks