AI search is changing how customers discover, compare, and trust providers, and it’s pushing marketing and sales teams to prioritise clarity, proof, and human reassurance over chasing traditional rankings or reach.
Search used to follow a familiar pattern. Someone typed a few keywords into Google, clicked a couple of links, and slowly stitched together an answer. Marketing teams focused on rankings, which often performed well. Sales teams waited for the phone to ring, and for many, it did.
However, that model is being gradually rewritten. AI-powered search tools are changing how people research services, compare providers, and decide who to trust. For growing UK businesses, the shift affects visibility, lead quality, and the expectations prospects bring into sales conversations.
AI search refers to tools that use large language models to generate direct answers to questions, rather than returning a list of links. People ask a natural question and receive a summary that feels confident, structured, and reassuring.
For leaders, the practical question is simple. If customers increasingly receive the “best answer” before they ever visit your website, how do you make sure your business is represented accurately and credibly?
In our UK research (May 2025), 68% of SME decision makers say they’re either fully embracing AI (28%) or selectively adopting it for key use cases (40%). Only 12% say they have no usage and no plans.
Source: Moneypenny UK research, fieldwork 30 April to 6 May 2025, n=750. Percentages shown are rounded for readability.
Buyers are asking fuller, more conversational questions, particularly when the problem they’re trying to solve is operational rather than purely informational.
Instead of searching for a generic phrase, customers now ask things like “what are the top 10 garages in my area”, “where can I find a physiotherapist specialising in….”, or “can you give me recommendations of the best providers to help solve this problem”.
AI search tools respond well to that kind of intent. They synthesise the problem, outline likely solutions, and often set expectations about what a good provider should offer. The result is fewer touchpoints, but deeper ones.
It also changes what “research” looks like. Prospects may not compare five different websites. They may take a single AI-generated summary, shortlist one or two providers, and then move straight into enquiry mode.
Traditional SEO rewarded scale. More pages, more keywords, more backlinks. AI search is less impressed by volume and more drawn to coherence.
AI systems look for clear, consistent explanations of a topic, signals of expertise, and evidence that a business understands the problem it claims to solve. They also pull signals from beyond your website, including reviews, third-party mentions, and content that shows up across the wider digital ecosystem.
For marketing teams, that shifts the centre of gravity. Clear service pages, grounded FAQs, and transparent “how it works” content often do more heavy lifting than clever campaigns. When your story is joined up, it’s easier for AI systems and humans to follow.
In practical terms, AI search makes fuzzy messaging expensive. If your website, reviews, and sales story don’t align, AI summaries can amplify that confusion and pass it to the prospect before you ever speak.
One of the most noticeable impacts of AI search is how it changes enquiry behaviour. AI-guided discovery tends to filter out casual browsers. Prospects who make contact are often better informed and more specific about what they need.
That can mean fewer leads overall, but a higher share of higher-intent enquiries. And for senior decision makers, that matters because it changes how success should be measured. The headline number of leads becomes less important than lead readiness and conversion quality.
This is also where operational support becomes part of the marketing conversation. If prospects are arriving better informed, you need the infrastructure to handle them well, quickly, and consistently.
That’s one reason why virtual receptionist and lead management services can have a quiet but meaningful role in performance. Not as a marketing add-on, but as the practical layer that ensures high-intent enquiries are handled in a way that builds trust rather than leaks opportunity.
In an AI search world, customers often arrive ready to act. A simple review of how calls and leads are handled can uncover easy wins, especially around responsiveness, clarity, and follow-up.
Sales conversations now begin with more context. Prospects may reference what they’ve read in AI summaries, ask sharper questions, and arrive with assumptions about what “good” looks like.
This can be a real advantage. Less time is spent explaining the basics. More time is spent diagnosing needs and shaping the right solution. But it only works if marketing and sales are tightly aligned.
It’s also worth acknowledging that AI-generated summaries are not always perfect. If a prospect believes you offer something you don’t, or misunderstands how a service works, the conversation can start with friction. The antidote is not more persuasion. It’s clearer framing and consistent language.
That consistency is also supported by operational services that capture intent and context properly, which is another reason a structured approach such as utilising a lead management service can shift the dial. It helps ensure the conversation stays relevant and nothing important slips through the net.
Even with rising AI adoption, people still lean human when the interaction matters. In our May 2025 study, 49% said they’d be more likely to choose a human telephone answering service, compared with 18% who’d be more likely to choose an AI telephone answering service.
What this suggests: when the moment is customer-facing and personal, reassurance still carries real weight, even for audiences who are adopting AI elsewhere.
Source: Moneypenny UK research, May 2025. Question base: respondents not currently using AI for telephone answering (n=494).
As AI tools act as intermediaries, trust becomes both more important and more indirect. AI systems look for signals that suggest a business is credible and reliable. Customers look for reassurance that the reality will match the promise.
The signals overlap more than you might expect. Clear service descriptions. Reviews that feel authentic. Consistent messaging across channels. And content that explains trade-offs honestly rather than overselling.
Trust is built beyond your own site. Review sites sit almost level with AI providers as a trusted source in our May 2025 research.
Practical takeaway: if reviews and third-party mentions help shape trust, they also help shape the story AI systems pull together about your brand.
Source: Moneypenny UK research, May 2025, n=750. Multi-select question, so totals do not sum to 100%.
Human reassurance becomes even more valuable here. Knowing that calls will be handled professionally, or that follow-up will be timely and thoughtful, can be the difference between a shortlist and a signed agreement.
A good test is to check whether your website, reviews, and sales messaging tell the same story. AI tends to reward brands that are consistent and clear about who they help and how.
AI search can make attribution harder. Journeys are less linear, and customers may move from an AI summary to a call without leaving clear digital footprints along the way.
This is where measurement becomes an operational advantage. When you can connect enquiries to sources, you can make smarter decisions about what to invest in and what to refine.
For many small businesses, phone enquiries still represent the most valuable moments. That’s why a call tracking service can be particularly useful in this new landscape. It helps identify which channels drive real conversations, not just clicks or impressions.
It also gives marketing and sales teams a shared view of reality. What’s creating demand, what’s creating noise, and where prospects are coming from when they’re ready to talk.
AI search can shorten the path from discovery to a call, which makes it even more important to understand which activities are generating genuine, high-intent conversations.
One of the ironies of AI search is that it often increases the value of human interaction.
As information becomes easier to access, the conversation becomes the differentiator. Customers want judgement, reassurance, and empathy, particularly when the decision affects their reputation or their day-to-day operations.
This is also why social presence matters, not as a vanity project but as a credibility layer. When people encounter a brand through AI summaries, many still check whether it feels real and consistent in public-facing spaces.
A considered approach like social media management can support that consistency, especially when content answers common questions, reflects customer concerns, and shows the human side of a service-led business.
AI search is not a threat to small businesses. It’s a filter. It rewards clarity, consistency, and genuine customer understanding, and it makes vague messaging and fragmented handovers more costly.
The work now is less about gaming systems and more about joining the dots. Marketing needs to tell a clear story. Sales needs to be aligned with that story. And the operational experience, from first call to follow-up, needs to match what prospects think they’re buying.
If there’s one steady takeaway, it’s this. As search becomes more intelligent, the businesses that thrive will be the ones that remain unmistakably human.
When marketing and sales share a clearer picture of what drives calls and leads, it becomes much easier to prioritise what to improve, what to test, and what to stop doing.
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