Building trust in AI: Missing the biggest brand opportunity of the decade

AI has handed every business the same extraordinary tools. The ones pulling ahead right now are treating AI as a brand asset: building deliberately, evidencing constantly and benefiting commercially. We have been part of this shift and this is what it looks like.

AI’s promise has always rested on a single, quiet assumption: that it is smart, safe and worth relying on. That assumption is what persuades a business to route its contracts through a model, a bank to let an algorithm inform its decisions, a person to type something into a chat window they would never say aloud. It is confidence, and confidence is the whole product.

Right now we’re at a moment when brand promises are being tested like never before and brand belief is often in short supply. That makes trust the scarcest, most valuable and most defensible asset in the entire AI economy, and building it is a branding discipline. At Underscore we see this as being good news, because it means that brand trust can be built, on purpose, and we have spent the past few years helping businesses do exactly that.

Why trust is the opportunity, not the obstacle

Adoption tells the story. By most measures, the overwhelming majority of large organisations now use AI in at least one part of the business, and global enterprise spending on it has climbed into the hundreds of billions. The technology has moved from experiment to infrastructure at remarkable speed, and it is creating genuine value: time saved, costs cut, and capabilities that simply did not exist five years ago.

What separates the leaders from the pack is no longer what their AI can do. It is whether people believe in it. Trust and truth are the two halves of that belief. Can I rely on you with my information, and can I rely on what you tell me? The businesses answering both questions well, with transparency about how data is handled, honesty about what a system can and cannot do, a visible security posture and evidence in place of assertion, are turning trustworthiness into a differentiator their competitors cannot copy overnight. Unlike a feature, it cannot be prompted into existence. It has to be earned, consistently, and evidenced when tested. That is precisely what makes it valuable, and precisely why brand, the discipline of making a promise and keeping it in public, has moved to the centre of the AI conversation.

We know this works, because we have watched it work, recently, in two very different corners of the AI economy.

Cambridge Spark: trust that compounds, inside and out

Cambridge Spark is an education technology company that helps organisations boost performance by upskilling their workforce in data and AI, a market full of bold claims and crowded categories. When we began working together, they had genuine expertise and real momentum, but a brand that had not caught up with either. We repositioned them as a Centre of Excellence at the forefront of AI and machine learning, refreshed the identity, and relaunched digitally across web and social.

What happened next is what earned belief looks like on a balance sheet. Cambridge Spark’s net worth grew sevenfold in three years, from £650k to £4.5M, with £18.6M in sales and a 61% annual growth rate. Over 70% of the market for Level 7 AI apprenticeships now belongs to them. Their 5,000+ learners achieve a 99.5% pass rate, their programmes have generated over £350M in calculated business value for the organisations they serve, and they were named Training Provider of the Year at the Apprenticeship & Training Awards.

However, the number we find most telling is a quieter one. Cambridge Spark’s own people rate the company 4.6 out of 5 on Glassdoor, 23% above the education industry average. That matters because trust in an AI brand is not only won in the market. It is won inside the building, among the people asked to deliver the promise every day. When employees believe the brand, customers can feel it. Clarity created belief, belief created growth and the growth is still compounding.

Retail Insight: making machine intelligence legible

Retail Insight is a global technology business that turns data from across the world into better decisions for retailers and CPG brands: algorithmic intelligence, applied to the shelf. Their challenge was never capability. It was legibility. When your product is, in effect, a machine telling an experienced retailer what to do, people will only act on it if they can understand it and believe it.

That was the brief for the brand. Our consultations uncovered the unique blend of retail expertise and mathematical precision behind their analytics, and we captured it in a single, memorable brand story, ‘shelf actualisation’, supported by an entirely new visual language for their data and products. The intelligence did not change. The ability to see it, understand it and trust it did.

The results speak the language every board understands. Retail Insight has reached approximately $28.1M in revenue, with software running across more than 52,000 stores and processing around 10% of the world’s grocery data. For their clients, that trusted intelligence has delivered over $600M in gross profit, saved $50M in trade spend and removed 225,000 tonnes of CO2, and the industry took notice, naming them Data and Analytics Company of the Year at the Retail Systems Awards. When people believe what the machine tells them, they act on it, and the value follows.

Two different businesses, one lesson. Trust in AI is built with clarity and kept with evidence and both of those are brand jobs.

The trend to watch: trust in AI starts at home

Here is the trend we would encourage every leadership team to watch. The next frontier of trust in AI is not just with the customer, it is within the workforce.

Every AI strategy ultimately lands on people: the teams asked to change how they work, adopt new tools and stake their professional judgement on what a system recommends. The evidence suggests this is exactly where the biggest gap sits. Research from within the AI skills sector has found that around six in ten employees have received no AI-specific training at all, even as the overwhelming majority of HR leaders express confidence in their organisation’s readiness. Leaders believe. Their people have not yet been given a reason to.

That gap is not a technology problem. It is an internal communications opportunity, and it is why we believe the employer brand is becoming the front line of trust in AI. A clear employer value proposition that tells people honestly what AI means for their roles. Engagement campaigns that bring the workforce into the change rather than announcing it to them. Intranets and internal platforms that make the strategy visible, human and easy to believe. This is the infrastructure on which internal trust is built, and internal trust is where every successful AI adoption we have seen actually begins. It is no coincidence that Cambridge Spark, an AI-native business, pairs its market leadership with one of the strongest employee ratings in its industry. The companies that win belief inside win adoption, and the companies that win adoption win the market. Happy workforce, happy business.

A category rising to the moment

Looking across the AI skills market in which Cambridge Spark competes and you can see a category maturing around exactly these principles, which is good news for everyone, because every well-built trust story raises confidence in AI as a whole.

Corndel is a strong example. Its Enterprise AI Academy, created in partnership with Imperial College London and supported by Microsoft, set out to skill ten thousand professionals, with ethics, privacy and responsible adoption woven through its programmes in line with the EU AI Act. Just as tellingly, its own workplace research openly names the readiness gap between leaders and employees, and calls on businesses to upskill leaders who can inspire trust. That is internal trust-building done at national scale, and it maps directly onto the challenge we described above: engaging leadership and workforce in the same honest story about AI.

Decoded has taken a different and equally instructive route. For more than a decade, it has specialised in demystifying data and AI for leaders and teams across FTSE 100 and Fortune 500 organisations, with leadership sessions built around confidence, judgement and asking better questions, and course titles that say it all: Demystifying AI, Responsible AI. Its premise is one we recognise from our own Truth Workshops. Understanding comes first, because people cannot trust what they cannot understand. Clarity is where belief begins.

We had no hand in either business. We simply think they are doing something right, and the whole category is stronger for it.

The question that matters most

We practise what we describe. We use AI every day, carefully and securely, to streamline and automate the work that used to slow brands down: saving our clients time, taking cost out of their processes and freeing their people to focus on the work that genuinely adds value. Used well, and used safely, it is one of the most powerful engines for growth a business has. That is exactly why we treat it as a brand question and not merely a technical one. How a business adopts AI, how securely, how transparently and how honestly, is now part of what its brand stands for. The promise of AI has to be kept in public, and keeping it is a branding discipline as much as an engineering one.

So the question we would put to any business adopting or building with AI is a genuinely optimistic one. If trust is the scarcest asset in the AI economy, and it can be built deliberately through brand, what would it be worth to be the most believed name in your category? The businesses answering that question now are the ones that will own the next decade.

That, in the end, is what almost thirty years has taught us. Trust is the whole game and it has never been more winnable.

We are not the kind of partner that parachutes in to build with AI for its own sake. We start with your business and brand objectives and help you put AI to work in service of them, implemented safely and securely, because in our view AI sits squarely under the brand rather than off to one side as a technical add-on. If you are thinking about how to adopt it in a way that supports your goals and protects the trust your brand has spent years earning, we would be glad to talk.

Explore our thinking and our work at underscore.co.uk, or get in touch at [email protected]