Three-quarters (75%) of UK and Irish SME leaders see AI as important to their long-term growth, yet just one in ten have fully integrated it across their business, according to our recent research.
For growth businesses, the challenge is turning that ambition into action. From taking the first steps towards AI adoption to understanding the risks, opportunities and implications for long-term business value, leaders need to consider how the technology fits into their wider growth plans.
Following BGF’s recent Landing investment in the age of AI webinar, Tom Pearson, Head of Data and Simon Steward, Head of Digital, share their perspectives on some of the key questions facing business leaders, drawing on their experience of working with ambitious companies across BGF’s portfolio.
Getting started with AI
“What does AI adoption mean for a business?”
There are several levels of adoption. Giving people access to approved AI tools is the first. This builds firsthand understanding of what the technology can do.
The next step is embedding AI into day-to-day workflows, before potentially using that experience to rethink products, services and even the business model itself.
“Should businesses build their own AI tools or use existing solutions?”
We’re seeing a mix of approaches, with businesses likely to combine existing AI tools with tailored solutions.
For standard functions, AI tools offered by established software providers are often the quickest and safest option. More specialised workflows may benefit from bespoke solutions, although these bring additional costs around integration, security and maintenance.
Neither approach guarantees better returns. The key is to weigh up costs against measurable business benefits, building on reliable existing systems wherever possible.
“How quickly can businesses implement AI projects, particularly without specialist skills in-house?”
For a focused first project, four to six weeks can be enough to demonstrate value.
Across our portfolio, we often connect companies with small specialist AI firms that can help define the opportunity, deliver an initial project and transfer knowledge so internal teams can build on the work. Our hackathons have demonstrated what teams can prototype in just a couple of days, although making something ready for everyday business use, with the right security and integration, can take longer.
The important thing is to start with a manageable use case, appoint an internal owner who can help embed the technology into the business, and focus on achieving an early, measurable outcome.
Where the expected return is time saved, businesses also need to think about how that time will be used to deliver tangible value.
Building the right leadership and capabilities
“How can businesses address a lack of AI understanding at board level?”
It’s difficult for a board to challenge management or provide effective oversight of AI without some firsthand understanding of the technology. Board members don’t need to be technical experts, but they should be using AI themselves, even for simple, low-risk tasks, and understanding its limitations.
Hands-on workshops for boards and senior teams can help enormously. AI is unusually easy to start using, so the barrier to getting involved is relatively low. Basic AI literacy is becoming an essential part of effective board leadership.
“What role can non-executive directors with AI expertise play in supporting business growth?”
We’re seeing increasing interest in board members who combine commercial experience with a genuine understanding of AI and digital technology, including its implications for marketing and growth. That expertise can be valuable in helping management teams test their assumptions, identify opportunities and manage the risks associated with AI adoption.
The important distinction is between someone who can talk confidently about AI and someone with enough practical experience to challenge and support a management team.
“How can growth businesses attract and develop the AI talent they need?”
Attracting AI talent, as with any specialist talent, starts with offering interesting business challenges, the freedom to make a difference and a leadership team that genuinely supports the work.
But not every company needs to recruit a large specialist AI team. A sensible approach is to develop AI capabilities among existing employees, recruit key specialists where there is a clear need and work with external partners to help deliver early projects.
Across BGF’s portfolio, we help businesses make relevant connections through our wider network. Ultimately, the aim is to build lasting capability within the business, rather than becoming dependent on outside advisers.
AI and the changing investment landscape
“How is BGF assessing the opportunities and risks presented by AI across different sectors?”
We’re considering AI risk and opportunity across all sectors, not just software businesses.
For a software company, the questions might focus on how it can maintain its competitive advantage, its pricing model and whether customers will continue buying software in the same way. In other sectors, the initial opportunities may be around improving operational efficiency, enhancing customer experience or developing tailored tools for internal use.
The underlying question remains the same: how might AI change the way a business creates value, and does its management team understand and act on that?
“Are businesses less exposed to AI disruption becoming more attractive to investors?”
Businesses with less immediate exposure to AI-driven change may appear more predictable, particularly where uncertainty is slowing investment decisions or exits. But we wouldn’t see this as a simple distinction between sectors. In most industries, AI presents both threats and opportunities. The same technology that challenges an established business can also help it become more productive and competitive.
We place considerable weight on a leadership team’s understanding of AI, its willingness to learn and its ability to adapt. This is because a strong business in a sector experiencing significant change, led by an exceptional team, may be better placed than a seemingly protected business that assumes AI won’t affect it.
“How does the investment approach differ between AI-native businesses and established companies adopting AI?”
An AI-native business, built around AI from the outset, doesn’t have the legacy systems, products or established ways of working that an existing business may need to change. It can start with a very different cost base and operating model, which can be a real advantage.
However, established businesses may already have valuable assets, including customers, data, trust, distribution networks and cash flow.
AI-native businesses aren’t insulated from change either, particularly as technology, competitors and customer expectations continue to evolve rapidly.
In both cases, we’re looking for a compelling customer proposition, a sustainable competitive advantage and a management team that can continue adapting as the market changes.
Turning AI opportunities into business value
AI presents significant opportunities for growth businesses, but making the most of them requires more than simply introducing new tools.
Whether a business is taking its first steps with AI or exploring how it could transform its products and services, the focus should be on identifying meaningful opportunities, developing the right skills and demonstrating measurable value.
For founders and management teams, the ability to learn, adapt and make informed decisions will be increasingly important as the technology continues to evolve.
To find out more, explore our recent report, Unlocking the value of AI: How growth businesses are moving from experimentation to impact.
