How small businesses can harness the productivity power of AI
AI can help automate processes to support business owners
There is a productivity problem in the UK, and small businesses unfortunately aren’t immune. Although a long-standing issue, poor productivity has been compounded by below-trend economic growth and one-off events like Brexit – it’s definitely tough out there! Xero’s report "Small business productivity: Trends, implications and strategies" reflects these macroeconomic changes, showing UK small business productivity declined by 7% between August 2022 and December 2023, and is now well below the UK’s pre-pandemic range.
Without improvement in labor productivity, we risk a domino effect whereby small businesses struggle to re-invest capital to drive growth. Business owners can’t just sit and wait for the economic conditions to become more favorable, and so are understandably looking for ways to boost the productivity of their operations.
For many, that means turning their attention to technologies like artificial intelligence (AI) to see if they can help solve the productivity problem. AI is increasingly being called out for the ability to help automate processes and relieve business owners of process-heavy and time-consuming tasks that hamper productivity. Time is often the most precious commodity for small businesses, and AI is starting to show how it can give some time back to owners, so they can refocus on more important tasks.
Of course, AI tech will not completely solve the productivity problem, nor is it a case of ‘one-size-fits-all’ for every small business – particularly when AI itself is a variety of different technologies and capabilities. But there are some key considerations for small business owners looking to effectively harness and leverage this technology – namely understanding where it can benefit them, what the limitations are, and finding ways to safely experiment with emergent but relevant tools.
EGM Technology Research and Advocacy at Xero.
Optimizing tasks, processes and workflows with AI
A good starting point is to look at key business processes and identify the critical activities which are causing productivity blockages through the requirement for manual, repetitive intervention. From there, small businesses can frame experiments that explore how AI might help automate or augment these tasks, thereby reducing the effort required to complete them at scale.
Some businesses stand to benefit from streamlining tasks like drafting emails and producing documents for stakeholders, which can otherwise soak up time. Various types of AI can help with starting and, in some cases, completing this work faster and more accurately, freeing up staff to spend more time on functions that are either more pressing or require more creativity.
Beyond that, small business owners can also gain critical insights that can enable smarter decisions. For example, our research tells us that most small businesses struggle to maintain a healthy cash flow. AI capabilities that are available today are able to assist with addressing this pressure point by helping answer deeper questions regarding an organization's finances, producing forecasts, and providing analysis of where to start to dig further when seeking professional advice. This can lead to busy business owners having greater control over their cash flow and knowing where to focus their efforts, enabling them to prepare for potentially leaner months.
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Alongside optimizing tasks and processes, small business owners can also look for opportunities to optimize their workflows by utilizing the new conversational capabilities unlocked by generative AI. One example of this is using AI-powered tools that meet you where you are already doing the work, saving you time and the need to switch between applications.
Risk awareness when using AI
We’re also gaining a better understanding of the limitations of AI technology and also some of the risks inherent in its use, like misinformation, discrimination and bias. For functions like finance and accounting, the problem of hallucination – where data points are ‘made up’ by the model – can be compounded if datasets that are used are not the right ones for the task, or are not kept up to date.
And when up-to-date but sensitive or proprietary data is used, whether the AI tool is directly managed by a small business or built into products and services used by them, it’s key to take measures to prevent LLMs from disclosing this data to other, unauthorised parties. This is particularly important when using ‘free’ or public AI tools: taking time to examine how they are using and protecting the data provided to them is key to managing the risk associated with their use.
It’s a marathon, not a sprint
Like any advanced technology, speculation around the ‘correct’ amount and style of AI implementation in small businesses is to be expected and should, in fact, be welcomed. Small business owners have an increasing stake in how technology is best used to improve productivity in their world and need to have opportunities to evaluate where it can be of most use to them.
Questions like – where will AI provide the most value in my business? When will it start producing better returns for the time I need to invest in exploring and using it? And most importantly, how do I make the best use of the tech given the goals and objectives for my business? – are important to ask, as they can be very useful in helping focus efforts in navigating a landscape of opportunity. Also, speaking with trusted advisors can help business owners become more confident in their transformation journey, and about a future with AI by their side.
When it comes to harnessing AI and unlocking its potential to accelerate and improve productivity, small business owners need to be well-informed. Understanding AI's capabilities, limitations, risks, and rewards will enable them to make better decisions around experimenting with and implementing these technologies in their businesses. In this way, productivity can be unlocked gradually, one improved, AI-powered process at a time.
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James Bergin is EGM Technology Research and Advocacy at Xero.