Getting Started with AI

Propelled by the explosive launch and subsequent popularity of highly accessible, free tools like ChatGPT, and the integration of these services into our lives through services like Microsoft Copilot, curiosity and fear around AI has skyrocketed in recent years.

We’re all repeatedly told about the myriad benefits of AI, and about the risks of nonadoption - so why are only 25% of UK businesses using this technology, and why do over 40% of businesses have no plans to adopt it, at all?1 What, exactly, are they missing out on, why could that turn into a big problem - and how can you avoid the biggest trap awaiting SMEs?

What do we mean by “AI”?

What is commonly referred to as “AI” is a family of technologies that combine data and algorithms at scale to support, enhance, or even automate decisions and the actuating of those decisions. This family includes natural language processing, machine learning, computer vision, and more.

Many of these technologies have been in popular use for decades. What has changed is scale: more data, better algorithms, faster computers with more storage and better connectivity, and lower barriers to entry have all contributed to the widespread availability of better-performing models at lower cost to end-users than ever before.

It is the unexpectedly high performance of these models, in generating sequences of pixels (images), waveforms (speech and music), and words (text) far in excess of peoples’ expectations and the performance of previous generations, that has captured imaginations and ignited new investment and excitement.

Why are SMEs slow to adopt AI?

Despite the many improvements of the current iteration of AI tools over previous generations, SMEs have been slow to adopt them. Lack of knowledge and skills, limited financial and human resources, limited ability to ideate and evaluate sufficiently compelling high-value or high-impact use cases, aversion to change, fear, poor quality data, limited time, and low risk appetite are all factors.

Cost, or rather demonstrable Return on Investment (ROI), remains a significant factor. Businesses typically deploy AI with either the intention of cutting costs and/or the intention of creating growth. The average investment of a business in adopting AI is currently around £12k for a small business and £480k for a medium business2. In a scenario where this investment comes out of existing profits with the expectation of creating growth, this investment represents around 10% of the median annual profit of a small business and 150% of the same metric in a medium business - so AI investments made by SMEs, far from being seen as longterm slow-burns, are under pressure to yield financial benefits quickly or fail fast.

This is a particular challenge for small businesses lacking the infrastructure, resources, and experience to establish performance measurement early and to artfully pivot when under-performance is identified. Similarly, in medium-sized businesses, potentially encumbered by inertia and elevated expectations, costs are skewed by a propensity to build solutions in-house rather than buy off-the-shelf.

What might happen if SMEs fail to adopt AI successfully?

Large businesses are sprinting ahead of SMEs, being much more likely than smaller firms to experiment with and adopt AI. While many initiatives are failing, the sheer volume of experiments means that some will eventually succeed - driving down costs, enhancing offerings, and opening up new markets; enabling these organisations to market and deliver their trusted enterprise-grade services to customer segments that previously would have been unprofitable for them, leaving SMEs priced-out and left-behind.

How can you avoid this trap?

The biggest blocker for many SMEs is a perceived lack of compelling use-cases for AI that combine affordable costs with tangible benefits to create meaningful ROI. The good news is that you don’t need to make a large financial investment in AI technology to start reaping the benefits - you just need to be structured and methodical in identifying where to get started.

Take, for example, this subset of tasks AI can perform:

If you list out the tasks that are executed in your business, can you categorise them according to these capabilities?

For each task, or sequence of tasks, can you estimate how much each costs you to execute, and how much value each creates? Which of these tasks would you like to do more of, and which would you like to do less of?

For your preferred 2-3 tasks from each extreme of the spectrum, what are the expected impacts, both positive and negative, of each? What are the risks?

It is on one of these tasks that you should focus your initial efforts to deploy AI - consider starting with the lowest-risk.

If you’d like some help and support performing this activity more comprehensively in your business, our BRIAREUS framework provides a robust basis for planning and executing AI investments, and can be tailored to most contexts and use-cases:

Would you like to know more?

It’s imperative that SMEs invest in building their knowledge and understanding of AI, start framing the opportunities for value creation in their organisations using AI, to consider the risks that AI poses to the organisation, and to start taking steps towards defining and executing a risk management plan in order to remain competitive.

If you’d like to discuss any of the topics covered in this article in more detail, including how to start creating value from AI in your own business or course-correct an AI or data investment that’s not delivering the return you expected, please reach out to alex@hecaton.consulting to arrange a no-obligation 30-minute chat.

About the author

Dr Alex Leathard (Hecaton Consulting) is an independent expert with over 15 years’ experience in digital, data, and technology, dedicated to helping SMEs unlock value from AI and data.

BRIAREUS was one of the three HECATONCHIERES in Greek mythology: hundred-armed giants known for their immense power and capability. hecaton.consulting