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Generative artificial intelligence (generative AI or #GenAI) is revolutionising the landscape in which businesses operate, communicate and innovate. Initially the preserve of large firms and big brands, this technology’s growing accessibility – through tools like ChatGPT, Midjourney and MS Copilot – is now making it a valuable strategic resource for small- and medium-sized businesses (SMEs) too.
This matters because SMEs make up over 99% of businesses in the UK. While their size allows SMEs to react with speed and agility to changes in the market, it also means they have limited amounts of time and money. Which is why GenAI could be a game-changer by allowing them to automate processes, cut costs and drive innovation.
In a report published in the summer 2023 – The Economic Potential of Generative AI – consultancy firm McKinsey estimated that the adoption of GenAI could add between $2,600 and $4,400 billion in value to the global economy. And many of its use cases apply to key functions for SMEs, like marketing, customer service, sales, product development and administration. It’s no surprise, then, that a survey conducted in 2024 by Teneo for the U.S. Chamber of Commerce revealed that almost all (98%) American small businesses are already using AI-powered tools.
So how can SMEs harness the power of generative AI to boost growth and improve competitiveness? Time to look at some numbers, use cases and real-life examples 🙂
#GenAI and SMEs: five use cases
There are already many proven applications for AI in small businesses in areas such as marketing, communications and branding.
Use case #1. Creating content for marketing and communications
GenAI can create text, images and video in seconds. Tools like ChatGPT, Jasper, Sora and Canva AI can help small marketing teams do more with less when creating content like:
- social media posts
- personalised newsletters
- SEO-friendly product descriptions
- video and podcast scripts
👉 Case study. Specialty coffee chain Grind Coffee reckons it got a 20% gain in productivity by using AI tools for tasks spanning content creation and messaging to development of a chatbot for handling the 2,000 plus daily enquiries they get from customers.
Use case #2. Automated customer service
As we touched on with Grind Coffee, #GenAI can power chatbots and virtual assistants that can speak to people in natural language. This enables firms to offer 24/7 customer care without having to hire more staff to handle things like:
- answering chats or emails
- designing, managing and automating FAQ flows
- supporting the pre- and post-sale customer journey
👉 Case study. Farmer.Chat is a GenAI-powered chatbot that provides technical assistance to small-scale farmers in the developing world. Results so far are encouraging, with a study by Cornell University revealing that the app has helped over 15,000 users with more than 300,000 queries.
Use case #3. Translating and localising content
Small businesses can use tools like DeepL, ChatGPT and Google Gemini to do the heavy lifting when translating their marketing and communications, and then hire a professional translator to check and clean up the output.
👉 Case study. The Eco Candle Co., a British firm selling natural candles and fragrances, wanted to expand in Portugal and Brazil, which meant they needed Portuguese versions of their marketing assets. They used generative AI to translate their entire catalogue, including product descriptions and customer testimonials. They then undertook a post-editing stage in which a human – a professional, native-speaking Portuguese translator – revised and polished the AI-generated translation, which still contained lots of translation errors. In this collaborative process between man and machine, AI did the grunt work, and human expertise added real value by whipping the raw output into shape and ensuring it was fit for purpose.
Use case #4. Automating admin tasks
Generative AI can analyse entire documents, extract data, draft reports and more. Small businesses are already using it to streamline their admin operations by:
- automatically generating quotes
- analysing financial documents and creating reports
- managing emails and internal communications
👉 Case study: GreenWorks is a Canadian environmental consultancy. It used to manually manage contracts, project reports and invoices, tasks that would take up hours of every working day for writing and archiving alone. So to free up time, the management team implemented robotic process automation (RPA) plus generative AI to draft contracts, produce reports, extract data from contracts and purchase orders and automate the sending and saving of email communications. The result? A 30% drop in the working time spent on repetitive tasks (document drafting, data entry, archiving and more) that allowed the management team to focus on more strategic work. What’s more, report time-to-delivery was cut in half, leading to greater customer satisfaction.
Use case #5. Prototyping and developing digital products
Solutions like DALL·E and Runway can help create visual concepts, while code generation tools aid software development. Now, with the right generative AI tools, it’s possible to:
- produce mock-up graphic designs (such as packaging) or UI/UX,
- automatically generate code for landing pages
- run simulations to test products before their launch
👉 Case study: Coframe is start-up that has developed an AI platform for optimising web sites and online stores in real time. In collaboration with OpenAI, it has developed a GenAI-powered tool to personalise the user experience based on the visitor’s behaviour or profile, as well as automatically test and adapt copy, calls-to-action and images, and generate snippets of code aimed at improving layout and UX dynamically.
Challenges, drawbacks and limitations
GenAI tools may be more accessible and less costly than ever, but they still come with risks and limitations in three key areas.
- Privacy and security
- Content quality
- Ethics and transparency
So what takeaways are there for those leading or working in SMEs who want to embrace #GenAI? Here are four recommendations:
Start small: to begin with, trial the use of AI in a specific area – marketing, customer care or other somewhere else that you see potential benefits.
Measure results: set key performance indicators like time saved, costs cut or leads generated.
Train the team: provide training so that even the least technically savvy people in the firm feel at ease with AI.
Human in the loop: remember that a human must always check and sign off any AI-generated output.
Generative AI offers extraordinary potential for SMEs that want to digitise, innovate and scale without necessarily having to hire more staff. It’s not a replacement for people; it’s a way of empowering them. Firms that deploy this technology strategically will be able to respond more quickly to the market, improve customer experience and cut operating costs.
But a word of caution: AI is not a panacea for all ills. As this insightful piece published by the Harvard Business Review in the autumn of 2024 reminds us, AI can only give your business a temporary advantage, because it will eventually be adopted by your competitors. It is human capital – specific, rare and therefore irreplaceable – that will give you a long-term strategic edge.