AI Business Strategy For SMEs

There is much discussion about the potential impact of artificial intelligence (AI) on how people live and work. Many large organisations have access to resources and personnel that will enable them to implement AI strategies. However, small and medium sized enterprises (SMEs) can also benefit from developing an AI business strategy appropriate for their needs and resources, to attract more leads and sales by delivering what their customers want.

AI Business Strategy For SMEs

Opening with A Brief History of AI, this article looks at Using AI in SMEs, AI Tools and Applications and outlines a Ten Step SME AI Strategy. It then explores Prompt Engineering, Writing Effective AI Prompts, The Art Of AI Prompts and includes Twenty Useful AI Prompt Examples. Learn more about AI by reading Generative AI: What It Is and Where It Is Going.

A Brief History of AI

Artificial Intelligence refers to computer systems that can carry out tasks which would otherwise require human intelligence, such as pattern recognition, data analysis, problem solving, language processing and content production. AI can process big data sets that are far larger than those commonly found in small business databases and managed using office applications to store, analyse and update client and customer records.

Theories related to AI emerged in the 1950s, although thinking machines had previously appeared in science fiction. During the 1960s AI was used mainly by universities and government departments. Expert systems developed during the 1970s and 1980s were used by organisations in areas such as finance, market analysis, managing supply chains and medical diagnosis. However, the use of AI was limited by its high cost and lack of sufficient computational power. This impacted investment in AI during the 1980s.

Increasing availability of computational power and the need to analyse large data sets led to growing interest in AI in the 1990s. Large businesses, including retailers, began using machine learning (ML) when looking for buying patterns, identifying customer preferences and to assist their decision making in relation to stock control and forecasting sales. Search engines also used AI to index and rank the rapidly growing number of web pages.

During the first decade of the twenty-first century there was a rapid increase in the volume of big data, which organisations wanted to analyse in the search for information that could drive success and innovation. Online businesses such as Amazon and Netflix used AI to provide a more personalised experience to their customers. AI was used to deliver more targeted digital advertising services to businesses promoting products and services online. Governments used AI to deliver more efficient public services.

AI assistants became available on devices such as mobile phones in the 2010s. Neural networks led to the development of deep learning, greatly increasing the power of AI, which could be used for complex tasks, such as image recognition and language processing. E-commerce platforms used AI chatbots for customer support and to dynamically manage pricing. Autonomous vehicles controlled by AI were developed. Technology companies, including Amazon, Google and Microsoft, offered cloud services with AI powered features, making them more affordable for smaller businesses..

During the early years of the 2020s generative AI and Large Language Models (LLMs) became widely available online, enabling individuals and businesses to produce content by entering suitable text prompts. The use of virtual assistants powered by AI for tasks such as customer services and staff training increased, as did use of AI in robotics and business functions including managing supply chains and inventory. However, concerns related to copyright, data security and privacy has led to discussions regarding ethical codes.

Using AI in SMEs

Businesses can benefit from making effective use of technology. In recent years many have explored the potential for AI to reduce costs and increase profits. No longer only available to large businesses with the necessary resources, small and medium sized enterprises (SMEs) can now benefit from using AI to boost their efficiency and productivity. In addition to the popular generative AI and LLM platforms, there are a growing range of pay as you go AI services.

There has been much discussion about the potential impact of AI on how people live and work. Large organisations are likely to have access to the resources and personnel that will enable them to implement AI strategies. However, SMEs can benefit by developing AI strategies suited to their business needs and available resources, to attract more leads and sales and deliver what their customers want.

SMEs often have limited resources and small teams, but respond more quickly than large organisations to changing market conditions and opportunities. AI training could enable existing staff to become more productive, by using AI to take over some repetitive tasks. Prompt templates could be accumulated for staff to use as required. FAQs or customer service chatbots could be trained on anonymised data accumulated from previous customer interactions and respond in a formal manner that reflects an understanding of end-users needs.

AI models can be instructed to take on a persona when responding to a prompt. For example, a software engineer or digital marketing expert, who has relevant knowledge and experience. This could assist teams developing new products or services, writing code to add functionality to a CMS or CRM, or the automation of administrative tasks, such as calendar scheduling, generating invoices, or the planning of content marketing strategies.

As with any investment, it is important to have a clear understanding of what a business hopes to achieve, to reduce the risk of wasting time and resources. AI can augment rather than replace human work. It can reduce the need to carry out repetitive tasks, provide useful insights based upon relevant data and free people to spend more of their time doing work that is creative and fulfilling.

AI Tools and Applications

Generative AI, such as ChatGPT, can be used to generate content, by entering suitable prompts, for little or no cost. The output could be in the form of text, images, numerical data or audio. AI can be used to research a topic and produce content, such as reports and designs, but output should be reviewed by people with relevant knowledge to ensure accuracy and correct errors. AI has also been integrated into software, including spread sheets, word processors and email clients.

Although ChatGPT is the most widely known Generative AI platform, there are many others available. Google Gemini enables individuals and businesses to analyse large sets of data, such as spreadsheets, to derive valuable insights that could identify trends and opportunities. For example, it could be used in digital marketing to analyse the performance of paid and organic campaigns. Platforms such as DALL-E, Midjourney and Stable Diffusion can be used to produce images, though there is considerable controversy surrounding their use.

SMEs can use Generative AI to help them produce material such as customer survey questions, training plans or initial drafts of documents. However, if they have the resources needed, applications developed to meet specific requirements of a business can deliver greater results. For example, improved accuracy and speed of accounting processes, increased data security, AI powered customer service agents, or Customer Relationship Management (CRM) systems that can automate tasks, including data analysis, or generating emails, letters and reports.

A business will likely prefer to keep valuable or sensitive business data within their organisation, rather than process it through a publicly available platform. If a business only uses their own data within AI applications, the output should be more reliable. This should also minimise the risk of possible ethical, privacy, copyright or other legal issues. The customers or regulatory authorities that a business deals with might require such safeguards to be put in place.

The development of open source or pay as you go AI services enables SMEs to benefit from affordable solutions. When designed with intuitive user interfaces, these tools can be be used by non-technical people who instruct AI using normal text or speech to deliver the results they want. AI is being used to manage and automate tasks related to inventory, human resources, support services, market research and social media. SMEs should research and compare what platforms offer and the experiences of their existing customers.

Ten Step SME AI Strategy

Before investing time and resources into the integration of AI within a business, it is important to put in place a project plan with clear objectives. A good plan can also ensure requirements and dependencies are identified and that tasks are carried out in a logical sequence. Implementing AI without a plan could lead to resources being wasted and might not deliver useful results. A strategy such as the ten step process described below could increase the potential for success:

1. Analyse current processes in a business, to acquire an understanding of data flow, storage and use. It is advisable to obtain input from relevant staff and management. In addition to providing insights into the details of their work and the tasks involved, they might highlight issues that need to be addressed or opportunities to improve existing processes.

2. Define objectives, by identifying issues that need to be addressed, problems to be resolved or opportunities for improvement. For example, more responsive customer service, better supply chain management or reduced costs. The AI plan should align with the long term goals of a business, such as increased efficiency and profitability. Measurable objectives could include increased leads and sales, or better customer retention.

3. Research AI tools and resources used by other businesses, to learn from their experiences and the results, to establish best practice. Consult relevant experts. Compare AI products and services provided by different vendors and look for objective evaluations of their performance. You might also consider the viability of having a bespoke AI solution developed. Identify the personnel and resource requirements and estimate likely costs, savings and increased revenues.

4. Implementing an AI strategy involves the use of AI models. They require suitable data for training purposes. Having identified internal or external data sources, it should be ensured the data is clean, accurate and represents the type of data that will be used when the system is live. Policies should be reviewed regarding data security, privacy and compliance with relevant legislation.

5. Develop a plan for how an AI strategy will be deployed in a business, with a break down of costs and requirements. Pilot projects could be run that would not disrupt normal business operations, but will allow the running of feasibility tests, providing measurable results. Have benchmarks against which results can be evaluated. The information can be used during the project planning stage and when scaling up across the business.

6. Identify AI skills and resources, internal and external, along with additional requirements for suitable training for existing staff or the need to hire people who possess relevant skills and experience. A business could build trust among existing members of staff by involving them in the AI implementation process, rather than it feeling like an imposition, particularly if it helps them to perform better in their job.

7. Comply with relevant rules and regulations, such the General Data Protection Regulation (GDPR). When a business is using data generated internally or from trusted sources, it might feel confident that results will be accurate. However, many people have concerns regarding ethical issues surrounding the use of AI, the sourcing of data, potential bias in decision making and the reliability of AI generated content.

8. Monitor and evaluate performance against Key Performance Indicators (KPIs). This should be an iterative process, enabling the performance of the AI to be improved over time. Feedback from people using the AI systems can help to identify issues requiring attention and opportunities for improvement. Taking a responsive approach could enable a business to adapt effectively to changing conditions and identify new use cases for AI powered systems and processes.

9. Be aware of emerging technological developments that might enhance AI performance across a business, after completing the AI implementation strategy. A business that regularly reviews their AI strategy will be better able to respond effectively to changing market conditions. This could include allocation of resources into the search for new opportunities that align with their current goals and might also lead to future growth.

10. Measure Return on Investment (ROI) in relation to metrics such as cost of using the AI and the resulting productivity gains, reduced running costs and increased profits. Such information can be used in good news stories and reports to boost moral within a business, or externally to attract new talent or investors. Evaluating the performance of an AI strategy can inform decision making that might contribute to long term stability and success.

Prompt Engineering

We live in a highly competitive business environment and most business owners are keen to find ways in which AI can boost productivity, reduce costs, increase profits and promote innovation. For example, it can assist with drafting reports, proposals, social media posts and emails, or researching and planning marketing strategies. However, many people feel intimidated by the terminology used in relation to AI and assume in depth knowledge of technology is required in order to integrate AI into their business processes.

Companies are offering large salaries to people with qualifications, skills and experience that they consider essential to excel at prompt engineering, including computer science and coding in languages such as Python. Consequently SMEs might assume they lack the resources needed to attract the talent that will enable them to compete effectively. They could fear being left behind as AI is widely adopted. However, SMEs might have the potential to not only compete against but outperform larger businesses in their sector. For example, by training their existing personnel.

The term prompt engineering is widely used to refer to writing prompts which when entered into a generative AI tool such as ChatGPT or Google Gemini will output text, image or audio content. Essentially this involves crafting the best possible text prompt to get the AI to output the optimum answer to a question. This is a skill that can be developed by practicing with different AI tools and learning how use of language and refining questions can deliver good results.

Although this article uses the term ‘prompt engineering’, it might be better to describe it as ‘prompt writing’. Use of the word engineering can be misleading and cause businesses to focus too much on technical expertise rather than the domain knowledge and experience that is relevant to the products or services that they sell. For example, a food company marketing expert using generative AI to help them develop a marketing strategy is more likely to get good results than a software engineer who lacks an understanding of the industry.

When a business is planning to develop a custom software application, it will be necessary to employ the services of people with relevant skills and experience. For example, AI platforms including ChatGPT and Google Gemini, provide an application programming interface (API), which can be used to develop custom applications powered by AI. SMEs typically lack such in-house resources, but increasingly AI is being integrated into applications business owners and their employees will be familiar with, such as Microsoft 365 Copilot.

Writing Effective AI Prompts

A logical mind, good writing skills and domain knowledge are valuable assets in the writing of effective prompts. Understanding the nuances, strengths and weaknesses of different generative AI tools and LLMs will help users to select the best platform for each task. Business owners and their employees will be familiar with terminology used in their sector, which will help them to write suitable prompts. They will also be better able to recognise the relevance and accuracy of AI output, correct errors and ensure content is appropriate for the intended audience.

Although coding skills are not essential, some basic technical knowledge can be useful. For example, awareness of issues around data security and terminology frequently used in AI. Writing concise AI prompts can also benefit from a basic understanding of conditional statements used in programming, such as if-then and if-else. Boolean logic, is a type of algebra that uses three basic operators: AND, OR, NOT to determine if a thing is true or false. Comparison operators, such as equal to, less than or greater than, compare values.

When attempting to formulate a good prompt you should have a clear idea of what you want to achieve. You could begin by asking generative AI to suggest suitable prompts, which might help you to get the results you are looking for. It is likely that you will spend some time refining your prompts and you might find that some unexpected answers prove useful. As your prompt writing skills improve you might begin to build up a range of effective prompts that you can share with colleagues in a knowledge base.

Writing efficient prompts can reduce the time required to get useful results and save money by reducing the usage of tokens, which is also more sustainable as it consumes less electricity. Rather than a specialist skill, writing effective AI prompts is likely to become something that most people will learn, as it can help them to succeed in their role. However, just as with other software tools, such as spreadsheets and word processors, those who learn more advanced skills will be able to achieve more.

The structure and quality of prompts will determine the output, as referred to in the phrase ‘garbage in, garbage out’. If prompts are vague the output will likely lack relevance, be too generic, or fail to align with business goals. In addition to clarifying the scope, depth, purpose and target audience of the output, a prompt can request details of factors that influenced conclusions and recommendations. This might inspire solutions or innovations that promote growth, while analysis of big datasets could provide insights that assist decision making.

The Art Of AI Prompts

A musician who develops an understanding of musical theory, along with a feel for their instrument, can apply this in their creative process. Writing effective prompts is a skill, with theory that can be understood and techniques that can be learned. However, it could perhaps also be considered an art form, in which the AI will respond more effectively to prompts that are written with a feel for the nuances of the AI platform.

LLMs recognise patterns and relationships among the datasets upon which they are trained. In response to a text prompt, the AI model generates answers that most closely correspond to what it predicts will come next in a sequence. The phrasing, structure and content of a prompt will determine the output. Rather than asking simple questions, the art of prompt writing involves guiding the AI towards the desired output. The audience for the required output could also be specified, to ensure the depth of complexity and language used are appropriate.

Twenty Useful AI Prompt Examples

Writing effective AI prompts is an iterative process. It will likely require you to experiment with and refine the structure and phrasing used. This could involve a conversational chain, in with each prompt improves upon the previous one. The resulting content could provide a good starting point, but will probably require additional work to ensure it is error free and meets specific requirements.

Instructional prompts provide explicit instructions. Example: ‘Provide a step-by-step explanation of the most efficient method that will solve the following mathematical problem.’

Priming prompts include examples that reflect the desired output from a particular input, in order to get the AI to generate something similar. Example: ‘The generated output should be similar in style, tone and content to these examples listed below.’

Socratic prompts can instruct an AI model to explain its reasoning process. Example: ‘Describe the advantages and disadvantages of employing the following strategy to resolve the following issue, which includes your reasoning process and describes sources of verified data.’

Mixed prompts include a combination of different prompt types. Example ‘Based upon the previous output (context), describe advantages and disadvantages of using this technology (instruction) and provide relevant supporting examples to explain your decisions, with evidence and sources (Socratic).’

Generating Code Example: ‘Write the HTML CSS, and JavaScript code for a fully responsive web page featuring a unit converter to convert between metric and imperial values of weight, length, volume and temperature. Put the JavaScript and CSS in external files, to ease maintenance and updating. Include comments explaining how the code works.’

Data Research and Analysis Example: ‘Generate a CSV file of the ten largest businesses selling (product or service) in the (region), which includes available data to populate the following fields of data (data required) within each record. The CSV file will be opened in an MS Excel spreadsheet to display data in a table, requiring suitable record and field names.’ (*CSV = Comma Separated Values)

Rules and Regulations Example: ‘Detail requirements for (project description) at (location) using (product) on (dates and times). Based upon the previous conversation and information regarding our business, highlight key issues and recommend any actions that should be taken to ensure compliance with rules and regulations.’

Strategy Planning Example: ‘Generate a SWOT analysis for a UK based SaaS startup selling cloud services to SMEs that has the following characteristics:’

Report Summary Example: ‘Generate a summary, between 80 and 100 words in length, for a sales pitch suitable for a non-technical audience that highlights key information from the following report:’

Social Media Posts Example: ‘Create a series of engaging marketing messages for (product or service) that will appeal to (customer persona) suitable for the following social media platforms:’

Email Responses Example: ‘Generate a professional response, highlighting key features of (product or service) detailed in the report (report name) summarised previously, that answers the questions in the following client email:’

Social Media Research Example: ‘Generate a report of the most highly commented social media content found online regarding (company name products or services), along with the most frequent positive and negative reviews.’

Market Research Example: Generate a market research plan for a business selling (product or service), identifying key data required. Segment customers based upon their demographic characteristics and suggest strategies that are most likely to persuade them to complete a purchase.

Market Forecasting Example: ‘Estimate the current and potential future UK market size for (product or service) and include a breakdown of relevant data upon which future predictions are based.’

Competitor Analysis Example: Generate a SWOT analysis of current market leaders selling (product or service) and compare the performance of each company. Identify key areas for improvement and generate a marketing and sales plan that should maximise customer engagement, leads and sales.

Consumer Behaviour Example: Analyse available online data regarding buying preferences for the following customer persona types (description). Based upon these findings, suggest a marketing strategy that will appeal to each persona and increase the probability they will complete a purchase.

Event Planning Example: Find a list of suitable venues for a conference to be held in (city name) on (dates) to be attended by (number and description of attendees) at which their will be discussion of (conference topic). Generate a list of suitable speakers and an event plan, with detailed itinerary for each day.

Comparing Product Suppliers Example: ‘Find the 10 best rated suppliers of (product) within (region), listing available data regarding pricing and delivery. Include links to best and worst online reviews, along with any relevant media stories with verified sources.’

Product or Service Research Example: Analyse past, present and projected future trends regarding purchase of (product or service type). Identify target audience characteristics and suggest new or updated product features likely to appeal to them. Include estimated production, storage and distribution costs.

Product or Service Design Example: Generate a list of essential features of (product or service). Create a step by step plan detailing the design process, highlighting issues to be aware of. Include key findings from relevant research data, to identify unmet niche demand and opportunities to differentiate the design from those already on the market.

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