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) might also benefit from developing an AI business strategy appropriate for their needs and resources. This could help them to deliver better products or services, compete more effectively, attract more leads and boost sales, increasing profits.
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Developing an AI Business Strategy
The rapid rate of technological change can be overwhelming and opinions regarding the future impact of AI range from utopian to dystopian. However, many business owners and their employees are concerned about the impact of AI on their ability to earn a living. The sections below explore practical uses of AI that might help an SME to remain competitive in a changing world.
Using Artificial Intelligence In Business
Artificial Intelligence Applications
Using Artificial Intelligence In Business
In recent years many businesses have explored the potential for AI to reduce costs and increase profits. Using artificial intelligence in business is no longer only an option for large organisations with considerable resources. Many small and medium sized enterprises (SMEs) are evaluating the use of AI to boost their efficiency and productivity. In addition to the popular generative AI and LLM platforms, there are also an increasing number of smaller specialised 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 a content marketing strategy.
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.
Artificial Intelligence Applications
There is considerable competition between artificial intelligence applications competing for audience attention and market share. 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.
Many businesses will 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.
What Is a Chatbot?
Similar to FAQ (frequently asked question) pages, a business could use a custom chatbot to answer common customer questions, reducing demand on their support services. Such a chatbot could be specific to the requirements of a business and keep internal data on systems they control. Customers could be directed towards human agents if questions are beyond the scope of the chatbot. I built the CraftBook Chatbot to answer questions about copywriting, digital marketing and the CraftBook website. Answers are displayed in the chat window above the question text box and Send button. This basic chatbot does not use an API (Application Programming Interface) to integrate AI-powered conversational capabilities, but it could be developed further to include such functionality.
Ten Step SME AI Business Strategy
Before investing time and resources into an AI business strategy, it is important to put in place a 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.