The article Using AI sensibly in the company: 7 application examples by Carsten Lexa first appeared on BASIC thinking. You can always stay up to date with our newsletter.
Companies and start-ups want – and need – to be faster, more efficient and better than the competition. They are often hindered by repetitive or non-value-adding activities that are necessary but strain time resources. The use of artificial intelligence (AI) can be an advantage. We outline seven examples of how you can use AI sensibly in your company.
There is now special AI software for many situations and tasks, be it for creating images, music, websites or presentations, but also for research tasks, podcast creation or workflow automation.
Nevertheless, Large Language Models (LLMs) such as ChatGPT, Claude or the AI solutions from Google and Meta offer useful solutions for everyday business situations at relatively low costs. Below we look at seven specific areas of application in which LLMs can effectively support start-ups.
Using AI in the company – examples
Automated customer interaction
Time and resources are scarce in every start-up – especially when it comes to customer support. With AI-powered chatbots and virtual assistants, startups can provide 24/7 support without the need for large teams. Whether it’s answering common questions, personalized product recommendations, or collecting and responding to feedback, LLMs can make interactions with customers faster and more efficient.
Content generation
In many cases, it is important for start-ups to reach their target groups online in order to inform them about new offers or to share information. But creating online content takes time. LLMs enable the rapid generation of blog articles, social media posts or product descriptions that are both high quality and target group-oriented. In addition, LLMs are quickly able to adapt the content of postings to the specifications or peculiarities of certain communication platforms.
Market analysis and trend forecasts
Data is the basis for strategic decisions – this realization is slowly but surely becoming established in Germany. However, analyzing such data and finding patterns in datasets can be complex and time-consuming. With LLMs, startups can analyze large amounts of unstructured data – from the essence of customer reviews to identifying recurring questions about products or services to tracking social media trends – and uncover actionable insights and similarities or differences.
Personalized onboarding and training
Rapid growth is one of the core characteristics of startups. In many cases this leads to rapid employee growth. However, onboarding new employees is often a challenge, especially in cases where startup managers have little or limited experience with the hiring and training process.
LLMs can create individual onboarding materials tailored to each position or department within a company. They can also serve as an interactive knowledge base, providing employees with answers to specific questions quickly and efficiently.
In addition, LLMs are able to develop training tailored to the skills and knowledge level of individual employees, rather than having to provide employees with training that assumes that everyone taking part in the training is at the same level.
Support with software development
For many start-ups, developing software is a central part of their activities, often even the basis of their products and services. This is where LLMs can help by writing code, optimizing it or diagnosing errors. Development teams benefit from an AI that acts as a virtual partner and takes on repetitive tasks so that the employees of a start-up can concentrate on creative problem solving.
And even if a start-up’s offering is not software-based, LLMs can be used to create custom software for a start-up to solve specific problems. The AI practically takes over the familiarization with the software and the assistance in creating the software.
Efficient project and task management
Organizing projects is often one of the major tasks in a start-up, especially when it is in a dynamic growth phase and the projects therefore become more extensive and complex.
Confusion quickly sets in. LLMs can help prioritize tasks, create schedules and allocate tasks sensibly based on the data – knowledge and skills – of individual employees rather than the gut feeling of a project manager who may have little experience. You can also automatically summarize meeting notes and generate calls to action so that project teams are quickly and comprehensively updated.
Optimization of sales
Anyone who saves on sales dies. This sentence clearly shows the importance that sales has – or should have – in a company. Many start-ups are very good at developing a new product or service, but have difficulty selling their innovation.
LLMs can help by creating personalized sales copy, conducting audience analysis, or generating automated campaigns that target potential customers. They can also use data to analyze which acquisition strategies are particularly successful, thereby helping to improve the sales strategy based on data.
Conclusion: Use AI for companies
As great as the possibilities of LLMs look at first glance, one should not overlook the fact that there are a variety of specialized AI tools and models that can perform certain tasks better due to their specific orientations.
However, especially for start-ups, which often work with limited resources, LLMs offer a cost-efficient and versatile solution.
They enable an uncomplicated entry into the world of AI, as they cover a wide range of applications in many areas and can replace the often expensive use of several specialized tools for simple tasks.
Added to this is the ability of LLMs to deliver acceptable initial results even with vague or imprecisely formulated tasks by the user. For start-ups that do not yet have any experience with AI-supported processes, this offers the opportunity to quickly obtain initial usable results without much training, which can then be refined and adapted.
Furthermore, it should not be overlooked that LLMs provide a new perspective for building long-term internal competencies. With their help, start-ups can establish a type of “intelligent assistant” that not only brings short-term efficiency gains, but also serves as a learning tool for employees. Working with LLMs promotes a better understanding of the use of AI and helps to anchor data-based working methods throughout the company – in my opinion one of the key skills of the future.
Finally, startups should keep in mind that the use of LLMs is becoming more commonplace. The sooner start-ups deal with the possibilities that LLMs offer and integrate them into their processes, the faster the use of AI will become a matter of course and can thus enable them to differentiate themselves from the competition, which believes that the use of AI models will still help to be able to wait years.
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The article Using AI sensibly in the company: 7 application examples by Carsten Lexa first appeared on BASIC thinking. Follow us too Google News and Flipboard.
As a Tech Industry expert, I believe that using AI sensibly in a company can greatly enhance efficiency, productivity, and decision-making processes. However, it is important to ensure that AI is implemented in a responsible and ethical manner to avoid potential pitfalls such as bias, privacy concerns, and job displacement.
Here are seven application examples of using AI sensibly in a company:
1. Customer service chatbots: AI-powered chatbots can provide instant responses to customer inquiries, improving customer satisfaction and reducing the burden on human customer service representatives.
2. Predictive maintenance: AI algorithms can analyze data from sensors and equipment to predict potential maintenance issues before they occur, helping to prevent costly downtime and repairs.
3. Fraud detection: AI can analyze large volumes of data to detect patterns indicative of fraudulent activity, helping companies to proactively identify and prevent financial losses.
4. Personalized marketing: AI can analyze customer data to create personalized marketing campaigns tailored to individual preferences and behaviors, increasing engagement and conversion rates.
5. Supply chain optimization: AI can optimize inventory management, predict demand, and identify cost-saving opportunities in the supply chain, improving operational efficiency and reducing costs.
6. Employee recruitment and retention: AI can streamline the recruitment process by analyzing resumes, conducting initial screenings, and identifying top candidates, helping companies to attract and retain top talent.
7. Data analysis and decision-making: AI can analyze large datasets to uncover valuable insights and trends, enabling companies to make more informed decisions and drive business growth.
Overall, using AI sensibly in a company can provide numerous benefits, but it is crucial to approach implementation with caution and consideration for potential ethical implications. By leveraging AI responsibly, companies can unlock new opportunities for innovation and growth while maintaining trust and transparency with customers, employees, and stakeholders.
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