Practical tips to effectively implement AI solutions in your operations

Unlock the potential of generative AII and learn how you can improve your business processes

AI solutions

14 August 2024

Practical AI consulting tips for immediate application

Many companies see and want to exploit the potential of generative AI, yet in reality, very few apply it. What is it perfect for, and what isn't it suited for? How can you identify those business processes that can be efficiently handled with generative AI? Based on our experience, these are crucial questions that organizations must consider to integrate AI into their operations effectively.

Business leaders hardly doubt that generative AI—which can generate new data, content, or even entirely new things—has a place in business processes. However, in most cases, the first step is still awaited. One reason for this may be that many are unclear about the precise meanings of certain AI-related terms, whether it's Machine Learning (ML), Large Language Model (LLM), Natural Language Processing (NLP), or Computer Vision (CV). Moreover, they also lack an overview of how to apply these tools, whether it’s at the levels of prompting, fine-tuning, or model training, which can be facilitated through AI strategy consulting.

Numerous tools make advanced artificial intelligence technologies easily accessible to end users. User-friendly interfaces, comprehensive APIs, pre-trained model collections, and platforms that enable model fine-tuning, as well as on-demand models, are available, making the deployment of complex AI software development in business and development processes simple. However, companies need to choose the right tool for their goals and apply it correctly, often requiring AI consulting services.

In which cases is it worth using generative AI?

Automation: AI automates repetitive tasks, freeing up valuable workforce.
Efficiency Improvement: It enhances operational process efficiency, reduces errors, and increases productivity, which are key focuses of AI development services.
Decision support: It helps in analyzing large amounts of data, and supporting decision-making processes and forecasts, a capability that AI consulting can help implement.
Customer service optimization: It optimizes customer service through chatbots and virtual assistants, an area where contact centre AI solutions are particularly effective.
Cost reduction: AI can reduce operational costs by automating resource-intensive processes, making it an essential part of AI business consulting.

But these benefits can only be achieved if the company adopts them correctly. Here are some industry examples that illustrate when generative AI can and cannot be used.

In the case of e-commerce companies, AI development can be excellently applied to analyze large datasets and create personalized recommendations based on shopping habits, but it is not recommended for handling complaints.
For wholesale companies, AI solutions can assist with inventory management, but they cannot replace human interaction in supplier relations.
In the food industry, AI can make the quality control process—filtering out defective products—more efficient, but it is not advisable to use it for developing flavour profiles.
For insurance companies, AI development companies can create systems that analyze incoming claims images and identify the type or extent of damage, speeding up claim processing. However, AI should not be used for damage calculation as it may overcomplicate the process.
AI can also assist HR professionals, effectively screening incoming resumes and pre-ranking candidates based on their skills and experience. However, it is not advisable to use AI for final interview evaluations, as it cannot fully assess human characteristics.

Artificial intelligence can be integrated into any business process, regardless of the sector. LogiNet created its AI-based efficiency improvement consulting service to help companies propose tailored AI solutions that can make their processes more efficient using AI tools within as little as four weeks.

What criteria should a company consider when choosing a generative AI solution?

It's important to understand that generative AI is not a panacea; it doesn't provide solutions to everything, as there are many processes where better, non-generative AI-based solutions exist.

Here are six criteria that characterize a good generative AI application.

Solving boring tasks requiring moderate creativity: This could be correcting the spelling of an article, but it is not yet suitable for the creative part, such as writing original and engaging content.
Interpreting unstructured text (images): Previously, the computer had to be instructed precisely and accurately about what was expected of it. This has changed, as it can now interpret an image, for example, but it is not advisable to use it for pricing.
Tasks not solvable with traditional algorithms: Generative applications are good for certain tasks, such as determining whether an article is more about economics or technology, but it is not an AI task to count how many times the word "economy" or "technology" appears in an article.
Working with large volumes of text, information: If many tasks need to be processed, it can significantly speed up the work. For example, one can ask the application to read the company's entire document archive before answering a question, but it is unlikely to be able to determine who should approve offers over 100,000 euros.
"Good enough is good enough": Using AI applications will not produce a perfect result. This must be accepted when using AI, and one should prepare for it. For example, it is not critical if the result of translating a recipe into English is not 100% perfect, but if an instruction manual for an aircraft is being created for a pilot, this could be a problem.
The goal is to enhance human efficiency: When using AI, humans cannot be left out of the workflow, but if part of their work is done by AI, this speeds up the processes. For example, AI can create potential diagnoses for a doctor or draft a response related to a complaint for customer service, but it would be risky to use AI to make the diagnosis for the patient or write the response to the customer complaint.

How can you identify a problem that can be solved with AI?

It is worth considering AI discovery, which involves a multi-step process. First, the company should map out what each tool is good for, what its characteristics are, and in which tasks it is useful, illustrated with use cases. Then, it should consider corporate processes and see which aligns with the six criteria previously outlined. After this, the company should create a feasibility application (Proof of Concept, PoC) to solve the selected problem, which can reveal the project's success indicators. If these steps are followed, the company is likely to create successful projects that genuinely enhance efficiency.

AI solutions from the perspective of companies

In practice, companies can leverage generative AI in various ways to optimize their operations and achieve significant benefits. By focusing on key areas such as automation, efficiency improvement, and customer service optimization, businesses can unlock the potential of AI to enhance decision-making processes, reduce operational costs, and increase productivity with AI business consulting.

AI usage within the company can only spread if employees are encouraged. This could be an internal competition where ideas are solicited from colleagues or the formation of small groups where such methods are tried in specific processes. Experience shows that even though AI usage may be possible, employees will not use it on their own.
AI is most commonly used for drafting social media posts, and emails, generating images, and brainstorming campaign ideas. In none of these areas could it replace the staff, but it is optimal for better distributing the workload and speeding up the work.
It cannot fully replace the work of customer service or telesales, but it can already handle basic tasks in chat.
For e-commerce companies, AI is ideal for conversion optimization, as it provides several tools to analyze processes, offering AI solutions to improve productivity in key sectors.
Webshops considering international expansion can find AI a significant help in translating Hungarian content, significantly speeding up the work.

Are you interested in optimizing your company’s processes using artificial intelligence tools? Do you want to harness the potential of generative AI? With LogiNet’s AI-based efficiency improvement consulting service, you can enhance your company’s processes within as little as 4 weeks using AI tools.

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