AI application areas
With AI credited for enhancing productivity, driving innovation, and streamlining operations, let’s take a look at some of the main AI applications in business:
Automation and increasing efficiency - One of the most obvious advantages of AI is its ability to automate repetitive tasks. This ranges from simple tasks like data maintenance to more complex processes such as the analysis of vast amounts of data. Assigning these tasks to AI, allows employees to focus on more demanding and value-adding operations. Concurrently, this offers companies the opportunity to partially compensate for the shortage of skilled workers.
Customer service - AI-driven chatbots and virtual assistants can revolutionise customer service by being available around the clock and providing instant, personalised responses to customer queries. This not only increases customer satisfaction but also frees up employees to focus on more complex queries.
Decision-making - With the ability to analyse large amounts of data and recognise patterns, AI can provide valuable insights to help decision-makers formulate strategies. From market analysis to risk assessment, AI can be a powerful tool for making informed decisions.
Once you’re certain about how you’d like to integrate AI into your business, it’s time to empower your employees. Knowing how to use AI is critical to minimising issues and maximising results, so be sure to follow the recommendations below:
Understand the basics of AI
The first step in preparing employees is to give them a basic understanding of AI technologies. This includes not only how the technology works, but also ethical considerations. The latter is about creating mindfulness amongst the workforce about AI, data, regulatory requirements, and violations of personal data protection. In addition, it is also about the potential impact on one's own workplace and how the range of activities may change or be transformed.
Develop specific training for specialist applications
Depending on the area of application of AI in an organisation, specific training programs should be developed that focus on the relevant applications and tools. Whether it is the use of AI-driven analysis tools or interaction with chatbots, employees need to know how to use AI technologies effectively and how they can add value to their day-to-day experience at work.
Foster creativity and problem-solving skills
In a work environment shaped by AI, soft skills such as creativity, critical thinking, and the ability to solve problems are becoming increasingly important. Training should therefore aim to promote these skills to prepare employees to work with AI and leverage its potential. It is also important to master what is known as correct prompting at this point. Prompting refers to the method used to enter queries, commands, or an order into an AI tool to generate corresponding results. Prompting should not be equated with entering data into an internet search engine such as Google. Employees need to understand the detailed requirements of AI tools to obtain meaningful results.
Promote continuous learning and adaptation
The landscape of AI technology is rapidly evolving. Therefore, companies must promote a culture of lifelong learning to ensure that their employees stay abreast of the latest technology while adapting to new developments. Numerous training providers specialise in providing training in AI knowledge and skills.
Choosing the right provider depends on various factors, such as the specific learning objective, the level of prior knowledge, the desired learning format (online or face-to-face) and the budget.
Below are some recognised platforms and institutes that offer high-quality AI training courses:
Online platforms
1. XueTangX
Overview: A MOOC platform initiated by Tsinghua University, offering a wide range of AI courses delivered by top universities in China and abroad.
What’s covered: Machine learning, deep learning, natural language processing and more.
Best for: Learners ranging from beginners to those seeking advanced knowledge.
2. China University MOOC
Overview: Collaborates with numerous universities to provide structured AI course pathways.
What’s covered: Core AI concepts, Python programming, data science and related foundational modules.
Best for: Learners seeking a systematic understanding of AI theory.
3. NetEase Cloud Classroom
Overview: Offers a wealth of practical, hands-on AI courses, with some instructed by industry veterans.
What’s covered: Applied machine learning, deep learning frameworks such as TensorFlow and PyTorch.
Best for: Learners who prefer learning through real‑world applications and hands-on experience.
4. Tencent Classroom
Overview: Offers AI courses ranging from introductory to advanced topics, closely aligned with current industry demands.
What’s covered: AI programming, computer vision, natural language processing and other in‑demand specialisms.
Best for: Learners aiming to build job‑ready skills quickly.
Specialised institutes and organisations
1. Baidu PaddlePaddle – AI Studio
Baidu’s deep‑learning platform offers a solid mix of free courses, hands‑on projects and open competitions.
What makes it stand out: Strong alignment with China’s home‑grown AI frameworks, making it a practical choice for those interested in industry‑level applications.
2. Huawei Cloud Developer Institute
Huawei Cloud provides a comprehensive learning environment covering AI courses, guided labs and certification pathways.
Best for: Developers who want to learn AI in combination with cloud‑based tools and services.
3. Alibaba Cloud Academy
Part of Alibaba Cloud’s education ecosystem, this platform focuses on the intersection of cloud computing and AI. It includes step‑by‑step tutorials for Alibaba Cloud’s AI tools and services.
Best for: Learners who are keen to explore AI development in a cloud‑native environment.
4. DeepBlue Academy
Known for its strong focus on cutting‑edge AI fields including SLAM and knowledge graphs, DeepBlue offers intensive courses designed to push learners further.
Highlights: Small‑group teaching, personalised feedback from instructors and project‑based learning using enterprise‑level scenarios.
5. Greedy Technology
This provider focuses on career‑oriented programmes such as AI Algorithm Engineer and NLP Engineer tracks.
Highlights: One‑to‑one career planning and access to referral opportunities with well‑known companies.
AI upskilling strategies
While tailored training programs and learning institutions are highly valuable when teaching employees how to use AI, it’s important to continually develop ways to upskill your team.
If you’re looking for some additional upskilling strategies (outside of the formal training methods), why not try the below:
Encourage participation in workshops and boot camps: To help employees gain practical skills quickly. These can be run in-house or through external providers or other specialised training organisations.
Foster collaborative learning: To encourage teamwork, innovation, and peer-to-peer learning. Group projects provide a useful way for employees to enhance their understanding of AI concepts.
Implement mentorship programs: To provide personalised guidance and support. Be sure to pair less experienced employees with internal AI experts to boost the benefits of one-on-one learning.
Invest in continuous learning: To enhance competitiveness and innovation. Encourage employees to stay updated with the latest AI developments by providing access to resources such as industry journals, webinars, and conferences.
Provide hands-on learning and problem-solving opportunities: To help employees apply their skills. Projects and case studies give employees the chance to turn theory into practice, demonstrating the tangible impact of AI on the business.
AI - risks and challenges
While it’s clear that AI has enormous potential to boost business outcomes, it must be noted that the technology comes with its own set of risks and challenges. Knowing what to watch out for will empower your organisation to leverage this revolutionary tech in a way that’s successful, ethical, and transparent.
To that end, be mindful of:
Data privacy issues -With AI systems requiring large amounts of data, there are natural concerns around data privacy and security. Responsible AI compliance and governance are crucial!
Job displacement: Due to its ability to automate, AI can lead to job displacement. Companies must manage this transition carefully, offering retraining and support for affected employees.
Bias in AI systems: AI algorithms can unintentionally perpetuate existing biases within the training data. Regular audits and diverse data sets are essential to overcoming this.
Integration difficulties: It can be complex (and costly) to integrate AI with existing systems. Thorough planning and phased implementation are key!
Change management: New AI technologies can cause apprehension amongst employees. Replace reservations with positive attitudes through open communication and effective training.
The introduction of AI provides organisations with the opportunity to transform their operations, gain a competitive advantage, and counter the skills shortage with technology. However, this change requires comprehensive conditioning of the employees who must learn how to use AI. Through targeted training programs and fostering a culture of continuous learning, companies can ensure that their teams not only meet the challenges of the AI era but also play a proactive role in shaping it. The future belongs to those who are willing to adapt, learn, and go hand in hand with AI.
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