Setup for success - How to use AI in your business

  1. Understand the basics of AI
  2. Develop specific training for specialist applications
  3. Foster creativity and problem-solving skills
  4. Promote continuous learning and adaptation
Estimated Read Time: 4 minutes

Implementing artificial intelligence (AI) into a company's ecosystem is no longer a futuristic scenario, but a concrete reality that companies in various industries are already experiencing and shaping today.

A survey conducted by the Hong Kong Wireless Technology Industry Association in 2024 found 85% of Hong Kong companies now embrace AI in operations but lags slightly behind the 93% observed in the rest of Asia.

It’s little surprise given AI’s power to increase efficiency and tap into new value creation potential. Whether deployed to tackle the automation of recurring tasks or the optimisation of decision-making processes, one thing’s for sure – AI is here to stay.

In this blog, we’ll learn more about how companies can train their employees and educate them so you can effectively use AI in your business. From the opportunities to the risks, we’ll explore everything you need to know about using this revolutionary technology in the workplace.

How to use AI in your business

David Jones, Senior Managing Director at Robert Half APAC, believes AI is often misunderstood. He says, “AI holds tremendous potential and that in itself makes people apprehensive. When it comes to how to use AI, I always caution businesses to deploy a people-centred approach.”

“Before you decide what applications are best for your business, know that AI should be seen as a tool to augment rather than replace the human workforce. If you sense employee hesitation, be sure to stress that humans have qualities that AI does not - creativity, emotional intelligence, and complex problem-solving skills. AI cannot replicate these skills but, it can offer efficiency and data processing capabilities that amplify human potential,” David says.

What’s certain is the importance of upskilling employees and fostering a culture of collaboration between humans and AI applications to foster a more dynamic and resilient workforce.

Related: 5 skills to shape modern leadership styles for Hong Kong executives

AI Application Areas

The Hong Kong Productivity Council (HKPC) AI Adoption study found that companies using AI in Hong Kong reported an average increase in productivity of 15%.

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:

  1. 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.
  2. 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.
  3. 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.

David says there’s no one-size-fits-all approach when it comes to AI. “If you’re wondering how to use AI in your business, start by looking at your competitors and industry leaders. In my experience, most industries in Hong Kong are honing in on the distinct ways that AI applications can sharpen their competitive edge. The way a healthcare business uses AI is going to be very different to the way a finance business uses it, so be sure that your applications are going to be relevant and revolutionary.”

Unsure about the practical implications of AI in your field? Let’s take a look at how to use AI across different industries:

  • Finance – AI is helping to improve accuracy and efficiency through bespoke algorithms that detect fraud, assess credit risk, and offer financial advice. Automated trading systems help to enhance profitability while AI chatbots help to provide 24/7 customer service.
  • Retail – AI is proving valuable for enriching customer experiences and streamlining operations. Systems work to analyse customer behaviour and preferences to suggest products, boost sales, and increase customer satisfaction. Virtual AI-driven assistants provide around-the-clock support to resolve issues promptly.
  • Healthcare – AI is raising the stakes when it comes to diagnostics and treatment. Machine learning algorithms are proving valuable in the detection of conditions like cancer in medical images. Predictive analytics also help to improve patient outcomes by flagging those at risk of chronic conditions and diseases.
  • Human Resources – AI is streamlining HR recruitment and employee management processes. AI-driven recruitment tools aid in initial application processes, identifying suitable candidates to boost the quality of new hires. AI analytics also help to monitor employee performance and engagement, informing retention strategies.
  • Manufacturing – AI is changing the face of manufacturing through automation and predictive maintenance. AI-powered robots perform routine tasks with high precision and low error rates. Predictive maintenance uses AI to evaluate machinery data to predict errors before their occurrence, mitigating issues and downtime.

Related: The impact of artificial intelligence in the workplace

Training employees for the AI era

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:

1. 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

  • LinkedIn Learning: Offers a wide range of courses in AI and machine learning that are ideal for professionals to enhance their skills.
  • Coursera: Offers courses and specialisations in AI offered by leading universities and companies such as Stanford University and Google Cloud.
  • Udacity: Specialised in technology-focused courses, including nano degree programs in AI and machine learning, which have been developed in collaboration with industry experts.
  • edX: A platform launched by Harvard and MIT offering a variety of AI and computer science courses from universities around the world.

Specialised institutes and organisations

  • DeepLearning.AI: Founded by Andrew Ng, one of the most prominent names in AI, DeepLearning.AI offers specialised courses in deep learning and machine learning.
  • MIT Professional Education: Offers advanced courses in artificial intelligence and machine learning for professionals who want to deepen their knowledge.
  • NVIDIA Deep Learning Institute: Provides hands-on training in AI and deep learning tailored to the use of NVIDIA technology.
  • Simplilearn: A platform that offers professional certifications and training, including courses in AI and machine learning developed in collaboration with leading companies and universities.
  • Fraunhofer Big Data and Artificial Intelligence Alliance: Offers a wide range of training courses on data science and AI.
  • European Information Technologies Certification Academy: The European Academy based in Brussels offers fully online and internationally accessible programs. It is managed by the European Institute for IT Certification and sets a standard in digital skills certification.

Face-to-face training and workshops.

Many local universities and technical schools also offer courses and workshops in AI. These include:

  • The Hong Kong University of Science and Technology (HKUST)
  • The University of Hong Kong (HKU)
  • The Chinese University of Hong Kong (CUHK)
  • City University of Hong Kong (CityU)
  • The Hong Kong Polytechnic University (PolyU)

Training through such institutions can be particularly valuable if you value direct interaction with lecturers and fellow students. Before deciding on a training provider, take the time to research reviews and testimonials from previous participants.

Be sure to carefully check the course content and, if necessary, take advantage of free trial offers to ensure that the course meets your requirements.

AI upskilling strategies

While tailored training programs and learning institutions are highly valuable when teaching employees how to use AI in your business, it’s important to continually develop ways to upskill your team.

David says, “AI training is not a ‘one-off’ session. AI itself is rapidly evolving and organisational training needs to support this. One online course won’t suffice – take the time to invest in continuous and collaborative learning that will help your employees to grow with AI.”

If you’re looking for some additional upskilling strategies (outside of the formal training methods), why not try the below:

  1. Encourage participation in workshops and boot camps – To help employees gain practical skills quickly. These can be run in-house or through external providers like SANS Institute or other specialised training organizations.
  2. 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.
  3. 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.
  4. 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.
  5. 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.

David believes that all training and upskilling initiatives must be regularly reviewed to track their effectiveness. He says, “Don’t assume that your initial AI training programs will be a magic bullet. Despite your best intentions, they will prove useless if they aren’t carefully critiqued. To ensure business growth, be sure to review each program against key metrics.”

Below are some important metrics to consider:

  • Performance improvement – Track changes in efficiency and accuracy before and after the training.
  • Skill proficiency – Deploy practical tests to assess employ proficiency with AI tools.
  • Productivity metrics - Assess any productivity ‘wins’, such as time savings, increased output, and reduced error rates.
  • Employee Feedback – Take the time to gather employee feedback about AI applications.
  • Business outcomes - Evaluate the impact on wider business goals such as revenue growth, cost savings, and employee satisfaction.

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:

  1. 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!
  2. 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.
  3. 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.
  4. Integration difficulties: It can be complex (and costly) to integrate AI with existing systems. Thorough planning and phased implementation are key!
  5. Change management: New AI technologies can cause apprehension amongst employees. Replace reservations with positive attitudes through open communication and effective training.

Related: What will be the future impact of AI technology on the workplace?

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 in your business. 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.