How AI can help companies

As AI evolves, it has the potential to transform businesses fundamentally. From streamlining business operations to enhancing customer service experiences, AI can help you remain competitive, especially within industries experiencing rapid change.

Here are the various ways artificial intelligence skills can boost growth and efficiency, so you understand why bridging the AI skills gap is so important in the modern business world:

• Increased efficiency: AI allows you to automate routine tasks, including data entry and processes that require adaptive responses, freeing up employees for work that needs human input.

• Enhanced data analysis: artificial intelligence helps companies identify trends and insights humans might miss by analysing vast amounts of data at high speed, supporting improved decision-making.

• Improved customer service: AI personalises interactions, provides 24/7 customer service via chatbots, and tailors product recommendations based on previous purchases.

• Operational automation: AI supports supply chain logistics and financial operations, optimising the time spent on these processes and reducing potentially costly errors.

• Streamlined HR processes: AI assists your HR department with tasks such as speeding up the screening of CVs, tracking employee performance and predicting workforce needs.

Understanding the AI skills gap

The AI skills gap refers to the difference between your workforce’s current capabilities and the advanced skills required for effective use of this emerging technology. In industries such as technology, finance and manufacturing, employers are actively seeking employees who understand AI. For example, high-demand roles to bridge the AI skills gap include:

• Data scientists to analyse complex datasets
• Machine learning engineers to track emerging AI trends and help your organisation find novel solutions to pressing problems
• AI ethicists to navigate the ethical implications of AI, including setting policies for responsible use and ensuring compliance with emerging regulations

To help address the AI skills gap, follow these steps:

• Identify where in your company artificial intelligence may have an impact
• Assess AI readiness in those areas, and look for gaps in expertise that prevent you from fully realising this technology’s potential
• Create targeted training programmes to build the necessary skills
• Recruit strategically to cultivate a well-rounded workforce with a firm grasp of the tech

Understanding where you have an AI skills gap and having people in place who know how to use artificial intelligence well can help your company compete in a digitally driven marketplace.

Artificial intelligence skills and roles

Bridging the AI skills gap requires filling certain roles with candidates who can design, train and manage AI systems effectively. Each position that uses this technology has unique responsibilities that contribute to ethical development and deployment. Here are several roles critical to adding artificial intelligence skills to your organisation and the specific expertise required for each.

Data science

Data science focuses on extracting meaningful insights from large sets of structured and unstructured information. Data scientists combine this analysis with machine learning algorithms and statistical methodologies to solve complex problems and predict patterns. These tasks, in turn, improve decision-making processes and deliver actionable insights.

Work within this role includes preparing the data for analysis, creating predictive models, and interpreting results. When recruiting a data scientist, look for a blend of maths skills and a computer science background to find candidates who can deliver data-driven solutions.

Machine learning

Machine learning (ML) is a subset of AI focused on algorithm and statistical model development. ML enables computers to perform specific tasks without operator input or instructions, continuously improving performance with exposure to more data.

Machine learning (ML) engineers design and implement these models, choosing the correct datasets for training and fine-tuning parameters to optimise performance over time. When recruiting an ML engineer, seek candidates with strong programming skills and proven ability to manage large amounts of data.

Natural language processing

Employees who use natural language processing (NLP) sort and analyse large amounts of data, feeding it into the AI. This helps artificial intelligence understand and interpret human languages, allowing better contextual connections.

NLP specialists may train AI chatbots to provide intuitive results or analyse customer sentiment data. When recruiting for this role, look for NLP specialists with a linguistics background who also understand machine learning.

AI research

AI researchers develop methodologies and technologies that solve complex problems. This largely academic role involves experimentation and innovation. It explores neural networking possibilities and works to improve existing AI algorithms. Recruit AI research specialists by seeking candidates with excellent maths and computer science skills and an advanced understanding of AI technologies.

AI ethics

While artificial intelligence solves many problems, it introduces others – that’s where specialists in AI ethics come in. AI ethicists promote using this technology for societal wellbeing. These professionals explore the moral implications of AI and attempt to prevent bias from arising in its use.

To do this, AI ethicists develop guidelines for responsible AI use within their organisations, assess employee displacement impacts and work with engineers to ensure ethical design and deployment. When recruiting for this role, look for a background in philosophy, law or social science combined with a speciality in AI technology.

Ways to close the AI skills gap

Because artificial intelligence offers such a game-changing effect on various industries, competition for professionals who can effectively develop chatbots, analyse data and engineer prompts continues to grow. So many openings for so few quality candidates means employers must often go the extra mile to find the professionals they need to bridge the AI skills gap. Fortunately, you can boost your chances of attracting top talent with these strategies for adding artificial intelligence skills to your organisation.

Education and training programmes

One of the best ways to get the workers you need is to retrain the employees you already have. AI has the potential to displace some employees, so finding ways to reintegrate them saves your company time and money. You can use that saving to create comprehensive training programmes to upskill existing workers, reducing recruitment costs down the road.

To retrain your current staff, partner with local or online universities and technical schools that align with your needs. Provide workshops, seminars and courses that smooth the transition from employees’ current positions to new AI-focused roles.

Recruitment

Changing the way you recruit new employees also helps you bridge the AI skills gap. For instance, you may need to completely rewrite job descriptions and change their requirements so potential candidates understand what you need for the role. 

Likewise, you might broaden your search to professionals in related fields who have transferable skills or include workers with non-traditional backgrounds, such as contractors with previous experience.

If your HR department already leverages AI, it might use those tools to seek out candidates with AI skills. It can also recruit at industry conferences, ethical hacking events and on social media to reach a broader range of potential candidates.

AI challenges and considerations

As the business world continues to embrace AI to enhance operations and improve services, a variety of challenges and considerations arise. For instance, workers may resist changes without clear-cut communication that helps them view AI as a tool rather than a threat to job security. 

Additionally, training costs and new tech may not provide the expected return on investment or increase profits. Compliance and regulatory issues can also make AI systems challenging to deploy in some industries.

The introduction of artificial intelligence continues to change the way the world does business. Stay on top of trends by finding ways to bridge the AI skills gap within your organisation, which will set a tone for improved performance going forward.