How AI can help companies
As AI evolves, it has the potential to fundamentally transform businesses. From streamlining business operations to enhancing customer service experiences, AI can help you remain competitive, especially within industries experiencing rapid change.
Let’s look at 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 lets you 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 better identify trends and insights that humans might miss by analysing vast amounts of data at superfast speeds for improved decision-making.
- Improved customer service: AI personalises human interactions, provides 24/7 customer service via chatbots and tailors product recommendations based on previous purchases.
- Operational automation: AI helps with 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 various tasks, such as helping to speed up the screening of resumes, tracking employee performance and predicting the needs of your workforce.
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 data sets
- 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 programs to build the necessary skills
- hire 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. Let’s take a look at several roles critical to adding artificial intelligence skills to your organisation and the specific expertise required for each one.
Data science
Data science focuses on extracting meaningful insights from large sets of structured and unstructured data. Data scientists pair this analysis with machine learning algorithms and statistical methodology 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 hiring 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 focusing on algorithm and statistical model development. ML lets computers perform specific tasks without operator input or instructions, continuously improving performance with exposure to more and more data.
Machine learning (ML) engineers design and implement these models, choosing the correct data sets for training their models and fine-tuning parameters to optimise performance over time. When hiring for an ML engineer, seek out candidates with excellent programming skills and a 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 input helps artificial intelligence understand and interpret human languages so it can make better contextual connections that it might not otherwise comprehend.
NLP specialists have a variety of duties, from training AI chatbots to provide intuitive results to analysing customer sentiment that goes into the inputs. When hiring for this role, look for NLP specialists with a linguistics background who 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. Hire 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. They 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 hiring 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 that employers must often go the extra mile to find the people 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 programs
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 programs to upskill existing workers, reducing hiring costs down the road.
To retrain your current staff, partner with local or online universities and technical colleges that align with your needs. Provide workshops, seminars and courses that smooth the transition from employees’ current positions to new AI-focused roles.
Recruitment and hiring
Changing the way you recruit and hire 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 that 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.
