Preparing the Workforce: A Guide to AI Training and Development for Employees

It’s no longer news that the advancement in artificial intelligence has taken the world of work by storm, reshaping industries and redefining job responsibilities by the minute. A recent study by the AI-Enabled ICT Workforce Consortium finds that 92% of ICT jobs are expected to be, at least, moderately influenced by this change. In this era, AI-centric skills will progressively rise in importance. The writing on the wall is that organizations must prioritize AI training for their employees to stay afloat. AI literacy will position the workforce to work effectively alongside various AI systems. 

This post unpacks different AI technologies, examining how they’re used at work, and the strategies managers can use to upskill their employees to meet the needs of working with these technologies. 

Natural Language Processing (NLP) 

Natural Language Processing is an AI technology that bridges the gap between human language and computer understanding. It does this by enabling computers to read, understand, and generate language in a meaningful way. 

NLP can be used to power customer service and support; its text and speech understanding functionality helps chatbots and virtual assistants handle routine customer queries. Through text mining and sentiment analysis, it can extract insights from large volumes of text and aid organizations to understand feedback. 

Edge AI and Internet of Things (IoT) 

Edge AI is the deployment of AI algorithms directly on devices without the need for constant connection to cloud servers. The Internet of Things is a network of physical devices with built-in software that allows them to collect, exchange, and act on data. 

These complementary technologies enable efficient operations by blending connected devices with real-time intelligence. The synergy can come in handy in industrial operations, helping machines adjust automatically or alert maintenance teams to prevent breakdowns. Similarly, in healthcare, medical facilities can use IoT in equipment to monitor patients and the environment while Edge AI analyzes the information to detect emergencies and irregularities. 

Robotic Process Automation

This technology uses software robots, popularly known as bots, to automate repetitive tasks. It interacts with applications at the user interface level and mimics human actions on a computer. Automating routine tasks across an organization’s departments helps the business save time, reduce mistakes, and increase productivity. 

Robotic process automation is beneficial and relevant in multiple aspects of work. When implemented in recruitment, it can reduce candidate ghosting and improve the entire candidate experience. It can help finance teams reconcile accounts and ensure consistency by comparing transaction records across systems. 

The bots can also process invoices by reading them, extracting data, and validating the invoices against purchase orders. Bots can enhance administrative tasks and operations by facilitating data migration between systems. They can also conduct routine audits and gather data from multiple sources for report generation.  

Generative AI

Currently enjoying a meteoric rise in popularity, generative AI is an AI technology that mimics human creativity and reasoning, all to create original content. The output can take the form of text, audio, video, image, or code. 

Generative AI has proven immensely relevant in powering marketing aspirations. Its text, image, and audiovisual generative capabilities facilitate content production. While it has its downsides, in the right hands, it can be used to generate engaging and accurate content. 

Brands can power their communication with this technology. Generative AI can summarize email threads and draft messages. It can be used to make accurate translations, supporting multilingual communication. 

Analytics

AI can be used to examine large datasets, uncover patterns, and generate insights that support informed decisions. AI-driven analytics is fast and accurate. It can be descriptive, explaining what happened, or diagnostic, explaining why something happened.

Predictive analytics foretells what’s likely to happen while prescriptive analytics suggests what to do. 

Analytics, as a type of AI technology, helps organizations turn data into actionable insights. It enhances business reporting by highlighting trends and exceptions. Analytics help HR teams with workforce planning, a major ingredient in talent intelligence. It can also help teams figure out industry-wide hiring trends, and with predictive analytics, organizations can accurately identify who may leave the team soon. 

4 Strategies to Upskill Employees to Work With AI Technologies Effectively

Here are four proven ways to implement AI training for your employees.   

1. Offer technical and non-technical training

To upskill your team members to use the various AI technologies, consider kicking off with non-technical training. Introductory workshops on basic concepts of language models, tokenization, sentiment analysis, and deep learning models can give a foundational understanding of how these technologies work. 

Provide technical training on how to use these systems. Guest lectures by AI specialists or courses on learning platforms are good starting points. 

2. Provide access to tools and infrastructure 

Giving team members access to tools and infrastructure exposes them to workflows that are currently becoming standard across industries. Access to AI platforms can enhance their understanding of the limitations, leading to more confident and responsible use. 

3. Encourage practice and experimentation 

Thorough AI training for employees requires bridging the gap between theoretical knowledge and real-world application. It’s important to create a safe environment for iteration and innovation; it can help your workforce view AI technologies as actual change enablers. Repetition can enhance their fluency in AI technology, while exploration can uncover novel applications that will boost productivity.  

4. Prioritise cross-functional collaboration

Organizations often have individuals in different departments with diverse skills. When these team members from different departments work together to achieve a common goal, they often share knowledge. Employees with strong AI competencies can share insights and best practices with other team members, enhancing their AI literacy. 

AI training for employees doesn’t have to be chaotic. Implement these strategies to ensure that your workforce is equipped for the AI-driven future of work.