How does AI transform the way employees work and interact with their employers?<\/p>\n
One thing that immediately comes to mind is automating routine tasks.<\/p>\n
You might have heard that AI is great for outsourcing manual or repetitive tasks, and that\u2019s exactly right. It can free up employees from these (at times mind-numbing) tasks, and allow them to focus on value-adding to the company in other ways.<\/p>\n
In this blog post, we take a deep dive into automation with AI, and some of the ways that AI has changed the employee experience of tech companies<\/a>.<\/p>\n Read on to find out more!<\/p>\n Like we mentioned, one of the primary benefits of AI in the workplace is its ability to automate routine tasks<\/a>.<\/p>\n This frees up employees to focus on higher-value work.<\/p>\n For example, in tech companies, AI can be used to automate the testing of software applications. This saves time and also reduces the risk of human error.<\/p>\n In addition, AI can be used to automate repetitive tasks like data entry or email management (these tasks may not be unique to the tech industry, but that doesn\u2019t take away from the fact that tech employees still have to grapple with them).<\/p>\n Through the lens of an employee, that\u2019s huge \u2014 imagine a world where you can outsource all your tedious, mundane tasks!<\/p>\n Before an employee joins the company, they have to go through recruitment and onboarding processes<\/a>.<\/p>\n Now, these are traditionally time-consuming and resource-intensive, especially in prestigious tech companies where there is often intense competition for top talent.<\/p>\n At a high level, the company\u2019s HR team needs to:<\/p>\n Here\u2019s where AI comes in: tech companies can now automate many of these tasks.<\/p>\n For example, AI-powered chatbots can be used to conduct initial screening interviews with job candidates, saving recruiters time and allowing them to focus on more strategic tasks.<\/p>\n In addition, AI can be used to analyze job descriptions and identify areas for improvement, making it easier for companies to attract the right candidates<\/a>.<\/p>\n Here\u2019s an example: Unilever uses AI<\/a> to conduct initial screening interviews with job candidates. Sounds crazy, right? The company partnered with Pymetrics, an AI recruitment specialist, to create a platform that will help initially assess candidates from their own homes, integrating this into part of their recruitment workflow.<\/p>\n If you\u2019re wondering how it works, the platform relies on a mixture of Natural Language Processing (NLP) and body language analysis to identify which candidates will be the best fit, while also providing real-time feedback to candidates.<\/p>\n (If that sounds familiar, you might know that ChatGPT is built on NLP as well, and uses the same underlying technologies to analyze and understand language).<\/p>\n In any case, Unilever has seen a lot of success with this as it has helped the company reduce recruitment costs and improve the candidate experience.<\/p>\n To be specific, this has led to<\/a>:<\/p>\n In fact, owing to AI, it is said that Unilever has “hired their most diverse class to date!”<\/p>\n We know that many companies are making an effort to ramp up their Diversity & Inclusion efforts \u2014 this is one great way of doing so.<\/p>\n Another thing that AI can do is to provide personalized training and development opportunities for tech employees.<\/p>\n How does this work? By analyzing data on employee performance<\/a>, AI can identify areas where employees may need additional training or development.<\/p>\n Companies can then come up with targeted training programs that are tailored to each employee’s needs.<\/p>\n In addition, AI can be used to provide real-time feedback and coaching to employees, helping them to improve their skills and performance.<\/p>\n Case in point \u2014 IBM developed a tool called Watson Career Coach<\/a> back in 2018, and they\u2019ve been using this tool to do a few things:<\/p>\n Specifically, Watson Career Coach uses machine learning algorithms and natural language processing to analyze employee skills, interests, and career goals, and then provides personalized recommendations for career development and growth.<\/p>\n According to IBM, this tool has drove great outcomes, including increases in employee engagement rates and retention rates.<\/p>\n If you\u2019re an employee who has access to such a tool, you can see how impactful it could be on your career \u2014 it\u2019s essentially a roadmap to helping you grow and advance in the organization.<\/p>\n This is especially gamechanging for tech industries. We know that the tech industry is cutthroat, and that employees can easily get poached by other companies who offer better career growth opportunities.<\/p>\n As such, having personalized training and development opportunities provided by AI can give tech companies a competitive edge in retaining top talent.<\/p>\n And from the employee\u2019s perspective: you get to keep up with new skills and trends to remain relevant in the industry. Again, it\u2019s a win-win!<\/p>\n One key benefit of AI is its ability to provide insights and recommendations that can improve decision-making.<\/p>\n How does this work? AI can be used to analyze data on customer behavior and preferences, helping companies make informed decisions in product development, marketing, and many other functions.<\/p>\n Let\u2019s talk about the product development team of a tech company, for example.<\/p>\n With the help of AI, the product development team can gather insights on customer needs<\/a> and preferences, including which features are most important to them, what problems they face while using the product, and what new functionalities they would like to see added.<\/p>\n By analyzing this data, AI can provide recommendations for product improvements, such as adding new features, changing the user interface, or addressing customer pain points<\/a>.<\/p>\n That\u2019s not all \u2014 AI can also help the product development team to prioritize their efforts by identifying which features or functionalities will have the most significant impact on customer satisfaction and sales. This can save the team time and resources by allowing them to focus on the most important aspects of product development.<\/p>\n Take Salesforce, for example. In 2017, the company developed and started using a tool called Einstein Analytics<\/a>, which it uses to analyze data on customer behavior and preferences.<\/p>\n The platform uses machine learning to identify patterns and trends in customer data, allowing employees to make data-driven decisions about product development and marketing.<\/p>\n <\/p>\n If you\u2019re an employee with access to such a tool, the benefits are obvious \u2014 you have all the data and insights you need to make better decisions, which helps you to hit those KPIs and get the job done!<\/p>\n We\u2019ve saved (arguably) one of the most important points for the last:\u00a0AI can be used to improve employee well-being!<\/p>\n Coming off the pandemic, we can all agree that employee well-being has become a critical concern for businesses. This is especially true for tech businesses, which often have partially or fully remote workforces.<\/p>\n In adapting to new ways of working, many employees have struggled with isolation, stress, and burnout. This is where AI can play a valuable role in supporting employee well-being<\/a>.<\/p>\n For example, companies can use AI-powered tools to monitor employee health and provide personalized recommendations for healthy living.<\/p>\n![\"\"](\"https:\/\/www.sogolytics.com\/blog\/wp-content\/uploads\/2020\/02\/alex-knight-2EJCSULRwC8-unsplash-1024x683.jpg\")
<\/a><\/p>\n1. Automation of routine tasks<\/h2>\n
2. Improving HR processes<\/h2>\n
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3. Personalized training and development<\/h2>\n
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4. Data-driven decision-making<\/h2>\n
5. Improving employee well-being<\/h2>\n
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