The nature of the workplace has changed dramatically over the past decade, due in large part to Artificial intelligence (AI) technologies12. AI programs are already being used – and further advanced – for such tasks as analyzing customer data, improving employee performance, and, of course, replacing humans in repetitive and tedious jobs34. What will workplaces look like a decade or two down the line? What do these kinds of tools mean for the employees and employers of the future?56

AI, which encompasses technologies such as machine learning, natural language processing, and robotics, is a set of tools that allows computers to analyze data, detect patterns, and accomplish otherwise human-performed tasks12. As companies implement AI into their workflows, they are identifying the tool's ability to increase productivity, decrease overheads, and enhance the level of precision34.

Whether in the form of robotics, chatbots, robotic process automation (RPA), or some other innovation, the theme of automation has been a major driver of work evolution over the past several decades12. However, with AI, automation has reached its next level. A growing number of tasks involving simple decision-making or data processing can now be carried out by intelligent algorithms3. Take customer support, for example. Today, customers often get automated responses to their inquiries via chatbots4. Or think about basic data processing tasks, such as scheduling and data entry. This can now be done by machines through RPA, which is more efficient and less prone to errors than humans12. This shift presents existential questions about which job roles will survive. There is a widespread fear that jobs will be replaced by AI; in reality, experts believe that jobs will be transformed, with employees released from drudgery to do more strategic, creative, and people-focused work5.

AI tools can help to boost productivity in several ways. For example, they can relieve employees of doing routine activities. This frees up time to perform high-value-added activities. For example, AI-supported project management systems can read the roadmap and schedule of a project and map the resources needed. It can even predict the risks of the project for the team so that they work more effectively.12 Furthermore, it can help with workflow optimization, looking at bottlenecks and recommending how to clear them. With predictive analytics, companies can guess what demand will look like and get ready for it.34

As more data becomes available at a faster rate, AI's quick and accurate processing provides more meaningful data points from which decisions can be driven. Some AI systems can find patterns within massive amounts of data that would otherwise remain obscure to human users and enable them to make decisions with far more data points than ever before12. For instance, sales teams can use AI to determine what types of customers respond best to certain offerings and how best to engage with them. Marketing departments can apply AI algorithms to optimize ad targeting and ensure that customers see the right ads at the right times3. In finance, AI can help monitor risk and detect fraud across vast pools of data to help boost a company's bottom line4.

By building human capital – investing in training and creating more experiential work cultures and cultures of lifelong learning – organizations can provide employees with the tools they need to work alongside AI12. This isn't limited to just technical skills, but soft skills like critical reasoning, emotional intelligence, creativity, and the ability to problem-solve and communicate in ways that will always remain uniquely human34.

AI is good at doing things that repeat, but it's not great at being creative. So, now employees are given a chance to be innovative, brainstorming new approaches and solutions to problems, and finding novel ways to enhance customer experiences. For instance, in the field of design, AI can create prototypes, as well as assist with technical aspects, while freeing the designer to focus on conceptualizing and refining their ideas. Likewise, in the realm of textual writing, AI can perform grammar and style checks, allowing the writer to focus on their narrative and messages.12

The increased use of AI for work also raises ethical issues for organizations, including the proper treatment of data, the potential for algorithmic bias, and the impact of automation on jobs.12 As AI systems increasingly depend on data, the safety and secrecy of that data is a top priority. Companies must reveal how they acquire and use data, especially when it comes to sensitive information collected from employees and customers. Vigorous data-protection measures not only comply with legislation but also help to win the confidence of stakeholders.3 A second problem is the possibility of bias in AI algorithms: if the data used to train the system is tilted or unrepresentative in certain ways, the results could reinforce existing inequalities.4 Whenever there is a 'black box' in one aspect of a system, there is likely a corresponding lack of control over an unknown (but potentially important) aspect of its operation. Organizations that care about running fair processes have to be at least as careful about monitoring and testing any AI system they use.5

While AI can increase productivity, it can also be a job killer. Some roles will no longer exist, and we could have millions of workers without a job. Companies have to be more responsible about this transition, helping displaced workers through career counseling or other forms of assistance.12 Studies suggest that up to 30% of jobs could be at risk of automation by the early 2030s, with sectors like manufacturing, retail, and transportation being particularly vulnerable.2 However, AI is also expected to create new roles, potentially displacing 85 million jobs while creating 97 million new ones by 2025.3 To mitigate negative impacts, companies should focus on reskilling and upskilling their workforce, while policymakers consider implementing strong worker protections and enhancing social safety nets.34

Looking to the future, work is likely to be increasingly augmented by AI. The next generation of such tools will likely become more human-like, and in turn, make our collaboration more effective. If the COVID-19 pandemic has taught us anything, it's that remote work is here to stay, and AI tools will enable geographically dispersed teams to communicate and collaborate seamlessly together. Naturally, leaders will have the ultimate responsibility here, setting the tone for how their organizations navigate this transformation, for better or worse. They will need to build, sustain and educate a culture of innovation and change, and to support and empower their employees to probe not only what AI can do for them – but what they can do with AI. There will have to be clear and regular communication about these changes so that employees can understand and embrace them.

The reality about the future of work is that we can confidently state that it's closely tied to emerging AI technologies. By automating mundane activities and enabling us to delegate more business processes to machines, AI will help us free us up for more people-centered pursuits – such as making better decisions, exploring creativity, and finding more stimulating ways to spend our time.12 This shift towards human-AI collaboration is expected to enhance productivity and innovation across various industries.3 For instance, in healthcare, AI-powered systems can handle routine tasks like monitoring vital signs, allowing medical professionals to focus on complex patient care and critical decision-making.4 However, this transition also presents challenges, including the need for workforce reskilling and addressing potential job displacements, emphasizing the importance of proactive measures to ensure a smooth evolution of work in the AI era.56