Human Resources

The Future of Work: The Age of Smart Machines and Artificial Intelligence

Oct 20, 2021

If you don’t get onboard now, it’ll be too late.

Toby CoxSenior Content Writer
The Future of Work: The Age of Smart Machines and Artificial Intelligence

The future of work is uncertain. Some say robots will dominate the workforce, perhaps eliminating human jobs altogether. The guesswork doesn't stop in imagining possible futures of an even more technology-driven economy. Amid such speculation, it’s easy for business owners to feel unsure about how to plan for the next decade.

In this article, we’ll look at the underlying trend expected to dominate the future workplace: The rise of artificial intelligence (AI). Recently, Gartner made six predictions about how businesses will work by 2028 (full content available to Gartner clients). These got us thinking about two critical impacts AI will have on the future workplace, what these mean for small and midsize businesses, and how business owners and HR leaders can start preparing for these trends in advance.

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Future of workplace: How organizational structure will evolve from 2020 to 2030

Prediction #1: AI will replace a number of middle management jobs

Ever imagined taking orders from a robot? This could soon be a reality.

Machine bosses will replace human bosses by the end of the decade. Algorithms that boss employees around, also known as robobosses, will be responsible for assigning work based on skill sets. Robobosses will also decide whether employees will get a promotion and what their salary increases will be.

Here are the top reasons why businesses will be interested in implementing robobosses:

  • Data-driven decision-making: It’s true that robots can't show emotions or empathy, but there's one area where they can outperform humans: data-driven decision-making. AI can scan large datasets and apply predictive algorithms to provide actionable insights to business owners. For instance, a roboboss can use factors such as efficiency, skill, knowledge, and motivation level to select team members for projects. This practice will ensure that members with the right skill set and work attitude are chosen, which will increase the chances of timely project completion.

  • Cost-effectiveness: Robobosses will take over most middle management tasks, eliminating the need for multiple middle management positions. This will not only lower the salary costs associated with middle managers but also make team management more efficient.

  • Availability: Unlike human bosses, robobosses will be available 24/7, making it easier for businesses to manage a global workforce operating in different time zones.

Impact of this prediction – 2020 vs. 2030

Team composition at the beginning of the decade

Today’s teams comprise employees with expertise in particular skill sets brought together by organizational hierarchy. For instance, a marketing team consists of members who have expertise in search engine optimization (SEO), email marketing, social media marketing, and analytics. Each team has a manager who supervises projects, manages conflicts and people-centric issues, assigns tasks to members, and ensures smooth project execution. The team manager is also responsible for monitoring employee performance and scaling the team size (up or down) as per business requirements.

Team composition at the end of the decade

By the end of the decade, a large number of teams will be autonomous with robobosses responsible for functions currently performed by team managers. Robobosses will manage project allocation, deadlines, delivery, and communication. Smart machines will be responsible for ensuring coordination among different teams, such as sales, marketing, and finance. They will also monitor employee performance and assess the need for upscaling or downsizing based on predicted project workloads.

ValueTeams in 2020Teams in 2030
Organizational structureTeams led by team managersAutonomous teams
Team sizeSmall teams managed by team leaders/managersLarge teams managed by robobosses
Employee designationEmployees in the same team have different domain-specific designations, such as SEO specialist, editor, and email marketing specialistEmployees need to learn diverse skills so there will be fewer designations across the organization. Hierarchy levels to be decided as per employees’ performance, experience, and expertise
Skills valuedGreater emphasis on leadership and collaborationFocus will shift to knowledge and functional expertise
Project managementProject allocation managed by team managersRobobosses will assign team projects
Management rolesManagement roles require team and project management capabilitiesManagement roles will focus on intuition, empathy, and interpersonal relationships
Interteam communicationTeam managers coordinate with team members via emails and meetingsRobobosses will coordinate with team members via chatbots
Performance managementTeam managers provide inputs on employee performance based on different assessment parametersRobobosses will leverage AI algorithms to evaluate employees on a wider range of parameters, such as timeliness, quality of deliverable, and creativity

Prediction #2: Smart machines will be our co-workers

Get ready to work alongside smart machines.

As AI algorithms become more robust and failsafe, they will take on more roles and responsibilities. By 2030, AI-enabled smart machines could be working as independent team members, their roles defined by underlying algorithms. There are two stages in which this process will occur.

Stage #1: Development of smart assistants 

As companies explore newer ways of implementing AI in their business, we expect to see smart machines taking the role of personal assistants to employees. The interactions between smart personal assistants and their human counterparts for tasks such as data analysis and communication management will provide sufficient data points to train smart machines on the nitty-gritty of employees' jobs.

Stage #2: Transition to co-workers

Once smart machines become proficient in their roles as assistants, they can use the learned skills to start functioning as co-workers. By the end of the decade, AI-based smart machines are expected to perform individual roles based on their expertise.

Impact of this prediction – 2020 vs. 2030

Smart machines at the beginning of the decade

Today’s teams perceive AI as an automation or smart analytics solution. For instance, sales managers use AI-enabled lead scoring to prioritize their lead communication efficiently. However, AI solutions lack autonomy; they are largely supervised and scrutinized from time to time to identify issues and areas of improvement. For example, after Amazon’s recruiting algorithm was found to be biased in screening candidates, the company retired the algorithm.

Smart machines by the end of the decade

Driven by improvements in algorithms, AI-based smart machines will become more efficient in their jobs. Smart machines will take up independent roles that involve data gathering, analysis, and repetitive physical labor. They are expected to work alongside human employees, tackling end-to-end job requirements with minimal human supervision. We also predict that each organization will have a “robot resources department” that will be responsible for managing smart machines and their roles at work, similar to the HR departments that currently supervise employees.

Value Smart machines in 2020 Smart machines in 2030
Reputation of smart machinesSmart machines are supervised extensively due to lack of trustSmart machines will prove themselves capable and work autonomously as coworkers
Resource managementCompanies have an HR department that manages employees and a tech department that administers AI toolsAlong with the HR department, companies will also have a robot resources department, which will supervise smart machines and designate their roles
Designation of smart machinesSmart machines are used as smart analysis or automation toolsSmart machines will work as coworkers, taking orders from robobosses and coordinating with human employees

How can business owners and HR managers prepare themselves for the future workplace?

Now that you’ve read our predictions and how they will impact your workforce 10 years down the line, you might be wondering, “why bother now?” 

We acknowledge that our predicted organization model will take at least 10 years to come into effect. But if you don’t start preparing today, you’ll be under enormous pressure to make these changes later. What’s more, your inaction could even lead to business failure.

In this section, we’ve listed three action items that you must start working on today to prepare for the AI revolution of the future.

1. Implement the “scrum master” approach in leadership

In the 2030 work scenario, the leadership approach will be that of a scrum master. The job of leadership teams will not be simply limited to assigning projects and tasks but will also involve overseeing the entire project delivery process and communicating closely with team members to identify and resolve project hurdles. Scrum masters will also be responsible for coaching and guiding teams through sprints to ensure that the speed of delivery doesn’t compromise the quality of the output. You can read this report to gain an in-depth understanding of the intricacies of the Scrum methodology and the role of a scrum master.

2. Invest in an AI toolkit for your business 

Since AI and smart machines are the future, businesses should start investing in the development or procurement of these systems now. We recommend investing in the following types of AI-based systems:

Robobosses: Work with HR leaders and team managers to implement AI-based systems that can evaluate employee skills and identify the best resources for projects. Based on workload trends, the system should be able to flag the need for hiring appropriate resources to ensure smooth operations.

Smart co-workers: Identify processes that can be automated using AI algorithms. Regularly update the algorithms of these identified processes to make them more efficient. When the accuracy level of these algorithms reaches near-human levels, employ them as independent workers.

3. When hiring, focus on skills rather than designation and experience

The workforce will primarily comprise employees with diverse skill sets, managed by robobosses, by the end of the decade. This means that skill-based traits such as creativity, efficiency, and knowledge will be more important than years of experience. Therefore, recruiters must focus more on these traits while hiring candidates. We recommend adding skill-based tests to assess candidate knowledge as well as case study tests to gauge the creativity of applicants.

GetApp features a catalog of AI solutions that can help you prepare for the future workplace. Check it out now!

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About the author

Toby Cox

Senior Content Writer
Hey there, I’m Toby. I’m a Senior Content Writer at GetApp. I bring you insights about software and technology trends for small businesses. Home base: Washington, DC; Things about me: I love bees, tacos, and yoga; Tech trends I think you should keep an eye on: Immersive reality technology and blockchain.
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