How artificial intelligence changes the future of work
In recent months, since the global introduction of ChatGPT, the internet has been loudly vocal about AI. It is the new shiny thing. As with anything that moons over the hype cycle rapidly, the best thing we can do is to relax, calm down, and take a big step back to evaluate the situation appropriately. Let's see how artificial intelligence can really change how we will work in the future.
This post originally appeared on the Remote-First Institute Blog.
In recent months, since the global introduction of ChatGPT, the internet has been loudly vocal about AI. It is the new shiny thing. As with anything that moons over the hype cycle rapidly, the best thing we can do is to relax, calm down, and take a big step back to evaluate the situation appropriately. Let's see how artificial intelligence can really change how we will work in the future.
To understand what AI can bring to the world regarding the future of work, we need to understand what AI is in the first place. Now, I want to avoid going into technical details, but there are two fundamental ways AI contributes to today's world.
Fundamentally, AI can do two things now, which will be refined in the upcoming years.
First, it can take a massive amount of data, analyze it, and throw it back to us based on the prompts we give. It can be text (copywriting with AI), it can be visuals (image creation with AI), it can be music (audio creation with AI), or even a combination of all in the video.
Second, AI shines where there is automation. Human prompts can configure the AI to do tasks, utilizing AI analysis capabilities. Now that part was here way before ChatGPT made it to the front pages - just think about the stock market and the bots that make investment decisions based on algorithms. Expect that these automation practices will extend further in the future.
The bottom line is that AI helps with analysis and automation.
We, future of work experts, when it comes to meetings, we say a lot that "this meeting could have been an email" - to avoid burnout because of meeting fatigue.
In the AI-influenced work, I'm sure we will say a lot that "this could have been an AI task automated" - but will this mean that most of our jobs will be done by bots?
I don't think so. But there will be five areas where AI will definitely shape and fundamentally change how we work.
Solving problems over analyzing problems.
In general, those jobs whose sole purpose is to analyze problems will change fundamentally. Most of the analysis becomes an AI workflow.
Data miners, data scientists, or literally anyone who works with huge chunks of data right now will see an increasing influx from AI in their tasks.
Of course, we will still need the human element, those who write prompts to the AI, as the AI doesn't know what to analyze.
Parallel to that, the fundamental skill of solving problems will be incrementally valuable in the future of the workforce. Problem-solving, in general, becomes essential as human prompts need to understand the big picture to control AI workflows effectively.
Ladies and gentlemen, creativity is back on the stage.
With the introduction of an army of technology and tools to workflows in the early 21st century, the creative workforce pretty much ditched creativity from work.
Everything became a tech-created template. Everything became a SaaS. And everything got measured, tracked, and monitored. Everything ended up as a hack. It was especially true in the creative industry, where creative agencies literally became tech companies.
Now that we can create written text, audiovisual content, and full-blown digital properties with a click of a button supported by AI, we will see an even more extensive amount of template-based production. Everything will start to look, read, and feel the same way.
It inevitably jumpstarts creativity back in the driving seat. We will still use AI capabilities but spend more time on actual creative strategy. Of course, it will affect first the creative industry, but it will go beyond that.
Anyone who will work with AI, which will be most of us, will need to spend more on making processes and production efficient, unique, and distinctive. Therefore, creativity will be an essential skill on top of problem-solving for the future workforce.
Say goodbye to HR. Long live people analytics!
What is HR now? It manages people as resources: paperwork, in-out flux, and internal development, whether skills or culture.
Most of this work will be done by AI, and I believe this will be one of the first areas where we will see massive adoption.
The activities of employees produce a great deal of data. Collecting these insights is part of people analytics anyway. But the insights can serve as a backbone for decisions only now. It will change with AI.
Why? Because AI doesn't care who you are - it cares only about what you do and how you do it. As a result, most of the bias and inequality we see daily in the workplace will go out of the window. The AI doesn't care what your gender, race, nationality, location, or religion is. It cares about your performance only.
I'm 100% sure we will see AI recommendations on performance within years. AI will play a fundamental role in compensation, bonuses, employee reviews, and employee retention. Not to mention the endless paperwork which will be done in an automated fashion by bots - but that happens anyway with most of the bureaucracy (so I wouldn't sign up for a law degree in 2023 if I were you).
Of course, the human element will stay, but we will call it something other than HR. It has to be a human who makes the decisions ultimately - the AI can only recommend. Also, people want to talk to people still - we are far away from human-bot relationships.
I would bet on the rise of people analytics jobs mixed with people-first roles, such as work experience designers, people experience specialists and more.
Async recruitment/hiring is here and won't go away.
Asynchronous hiring and recruitment are already getting traction, and they will be even more dominant in the future. It is easy to understand why.
Let's say you have a role, and you have 1,000 applicants. All of them submit their CVs or profiles to your ATS. Do you still go through all of them manually as you would with a dating app, swiping left and right? I don't think so.
With the language processing and automation capabilities of AI, the first 1-3 phases of recruitment will be fully async and automated. Recruiters will step into the picture on two occasions: configuring the AI filtering based on the job role requirements and doing the screening interview.
Anyone who participated in recruitment as a recruiter can tell: that is pretty much the most time-consuming part of the job. The AI will present only those candidates for a screening who are fit for the role, at least based on their skills. The rest, cultural fit, for example, still be part of the recruitment's human element.
I am sure that recruitment, in general, will experience a tremendous shift in workflows just because AI will do most of the work for them.
An era of more horizontal and transparent organizations has begun.
After all the direct impact we went through, there will be a massive indirect hit on all organizations. They will become more horizontal and more transparent.
Since monitoring and analysis will be part of AI workflows, and the human element will be much more needed, the middle management of companies will face a fundamental shift in their roles.
People who spent most of their jobs creating reports and facilitating project management with their teams through delegation and standups will face enormous challenges. It will be hard to justify why we need those activities if we have a full-blown AI supporting our internal workflows.
People who spend most of their jobs analyzing work will have the same issues. AI will support most decisions as well as facilitate them. And the AI will be able to make those decisions better - since no human can compete with the analyzation capabilities of a computer.
So where is the way out? How can we ensure that our jobs will still be needed, even with the addition of AI in the upcoming years?
It is a simple answer. It is the answer to all the challenges above. It will all come down to human creativity, problem-solving, empathy, connections, and relationships.
The future of the workforce becomes more people-first. Yes, you've heard it right. We need to take a more people-first approach when we add a non-human (AI) element to our work.
We need to be more supportive and spend more energy on creating work environments that facilitate empathy, understanding, and the value of people. We need to invest less in tactics, analysis, and decisions and more in our teams' facilitation, support, mentorship, and coaching.
People support people. We mentor each other. We help each other. We take care of each other.
The most crucial indirect effect of AI will be in learning and development. Within years, organizations will spend more resources on internal L&D programs. Not just to upskill their AI prompt skills to work better with AI but also to level up their skills in mentorship, support, and facilitation.
Regarding the current stage of remote work, flexibility won't be just part of where and when we work. But with AI's mass adoption, it will also be about how we work with each other.
2023 and 2024 will be the best years to sign up for learning and development programs to help you level up your current team.
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Task Automation for Remote Teams
With remote work becoming the norm, efficient collaboration and streamlined workflows are crucial. Task automation can save time, reduce human error, and boost productivity for remote teams. This guide aims to help you implement task automation effectively by exploring its benefits, tools, and best practices.
With remote work becoming the norm, efficient collaboration and streamlined workflows are crucial. Task automation can save time, reduce human error, and boost productivity for remote teams. This guide aims to help you implement task automation effectively by exploring its benefits, tools, and best practices.
We will cover various task automation tools, strategies for identifying repetitive tasks, and best practices for implementing automation workflows. By the end of this guide, you'll be equipped to leverage task automation to enhance your remote team's performance and efficiency.
Why automate?
Time savings: Automating repetitive tasks frees up valuable time for team members to focus on more strategic, creative, and meaningful work.
Reduced errors: By minimizing manual input, automation reduces the risk of human errors, ensuring more accurate and reliable results.
Improved productivity: Automation streamlines processes, enabling remote teams to work more efficiently and effectively.
Enhanced collaboration: Automated workflows can enhance communication and collaboration by providing real-time updates and keeping everyone on the same page.
How to plan your automation journey?
After exploring the benefits and tools of AI-driven automation, it's crucial to understand the strategies and best practices for implementing AI in your remote operations management.
Assess your current processes: Begin by conducting a thorough analysis of your existing operations to identify areas where AI can make the most significant impact. Look for repetitive tasks, manual processes, and bottlenecks that can be improved or automated.
Set clear goals and KPIs: Establish specific, measurable, and achievable goals for AI implementation, as well as key performance indicators (KPIs) to track your progress. This will help you prioritize areas for AI integration and measure the success of your initiatives.
Choose the right AI tools: Research and select the AI tools that best fit your organization's needs and goals. Consider factors such as ease of integration, scalability, and user-friendliness when making your decision.
Develop a rollout plan: Create a detailed plan for implementing AI in your remote operations, including timelines, responsibilities, and any necessary training or resources. Consider a phased approach, starting with a pilot program to test and refine your AI integration before scaling up.
Train your team: Ensure your remote team is equipped with the knowledge and skills necessary to work effectively with AI tools. Provide training, resources, and ongoing support to help them adapt to new processes and technologies.
Monitor and optimize: Continuously evaluate the performance of your AI tools and their impact on your remote operations. Use data and feedback to identify areas for improvement, fine-tune your AI implementations, and optimize your processes for maximum efficiency and effectiveness.
By following these strategies, you can successfully integrate AI into your remote operations management, driving productivity, efficiency, and innovation across your organization.
Best Practices for AI in Remote Operations Management
To maximize the benefits of AI in your remote operations, consider these best practices when implementing and managing AI-driven automation:
Foster a culture of innovation: Encourage your team to be open to new technologies and approaches. Share the benefits and potential of AI with your team, and promote a mindset of continuous learning and improvement.
Ensure data quality and security: AI tools rely on data to function effectively, so maintaining high-quality, accurate, and secure data is essential. Implement data management and security policies to protect sensitive information and ensure the reliability of your AI tools.
Prioritize user experience: User-friendly AI tools are more likely to be adopted by your team and yield positive results. Choose tools with intuitive interfaces, and consider your team's needs and preferences when selecting AI solutions.
Communicate clearly and transparently: Keep your team informed about AI initiatives, their goals, and the expected outcomes. Be transparent about how AI will impact their roles and responsibilities, and address any concerns or questions they may have.
Measure and track results: Regularly evaluate the performance of your AI tools and their impact on your remote operations. Use data-driven insights to identify areas for improvement, and continuously refine your AI implementations to optimize outcomes.
Learn from your experiences: As you implement AI in your remote operations, take note of what works well and what doesn't. Use these insights to inform future AI initiatives and enhance your overall approach to remote operations management.
By following these best practices, you can effectively harness the power of AI to streamline and enhance your remote operations, fostering a more efficient and productive work environment for your distributed team.
Embracing AI in remote operations management has the potential to revolutionize the way companies work and interact with their remote teams. By automating repetitive tasks, utilizing RPA tools, and implementing effective strategies and best practices, organizations can not only save time and resources but also enhance productivity and efficiency.
As remote work continues to grow in popularity, leveraging AI technologies will become even more critical in maintaining a competitive edge. Companies that proactively invest in AI-driven solutions for their remote operations will be better positioned to adapt to the ever-changing landscape of the future of work.