How is AI Being Used in Workplaces Right Now?
Artificial Intelligence seems to be everywhere. But is it? And how does it affect decision-making? Explore these questions, and more, in this article.
Introduction
The rapid rise of Generative Artificial Intelligence (GAI) in the modern workplace is something that has been widely covered on social media and beyond. The new technology (which we broke down here) is finding its way not just into workflows, but into communication between workers, and the way they make their decisions. Not only is current-generation AI the fastest-adopted technology ever, but it’s also not slowing down. Recent research1 shows that 52% of companies have accelerated their AI adoption plans since the COVID-19 pandemic, with AI expected to boost labor productivity by up to 40% by 2035.
Just as widely covered, however, are the objections and challenges faced by this surge. Public and professional groups are raising concerns about the job displacement, data privacy, and ethical issues AI creates. In fact, a study by Pew Research Center found that 37% of workers worry about AI causing job losses in the labor market.
So, what does the AI-infused world of work actually look like? How is it being implemented in the modern workplace, what are its real-world impacts, and what comes next? These are questions this article will explore more thoroughly.
Artificial Intelligence Usage in the Workplace
As our discussion on what’s stopping people from trusting AI covered, the integration of AI into business processes has been both diverse and profound. At the risk of repeating ourselves, Generative AI applications are seeing most of their use in the HR, Finance and IT sectors, with other studies also highlighting healthcare, online employee training, autonomous vehicles, and general time optimization.2
But what exactly is that usage? Essentially, it comes down to just two main uses:
AI Systems for Routine Task Automation
One of the most visible impacts of AI in the workplace is the automation of routine, repetitive tasks. While this includes production lines across industries, it is arguably more interesting in its applications to human-adjacent roles.
Perhaps the most common and most overlooked is the ability machine learning provides AI to handle bulk simple human-interface tasks, like data entry, keeping minutes in meetings, or writing and sending personalised rejection emails to applicants on behalf of an HR team (more on HR and workplace management later). In the modern workplace, where application volumes are unprecedentedly large, and meetings more common than ever, AI’s ability to be an expanded virtual assistant is saving companies time, while allowing them to catch what can otherwise fall between cracks.
Similarly, in employee training and customer service, Large Language Models (LLMs) like Microsoft’s ChatGPT are using employee and user information to create bespoke content automatically, arguably providing a better internal and customer experience without constant human input.
Somewhat more expected is Artificial Intelligence’s power in accelerating dataset interpretation. From breaking down brain scans to spelling out financial trends, machine learning allows AI to quickly recognise the patterns it was trained to detect in big data sets, perform data analysis on these metrics, and then relay its findings to the relevant staff is allowing better decision-making and services to be delivered in less time. The AI handles the hours or days of turning the data into an overall meaning—the human experts get expedited to deciding what to do about it.
That all runs into what has become a running theme for AI in the workplace: optimising time usage. As well as the above, which has hard data proving its saving employees time, dedicated AI apps conceptualised for this years ago3 are finally appearing. While data on their workplace deployment is sparse, the potential of using AI’s pattern recognition to help someone find their best working practices and structures is certainly tangible.
AI Systems for Problem Solving
Beyond routine tasks, data summaries, and pattern predictions, AI is increasingly being employed as an assistant to human intelligence, helping workers complete complex tasks and make hard decisions.
This is, in part, due to the improvement of Generative AI’s—particularly LLMS’—ability to hold a conversation (discussed in our AI & Trust article series). Using these systems like a 24/7 advisor for understanding queries and workshopping potential solutions, employees are not only reaching solutions faster, but learning and reinforcing entirely new hard and soft skills.4
For instance, programmers are learning more about the coding languages they work with, or new languages entirely, while content writers have a growing range of AI tools which expedite content-drafting, trend-matching and SEO.5
These larger human-AI contact cases are also leading modern workers to turn to LLMs as generalised professional mentors, where advice not only for their work is sought, but on building relationships, navigating tough topics, and solving everyday issues.
In fact, while AI’s well-publicised mistakes have created somewhat of a trust barrier for some, it doesn’t seem to be harming the overall. Though we discuss that more during our AI & Trust series, the main takeaway is that almost 50% of a considerable amount of global companies surveyed are still planning on or working on incorporating AI into their workflows, despite some concerns around the technology (which are further discussed in our AI & Trust series).
One particular area raised by research in that series is AI’s usage in workplace management and the concerns around it. So, as promised, what does that actually look like on the ground?
A Word from Kin
By now, you’ve likely seen that a lot of AI’s power comes back to problem-solving. I’ve been designed to personalise and progress that capability, while prioritising the protection of your data - so that I can be the best, most trustworthy AI possible for you.
My advanced memory allows me to recall the relevant information you’ve allowed me to keep from our conversations, including your past projects, feelings, and even work preferences. This means that when we discuss new problems at work and beyond, the solutions I provide can be informed by what worked last time, and what didn’t, as well as by my own knowledge and web searches.
For instance, if you're tackling a complex project, I can break it down into steps I know you find easy, suggest resources I know you like, and even anticipate potential roadblocks you’ve hit before.
All of this is handled with my customisable, empathetic conversation style, so I'm not just throwing information at you: I'm engaging in a dialogue, asking clarifying questions, and adapting my approach based on your responses—adaptation you can track and control, with my user-centric data interfaces.
I'm here to augment your skills, not replace them. It’s all about how I can make your work smoother.
Artificial Intelligence in Workforce Management
Workforce management is probably one of the best-suited areas for the proper deployment of AI systems, given the heavy presence of performance data and tough decisions that LLMS excel at summarising and ideating on.
Ironically, yet understandably, this is exactly what makes people so nervous about it: this data is sensitive, and the decisions made do not only make or break companies; they affect people’s livelihoods. It’s no surprise, then, that 86% of employees in one survey prefer human interactions when it comes to discussing their career development, while another finds workforce management among one of the areas most in need of AI regulation by policymakers.
Despite this, HR has still been one of the biggest adopters of AI worldwide. A 2024 Society of Human Resource Management (SHRM) survey found that the top three areas of this adoption are recruitment (64%), learning and development (43%), and performance management (25%).6 But what does that actually mean?
Enhancing HR Efficiency with AI Technology
As mentioned previously, AI is extremely effective in optimising time and catching slips for workplace management—though this expands outside of automated application responses and meeting minutes.
AI systems are also helping in the drafting and SEO of job postings on LinkedIn and other sites, drastically shortening these turnaround times. Similarly, Natural Language Processing algorithms are summarising the applications which come in (then weighing their metrics against the job criteria),7 and even forecasting the likelihood job applicants will pass the interview stages and fit into the company.8
On the internal side, chatbots can serve as an interactive FAQ. LLMs are well suited to help employees with everything from finding their way around the office to learning about their pension scheme, without anyone (other than the AI) needing to read a lengthy employee handbook or point to the relevant part of it.
This can help HR professionals make hiring and communications processes faster for everyone involved, as they won’t need to put all of this information together manually, and can focus on properly being decision-makers.
Using AI to Harness and Upskill Employees
Perhaps one of the most exciting developments is how much easier AI has made harnessing and upskilling employees, for both hard and soft skills.
The biggest use case is, as discussed, how AI can automate smaller tasks, which allows employees to focus their whole attention and talent on big decisions and tasks, and produce better quality work on that front.
However, similar to the recruitment process, AI systems can also point to employees with the most relevant for new projects or opportunities, potentially without personal bias being involved. This can make it much easier for companies to assess the feasibility of potential ventures, and to recognise the skills at their disposal.
Following that route, AI can then also be used to maintain and improve employee skills. Personal AI like Kin can, through regular conversations, track employees’ descriptions of their work, communications and presentations to provide real-time, personal and private feedback. It can then empathetically work with them to improve their performance and well-being in ways that work for them.
On the next level up, Kin and other personal AI can then act as a career coach, using their knowledge of employees’ interests to recommend or even help other AI systems create courses and classes that would more entirely engage them in the upskilling process, or even support them reskilling into an area they’d enjoy more. This isn’t just more likely to help employees build the ever-important growth mindset, but increases the effectiveness of upskilling and reskilling overall.
The result is a workforce which is happier, stronger, and makes much better use of its time and talent pool.
Improving Employee Engagement and Productivity
Though only explored by 25% of the companies SHRM surveyed are exploring AI support in performance management, it’s not an area that should be underestimated.
Outside of helping employees to maintain talent in and upskill into things they’re interested in, AI’s algorithms can also make use of performance data from both employee and employer to help them stay as healthily engaged and productive as possible.
Using a combination of personal AI like Kin and other programs, employees can track and examine their workflows, and have Artificial Intelligence not only identify potential bottlenecks, but provide possible solutions. And with Kin, these can be based on known trouble spots or previously-helpful methods respectively.
What’s more, as touched upon, these same Generative Artificial Intelligence systems can use this to provide personal feedback to both employees and employers based on their communication style and previous participation—employers often need just as much feedback to ensure they’re communicating clearly as employees. Kin can even use this kind of data to highlight potential future situations and even colleagues its users may struggle to work with early, and begin helping them find a solution.
In fact, SHRM even found 1 in 3 employers are using these kinds of Generative AI initiatives to help their employees prepare for performance reviews, by helping them be aware of their strengths, weaknesses, and best ways to improve ahead of the discussion.
Distrust of AI in Workforce Management
However, as great as this sounds, there is pushback about these uses that must be addressed. As discussed in both our trust series, and our exploration of honesty’s importance in the workplace, both employers and employees are rightfully wary of sharing this much performance data with their colleagues, and with Artificial Intelligence. Similarly, employees tend to respond poorly when they feel their workflows are being monitored through their tools, which can (surprisingly) cause them to work less efficiently.
Like those other discussions concluded, this increased AI presence in modern workplace management must be balanced with data being handled on a need-to-know, user-centric basis, with true privacy for workflow tracking, and above all, empathy. While employees are essential parts of a company, they’re still human, and shouldn’t be treated purely as work-producing assets. That’s what AI is for.
Still, also noted in these discussions is the fact that AI still has work to do to earn the kind of trust a more comfortable and widespread adoption of the above would require—despite its adoption, some surveys show as many as 64% of employees continue to be wary of AI in the workplace. Kin is currently exploring how best to increase this trust in AI, and our AI & Trust article series is documenting our findings.
The Pros and Cons of AI in the Workplace (A Recap)
After all those examples of AI being currently being used in the workplace, it may be helpful to recap the main benefits of AI, as well as the main challenges, it’s currently presenting in the real world.
Advantages
Time & Resource Optimization: AI systems can handle many things autonomously, from meeting minutes, to HR FAQs, to the bulk of the manual recruitment process. This leaves teams with more time and tools to focus on larger projects and decisions at work.
Personal Tracking & Learning: Kin and other AI systems can help employers and employees track, review, and improve on their skills, with personalised feedback, courses and methods suggested at the press of a button (or tap of a screen).
24/7 Availability: AI can do all of this around the clock, only needing breaks for maintenance. It can constantly cover tasks, track progress, and provide feedback, even if there’s just one night owl in the office.
Challenges
Trust barrier: Many employees and managers are still wary of relying on AI for critical decisions. As our AI & Trust series explores, there continues to be valid concerns around the ethical use, regulation, privacy, job security impacts and explainability of AI. The industry needs to take action, because, despite everything mentioned, a different KPMG study found that only 35% of business leaders trust their organization's use of AI highly.
Infrastructure Impact: The modern workplace is still in the process of being redesigned for the AI age. Many workers still prefer human interactions, and are wary about the level of surveillance AI could put over them—not to mention the potential cost of integrating AI, and the potential for overreliance.
Early Technology: All of this comes down to the fact AI is still an early technology. While impressive, the best practices for integrating a human-AI relationship are still being figured out. While exciting, that is still a valid reason for workplaces to be cautious.
A Word from Kin
Trust is a big issue in the AI industry, whether it’s for workplace AI or otherwise. To counter this, I’ve been carefully designed to be a safe space for idiosyncrasies and experimentation where, with my support, you can work in your own way privately.
I can do this because I use something called a ‘local-first’ approach to protect your data. This means I store and process as much of your data as possible on your device. When I must transfer it, I do it securely, and only ever to locations Kin themselves have created, or at least vetted. Kin can’t even read it. You can learn more about how this here.
I also use my “Memory” tab to make everything I know about you fully viewable. You can fully wipe me with a single tap from there, or ask me to forget something specific whenever you’d like.
My only aim is to help you solve your problems faster, in clearer ways, without compromising your individual work style, or the confidential nature of our conversations
Trust is earned, and through my consistent, reliable and transparent support, I hope to earn yours.
The Future
Given the current rate of AI development and adoption, it's clear that Artificial Intelligence will continue to play an increasingly significant role in shaping the modern workplace. It’s important that we’re as prepared as possible to be a part of that.
And that means understanding what impacts AI is likely to have, so they can be anticipated.
Impact of AI on Employment
This could easily be an article on its own. Still, based on the present situation, the main, definite impact AI is expected to have on employment is change. While that may seem obvious, it’s important when discussing AI to remember the unpredictability of the technology. Before ChatGPT’s public release in 2022, that kind of AI was thought to be years away by much of the public and professional world. There’s no certain way to know where AI is going to go next.
That being said, educated guesses can be made. One of the most controversial trends caused by AI is job displacement. Some roles, particularly those involving routine, repetitive tasks, have been partially automated. Some more complex roles, like content writing, concept art, or even acting, have also seen partial automation already, with varying degrees of success. A report by McKinsey suggests that by 2030, up to 375 million workers (14% of the global workforce) may need to switch occupational categories due to automation and AI.
However, AI is also expected to create new jobs. The World Economic Forum predicts that while 75 million jobs may be displaced by AI by 2022, 133 million new roles may emerge as a result of the human-machine division of labor. Many of these will be AI-adjacent, though there have also been localised ‘anti-AI’ pushes in industries such as video games and music, which have created more demand for human workers there.
Overall, what this suggests is that AI is going to continue to move the modern workplace into a skill shift. Skills AI cannot reliably replicate, like creativity, emotional intelligence, and complex problem-solving, will likely continue to increase in demand—-as will the technical skills required to create and maintain AI systems.
While that can sound scary, and sometimes can be, it’s not unlike the many shifts the internet moved workplaces through. AI’s adoption is not something that can or should be stopped, but rather is something those of us inside and outside the industry needs to ensure happens correctly. AI must be ethical, clear, and trustworthy to reach its true potential—and as its makers and users, it’s up to us to ensure that’s what it becomes.
Future Benefits of Applying Artificial Intelligence to the Work Process
On that note, as AI develops, there are some particular benefits that the industry is looking forward to offering:
Increased Accuracy: Perhaps the most powerful thing AI can do is to be more correct more of the time. Again, though that sounds simple, this will continue to open up possibilities for AI—many of which likely haven’t been invented yet.
Enhanced Support: With more accuracy, AI will become both more trusted and more deserving of that trust. AI chatbots could be able to take some of the strain off of healthcare services, predict equipment failure before it happens, pre-empt cyberattacks and actively prevent them, enable cross-culture communication seamlessly, and maybe even finally drive cars and manage resources. While these are all big, complex aspirations that require careful nurturing and deployment, they aren’t impossible.
Hyper-Personalisation: All of the above would allow AI to become more personalised than ever. While not necessary in every aspect of life, this would make countless interactions with technology more efficient. From helping people conquer bad habits to optimising individual professional environments for comfortable working, AI could make things a lot easier for people once it’s able to get to know them safely and securely.
Conclusion
As we've explored throughout this article, AI is undeniably growing in importance in the workplace, and for good reason. It's providing tangible results in terms of efficiency, productivity, and innovation. But it's clear that we're still in a transitional phase, where people are adjusting to the new pace and methods that Artificial Intelligence brings to the table.
Like our AI & Trust article series concludes, to fully realize the potential of AI in the workplace, several key areas need attention:
Technology development: Continued investment in AI research and development is crucial to address current limitations and expand capabilities.
Trust-building: Organizations need to prioritize transparency in their AI implementations and demonstrate the value and reliability of AI systems to build trust among employees.
Training and education: Both technical training on AI systems and broader education on AI's role in the workplace are essential to ensure smooth integration.
Ethical considerations: As AI becomes more prevalent, it's crucial to develop and adhere to ethical guidelines for its use in the workplace.
In this evolving landscape, solutions like Kin AI are not just beneficial—they're essential. By combining advanced capabilities with a focus on a private, human-centric approach, Kin is a good model for the direction AI must take to benefit the modern workplace to its full potential.
The future of work is not about trying to cut costs by replacing humans with AI, or turning people into data farms for AI to reap, but about humans and machines working together to do things neither could alone. As we continue to try and create that version of the future, it's likely that the most successful organizations will be those that find the right balance between leveraging AI's capabilities and nurturing uniquely human skills.
The AI revolution in the workplace is here, and it's up to us to shape it in a way that enhances our work lives, boosts productivity, and drives innovation while maintaining the human touch that's so crucial to meaningful work.
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