Generative AI and the future of HR (2023)

(7 pages)

Generative artificial intelligence: it's available. It promises to change the way we work. in this episodeMcKinsey talk about talentIn this podcast, talent hosts Bryan Hancock and Bill Schchaninger discuss the promises and perils of using genetic artificial intelligence in HR, from recruiting to performance management to chatbot support, with McKinsey Technology Council President Lareina Yee and Global Editorial Director Lucia Rahilly. An edited version of their discussion is included below.

What's different: So devastating

Lucia Lahiri:In recent months, there has been a lot of talk about generative artificial intelligence and tools like ChatGPT. Many seem to vacillate between marveling at the potential of these tools and fearing their inherent risks. Lareina, what makes generative artificial intelligence different and what lies behind its disruptive potential?

Larena Yeh:Several things stand out about generative artificial intelligence. In November 2022, OpenAI released ChatGPT 3.5, and within 5 days the number of users exceeded one million. So the adoption rate is unlike anything we've seen.

The most profound thing for me at that moment was that anyone, of any age, any level of education, any country, could go into GPT, search a question or two, and find something useful or interesting, like a poem or an article. There is an experience for everyone. Since then, we've seen great advances in technology, and it's only been a few months.

Another super cool thing is that you don't have to be a computer scientist to take advantage of this technology, it can be used for all kinds of jobs. OpenAI research estimates that 80 percent of workplaces could incorporate generative techniques and artificial intelligence capabilities into the activities that take place at work today. This has profound implications for talent and work, and it's not in the same way we talked about before.

Somehow, the genie is out of the bottle. Trying to get him back is probably not the best strategy. Lean forward and learn how to use it effectively and safely.

Lucia Lahiri:The immediacy of the use case feels so new and so fast. Please explain what generative artificial intelligence is, which is why we are working on a common definition of the term.

Larena Yeh:Generative artificial intelligence is a technique that suggests the next best answer. Many people use ChatGPT to collect information, to compile an answer to something by collecting large amounts of public data. But there are also amazing pictures. Maybe you want songs, audio, video or code. Code is a great example. The range of things that generative artificial intelligence can do in the world is amazing, and it's just getting started.

Brian Hancock:I asked ChatGPT about me and he correctly told me that I work hard on talent. However, he falsely reported that I went to Cornell because he felt Cornell was the most appropriate answer based on my background, rather than the University of Virginia I attended. I think it's very interesting that you don't necessarily get the right thing, but the logical thing.


Larena Yeh:In a way, this mimics the way we think. I'm not saying I think like a human being, but in many ways we use shortcuts and clues to make assumptions. That's why people say, "Man, that's really smart." But, Brian, that's not 100% true. There's a good term for this: "hallucinations."

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What the AI ​​generation means for recruiters. . .

Lucia Lahiri:We'll talk more about some of the risks, but let's look at what these generative AI capabilities mean for talent in particular. Do you expect generative artificial intelligence to reshape or change?Recruitment processin any meaningful way?

Brian Hancock:I think it will reshape employment in two significant ways. The first is to help managers write better job applications. Generative techniques can actually demonstrate the skills you need to be successful at work. This does not mean that managers do not need to review the final product. They have to be vigilant to make sure that the job requirements are good. But the AI ​​gene can significantly improve speed and quality.

Another application in recruitment is candidate personalization. Now, if you're an organization with tens of thousands of applicants, you may or may not have a super personalized way to reach applicants. With generative artificial intelligence, you can further adjust candidates, jobs and possibly other jobs on offer if the candidate does not fit. All these things are easier and faster with generative artificial intelligence.

Bill Schninger:The best generations of AI applications are largeskills libraryYou are trying to fill a fairly well-known position. We need a more efficient way to navigate through all the passed configuration files. What makes me a bit concerned is any time it's a new job, a new role, or even, according to US law, a job change of more than 25% or 33%. In these cases, you should go back and reconfirm your judgment about the people in or out of the pool.

The challenge with validation is that you need performance metrics to go back and say, "What's the difference?" In some cases, this means figuring out how to get them out of the data lake without violating someone else's proprietary performance data standard. If you say, "Well, we're only going to use our data as an employer," then you're just basing the standard on the people you've hired. To check, you have to look at the people you didn't hire.

This does not mean that technology cannot be used. It just means that there will likely be more entry-level jobs to apply for new positions and a wide range of opportunities for a large skill set.

Lucia Lahiri:We often talk about over-indexing of qualifications and under-indexing of skills in the recruitment process. Can generative artificial intelligence work?accelerate changesFrom credentials like a college degree to the skills a candidate can actually bring to the workplace?

Larena Yeh:I'm optimistic. One thing this technology does very well is tagging: the ability to tag words for unstructured data. There are many companies that are thinking about applying it to e-commerce and different types of retail experiences. But you can also apply it to talent acquisition or skill hunting. Now you don't have to look for certificates or degrees. You can search keywords based on skills and abilities.

(Video) HR and ChatGPT: is this the future of HR?

Look at social media, how do people talk about certain skills? You may find that there are better words to relate to someone with those abilities. Think of a world where you want to find candidates who have experience learning on the job, but don't have a PhD or college degree. I'm optimistic, this can open more doors for people like this.

Bill Schninger:This is an interesting trade-off in the business world, which favors proprietary datasets and profile groupings. The real power might be, "How much can you get in the public domain before you start attacking the paywall?"

A long time ago, when LinkedIn was acquired, the API was limited to job titles, not necessarily all the specifications below. There is power in these groups, especially in job profiles, because then tasks and skills are visible. I think there's going to be a race here to figure out how we can put this together to form an ontological cloud, so to speak, of "these 17 things that describe a capability."Skills, not credentials.

...what this means for professional development

Brian Hancock:You can also think of this as helping with skills-based transitions, not only from an employer's perspective, but also from a candidate's or employee's perspective. In today's world, if you may have some skills but are not entirely clear about your career options, you will be very dependent on a manager or someone who takes an interest in you and helps you navigate your "non-traditional" path.

But in the world of generative artificial intelligence, you can talk to a chatbot that's really smart and say, "Hey, here are my skills and experience. What jobs are available for me?" You can respond and say, "Well, most people with your skills will do these things, but some will do A, B, C" where "C" is coding. Then you can say, "Tell me what those coding jobs are," and you can show a coder job description that's not only applicable to IT people, but can also be translated into text you can understand. Then you can say, "Okay, this is great. I'm interested. What learning experiences do I need?" Generative AI can tell you what those learning experiences are.

So for people with innate but unknown abilities, generative AI could shed light on different career paths and begin to help people understand how to get there.

Larena Yeh:Imagine that ten years after my graduation I feel a bit stuck. What if I had an AI career assistant to help me think about things like, "What kind of job should I be looking for? What types of jobs are available at my company? How can I see them?" and "What courses should I take??" instead of waiting for someone to retrain me, that sounds awful. How can I proactively build my skill set and understand the scope of work that matches my abilities, ten years after my degree? That's very nice.

Bill Schninger:Depending on the regulatory environment you're in, you can't make selection decisions without human input. This is especially true for the European Union. This is a great way to increase human performance without reducing decision-making. Regarding personnel, it should ensure greater transparency; in fact, it shows how close you are to many things. I like the employee experience part. I'm looking forward to the selection part just because we're still not sure what's in the data lake and how good humans are at giving AI clues.

Larena Yeh:rectify. I'm happy to give you some options, but this is not a response or recommendation mechanism. Your judgment is important.

Brian Hancock:Another thing we've seen is that ChatGPT, and generative AI in general, is particularly good at onboarding new hires faster.

Erik Brynjolfsson of Stanford University and others at MIT recently conducted an interesting study looking at call center workers. They found that generative AI capabilities were not as useful for more experienced agents. This is very useful for newcomers as they can gain institutional knowledge faster. It's within reach. I can ask questions and get answers. As a result, new hires are significantly more productive. Generative AI can really get you to 80-90% full skill.

Larena Yeh:I like that, Brian, and I'm an optimist.

Generative AI and the future of HR (1)

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What's new in performance reviews

Brian Hancock:One of my personal favorite uses of generative AI for humans is actually performance evaluation. Hear me out: I don't want generative AI to actually generate someone's performance review. This requires informed human beings, human judgment and empathy.

But let me use this example to illustrate what I do as a McKinsey reviewer: I get written feedback from 15-20 people. They write it in the number system. I got a long feedback. I look at feedback results from the bottom up, including written reviews and ratings based on specific numbers. I observed how often people actually implement commitments. I review compliance-related measures. Did they deliver the items on time? all kinds of things. For me as a reviewer, getting the first draft was a very daunting process. I'm proud of the time and consideration that went into it.

But what if you could press a button and get an eraser? What if I already have an outline of every interview with the 15 people who know the person I'm evaluating best? It's not a substitute for everything, but the initial synthesis will help me understand more quickly the development and growth of the person I really need to explore.

I'm excited about this use case because it saves a lot of work. At first, many people will think, "I never want to generate an AI anywhere near a performance review." But if we think about it as something that increases productivity or helps us be better, that would be exciting.

Larena Yeh:Now let's talk about the employee you are evaluating. The employee gets the feedback, Bryan probably writes it down clearly, conveys it with empathy, so that the person feels, "Okay, I have some strengths, I have some development needs."

But if I, as an employee, can ask, "Who are five successful people who have my strengths and weaknesses, and what did they do next? How can I envision my career growing? How can I continue to work hard?" I also have an assistant who helps me plan my career development. That way, when we moved a year later, I really progressed and increased my ambitions.

What if Bill was someone you should emulate? Without Bryan introducing me to Bill, generative AI helped me realize that I had what it took to be Bill Schanyer. I can be inspired by it. I think there are many things that can improve what we have been trying to do for years.

Bill Schninger:We are talking about re-engaging managers in performance management. Every time you talk to someone about something good or bad, write it down. So, it's more about adding up and synthesizing towards the end of the year, which shouldn't surprise anyone. But it requires regular access. While I like what you're describing, it's not technology, it's technology. they are people working on generic data collection and a generic approach to achieve it.

Brian Hancock:Your opinion is good. Then, as an evaluator, I apply my human judgment.

Bill Schninger:Canonical data is fine. When we receive our sponsorship and training data at McKinsey, we see how we compare to other partners in a given region. But how do you know what's "good" if you don't have a reference point? Once you have the canonical data, you can start to get some guidance. I like it all and it's all backed up by loads of data.

(Video) AI in HR - What is the Impact of Artificial Intelligence or AI on HR?

If it leads to a more robust and healthy view of actual performance, havingDifficult acting dialogue..We have toPut managers back on performance managementBut can we make it easier for managers so they can spend their time managing instead of sloppily making a timeline or knitting 15 data points?

Bias and other risks

Lucia Lahiri:Let's talk a little more about risk. Generative AI learns from historical data whose historical patterns reflect historical biases. What is the risk that we inadvertently spread these genetic biases by relying on AI-powered generative tools?

Larena Yeh:Today, of course, generative artificial intelligence amplifies the bias.

Let's say I'm hiring and I'm describing several different qualifications. I was looking for a talent center and decided to look for basketball captains or conversely I said lacrosse captains would be preferred. They are team sports with captains and leaders, so it kind of makes sense.

But if you look at the demographics, the people who play basketball in the cities are very different from the people who play lacrosse. So by emphasizing lacrosse, you'll generally get more young white male leaders, while if you choose basketball, you might find more African-Americans or Latinos. What about softball, where do we see women? Conversely, what if we select the entire set of sports? However, simply selecting sports as a filter can reinforce the bias in the question. I think the power of this question lies in us humans.

Brian Hancock:Of course, there are also issues of intellectual property.

But I also think we all run the risk of becoming less interesting. If you're in a creative field and you're taking advantage of generative artificial intelligence to increase your output from 6 articles a week to 12, you'll spend less time on each article. You may have to do this in order to post it on time, but it also means you won't spend as much time showering, running or driving.thoughtAbout the article. Your productivity will increase, but you may not have as much time for creative thinking. We know that the most creative ideas come from free time, when you are doing other things and letting your mind wander.

This not-so-fun risk is an important one, and we probably haven't fully considered it yet.

Larena Yeh:exactly There are many risks. Let's also think about the managers who implement this technology. People often have a workflow where they think about technology and business ROI, only to end up asking, "Are there any risks we need to worry about?" I recommend thinking about risk in your workflow design beforehand.

The second thing is the real opportunity for what we usually call "change management". If you're not thinking carefully about how technology is changing work, workflow, or collaboration models, you're not necessarily spending extra time on more value-added things. You need to consider how this affects the work day and the rest of the work week.

Bill Schninger:In many cases, we prefer to blame the technology rather than highlight the poor handling of problems that occurred before it was implemented. Getting a better, lighter, faster, and wider tool doesn't relieve you of the burden.

Larena Yeh:More importantly, the three of us spent this time thinking about all the positive intentions and how we can put them to good use. But there may be people who think about this technology and wonder, "How can I use it to cause harm?" Traditionally, this is why government regulations, policies and international standards have played a fundamental role in our society. I do not think that the private sector can be completely left to self-regulation.

prepare for the inevitable

Lucia Lahiri:People's biggest fear is that these tools will lose their jobs or, perhaps worse, become their boss. What do you think people can do now to prepare for the changes that generative artificial intelligence will bring?

Bill Schninger:I will try to make it easier for them to learn and use. This is better than still trying to resist him. I don't think we should be held hostage by these fears.

Lucia Lahiri:Assuming HR and talent processes become increasingly automated, how can leaders ensure that generative AI doesn't get in the way of what Bryan calls "people in the loop"?

Larena Yeh:Leaders can make a big difference in two ways. One is that within the scope of his functions, he carries out modernization and rapid development of his own talented abilities. Second, if 80% of your workforce is being transferred, this will play a big role in how the transfer will occur and how the transfer will affect the company's employees. I think the leaders have a lot to say at the negotiating table.

(Video) Will AI Replace HR Professionals?

Brian Hancock:This is a great opportunity for HR to increase the chances of a large number of employees getting the opportunity. this is an opportunity to winManagers achieve performance levels more consistentlyHuman resource managers have always wanted to achieve this rather than work in administrative positions. I hope HR sees this as an opportunity to routinize work they don't have to do and get rid of it. And then for the work they have to do, they can use this technology to find a way to get better answers faster.


How does generative AI affect HR? ›

The Impact of Generative AI on HR

Recruitment and Selection: Generative AI can automate and enhance the recruitment process. It can draft job descriptions, screen resumes, and conduct preliminary interviews. Imagine the efficiency and fairness it can bring to the selection process!

What is generative AI in HR? ›

In HR Tech, generative AI chatbots can streamline recruitment, assist in performance management and improve employee engagement by reducing response times and enabling data-driven decision-making.

Is AI the future of HR? ›

That aligns with other research that suggests AI's usage in HR is expected to grow in the coming years. IDC's Future of Work 2022 research predicted that this year, 60 percent of global 2000 businesses will deploy AI and machine learning (ML) tools to support the entire employee life cycle experience.

What's next for generative AI? ›

Over the course of the next three years, there will be many promising use cases for generative AI. The most valuable and viable are personalized marketing campaigns, employee-facing chatbots, claims prevention, claims automation, product development, fraud detection, and customer-facing chatbots.

How will generative AI change the workplace? ›

Generative AI and chatbots including ChatGPT will create many new jobs and change the nature of existing work positions. That will start as high as the C-suite, with the position of chief AI officer, and filter down through employment in fields from IT to service.

What is the danger of generative AI? ›

And while not strictly a cybersecurity problem, there's a danger that generative AI could provide answers that use copyrighted information from sources, leave out critical information or even lead people to the wrong answers, which could all present legal liabilities.

How AI is reinventing HR? ›

AI is disrupting how organizations recruit and train employees and how data is harnessed to provide people with analytics. By freeing HR professionals from repetitive tasks, they can focus on strategic tasks that demand human intervention.

What is the benefit of generative AI? ›

Benefits of generative AI

The most compelling advantage generative AI proposes is efficiency, in that it can enable businesses to automate specific tasks and focus their time, energy and resources on more important strategic objectives. This often results in lower labor costs and an increase in operational efficiency.

What is an example of generative AI? ›

What are some examples of generative AI tools? Generative AI tools exist for various modalities, such as text, imagery, music, code and voices. Some popular AI content generators to explore include the following: Text generation tools include GPT, Jasper, AI-Writer and Lex.

Will HR get replaced by AI? ›

Does AI in HR replace humans? The short answer is no. AI's role in HR is to help humans, not replace them. While AI can certainly handle many of the tasks that are currently done by human HR managers, it's still up to humans to make decisions about the work that AI does.

What jobs will AI replace by 2025? ›

The Top 10 Jobs Most Likely to Be Replaced by AI
  • Entry-level Admin Roles.
  • Data Entry Clerks.
  • Software Engineers and Coders.
  • Customer Service Reps.
  • Paralegals.
  • Copywriters and Content Roles.
  • Graphic Designers.
  • Bankers and Accountants.
May 22, 2023

What jobs will AI replace by 2030? ›

How Many Jobs Will AI Replace By 2030?
  • Data Scientist. Data scientists are a new generation of data analytics experts, already among the most in-demand professions for AI. ...
  • Artificial Intelligence And Machine Learning Engineers. ...
  • Data Labeling Professionals. ...
  • Hardware Specialists For Artificial Intelligence.
Mar 30, 2023

What is generative AI predictions for 2023? ›

In 2023, influencers will start using generative AI tools to enhance their appearance and create content for their social media posts. This will lead to the emergence of "synthetic" influencers who will have entirely generated images, videos, voices, and dialogue, making them appear like real humans.

Where is generative AI headed in 2023? ›

We predict that in 2023, as businesses start to realize the benefits of using AI to help with things like customer service, sales, and client retention we will see them adopt them with enthusiasm.

Why is generative AI popular? ›

Generative AI reduces the money and time needed for content creation. It could also breed innovation, paving the way for new business models and applications. However, the technology could displace jobs and lead to copyright issues and data security risks.

What will be the most significant impact of generative AI on the future of jobs? ›

The report acknowledges that generative AI could also create new jobs and industries that do not exist today or are not captured by current data. Moreover, generative AI could enhance labor productivity growth and boost global GDP by as much as 7% over time.

What are some of the common challenges generative AI is facing? ›

However, despite its potential benefits, implementing Generative AI in a company and its applications is not without its challenges. Companies face hurdles in terms of data quality, employee training, ethical considerations, security measures among others when utilizing this technology.

What is generative AI How is it being used today? ›

Generative AI models use neural networks to identify the patterns and structures within existing data to generate new and original content. One of the breakthroughs with generative AI models is the ability to leverage different learning approaches, including unsupervised or semi-supervised learning for training.

What is the disadvantage of generative design? ›

Generative design also comes with drawbacks, though not necessarily of its own doing. The biggest is its potential to automate many jobs and make human workers redundant. That's especially true in the construction industry. Wood trades, painters, plasterers, floorers, and decorators are also vulnerable to automation.

Why AI should not replace humans? ›

One of the main reasons why AI cannot replace human beings is the lack of creativity. Humans possess a unique ability to think creatively and come up with new and original ideas. Creativity is a complex human trait that is influenced by various factors such as emotions, culture, and experiences.

What are the negative impacts of AI in HR? ›

If used too frequently to replace regular human interactions, the technology can also start to make your work environment feel distant and alienating. If you don't keep these concerns in mind, you risk making your hiring and HR processes less useful and more painful for current and potential employees.

What AI is and how it can will be used for HR purposes? ›

AI has streamlined the recruitment, onboarding, training, and ongoing staff analytics processes. Using AI to data-mine a company's HR information system can help predict employees who are at risk of leaving the company and which will guide and focus retention activities.

How can artificial intelligence transform the future of HR analytics? ›

Organizations can use AI-powered data analytics or predictive analytics to develop personalized training programs that align with different employees' learning patterns and needs. This helps achieve a better synergy between the training programs and employee engagement.

What are the common applications of generative AI? ›

Generative AIs are beneficial in producing new music pieces. Generative AI-based tools can generate new music by learning the patterns and styles of input music and creating fresh compositions for advertisements or other purposes in the creative field.

How are companies using generative AI? ›

For instance, companies may use generative AI models to analyze large amounts of data and make predictions about prices or improve the accuracy of their services.

What are the most popular generative AI? ›

Generative AI Apps and Tools: Table of Contents
  • ChatGPT.
  • AlphaCode.
  • GitHub Copilot.
  • Bard.
  • Cohere Generate.
  • Claude.
  • Synthesia.
  • DALL-E 2.
May 2, 2023

What are the major generative AI models? ›

Notable generative AI systems include ChatGPT (and its variant Bing Chat), a chatbot built by OpenAI using their GPT-3 and GPT-4 foundational large language models, and Bard, a chatbot built by Google using their LaMDA foundation model.

Will HR be automated by AI? ›

While AI can automate many tasks traditionally done by HR professionals, it is important to note that AI cannot replace the human touch entirely. HR professionals will still be needed to provide a personal touch, make strategic decisions, and manage complex issues that cannot be automated.

Is HR in danger of automation? ›

Entry level HR jobs are among those at the highest risk of automation, according to new research from HR qualification company Academy to Innovate HR (AIHR).

Can chatbot replace HR? ›

While AI can potentially transform HR, it is unlikely to completely replace HR professionals. Instead, AI will augment HR roles, allowing professionals to focus on more strategic tasks that require human decision-making and interaction.

What jobs will AI not be able to replace? ›

As such, jobs that require high emotional intelligence, such as therapists, social workers, and nurses, are not likely to be replaced by AI. Specialized Professionals: Jobs that require deep expertise in a particular field, such as doctors, lawyers, and scientists, are less likely to be fully replaced by AI.

Which jobs are in danger due to AI? ›

5 Job Roles in Danger of Disappearing Because of Generative AI
  • As AI tools become increasingly popular, people worldwide are concerned that the technology will replace human employees in several job roles.
  • Along with assembly lines, AI may also start impacting many sales, marketing, law, and healthcare roles.
May 16, 2023

What will AI do in 10 years? ›

In the next 10 years, it is predicted that advancements in AI technology will continue to allow for a more efficient way of life. Through machine learning algorithms and deep neural networks, AI can also learn how to solve complex problems faster than humans ever could.

What is Elon Musk's warning about AI? ›

Tesla Inc.

CEO Elon Musk, renowned for his outspoken warnings about the potential dangers of artificial intelligence (AI), has once again cautioned about the risks posed by a “benign dependency” on these complex machines, tweeting that it can be dangerous to civilization.

What year will AI surpass human intelligence? ›

The path to AGI will likely require unpredictable breakthroughs and innovations. The median predicted date for AGI on Metaculus, a well-regarded forecasting platform, is 2032. To me, this seems too optimistic. A 2022 expert survey estimated a 50% chance of us achieving human-level AI by 2059.

What jobs will be left after AI? ›

Insider talked to experts and conducted research to compile a list of jobs that are at highest-risk for replacement by AI.
  • Tech jobs (Coders, computer programmers, software engineers, data analysts) ...
  • Media jobs (advertising, content creation, technical writing, journalism)
5 days ago

How will generative AI change the world? ›

Generative AI Market Trends:

GenAI is considered a major game-changer for businesses, as it has the potential to increase efficiency and productivity, reduce costs, and create new opportunities. Businesses that are capable of effectively leveraging technology are likely to gain a significant competitive advantage.

Will 85 million jobs be replaced by machines with AI by the year 2025? ›

Artificial Intelligence, AI and technology are expected to displace around 85 million jobs by the year 2025. This finding comes from the latest Global Risks Report 2023 issued by the World Economic Forum. With the rise of AI tools, such as ChatGPT and more, many jobs are expected to be displaced.

What is the future of AI in 2030? ›

By 2030, artificial intelligence (AI) will be an essential component of day-to-day company operations, assisting individuals in their creative activities, producing new ideas, and solving previously unachievable technologies. In some cases, collaborating with AI will be needed.

What is the most advanced AI yet? ›

GPT-3 was released in 2020 and is the largest and most powerful AI model to date. It has 175 billion parameters, which is more than ten times larger than its predecessor, GPT-2.

How much is the generative AI industry worth? ›

According to Precedence Research, the global generative AI market size valued at USD 10.79 in 2022 and it is expected to be hit around USD 118.06 by 2032 with a 27.02% CAGR between 2023 and 2032.

What is the latest AI technology in 2023? ›

What is the trend in AI and machine learning in 2023? A. Terrific growth in automation across different business sectors, implementation of edge computing to improve efficiency, and computer vision are some of the topmost trends in AI and machine learning in 2023 that the market will be watching out for.

What are the criticism of generative AI? ›

Critics of generative AI are also likely to overestimate individual contributions. The size of generative AI models are huge, and the contribution of any single person is miniscule. Generative AI systems should be prohibited from producing content based on the style of an artist without their permission.

What are limitations of generative AI? ›

Generative AI can't generate new ideas or solutions

One of the key limitations of AI is its inability to generate new ideas or solutions.

What is the risk of generative AI? ›

Without proper governance and supervision, a company's use of generative AI can create or exacerbate legal risks. Lax data security measures, for example, can publicly expose the company's trade secrets and other proprietary information as well as customer data.

What is the effect of automation and AI on HR? ›

Human Resource Implications of AI and Automation

By utilising tools such as chatbots enabled by AI and applicant tracking systems, HR can streamline candidate sourcing, screening, and shortlisting, thereby reducing the time and effort spent on manual recruitment tasks.

How does AI help HR recruitment? ›

What is AI for Recruiting? AI recruiting is the process of using artificial intelligence to automate time-consuming, repetitive tasks while offering personalization and data insights throughout the hiring process.

What are some potential drawbacks or concerns with using generative AI? ›

Disadvantages Of Generative AI
  • Cost. Generative AI can be expensive to implement. ...
  • Time. Generative AI can take a long time to train and deploy. ...
  • Data Quality. ...
  • Overfitting. ...
  • Explainability. ...
  • Ethical Concerns. ...
  • Mitigating the Disadvantages of Generative AI. ...
  • Conclusion.

What is the difference between AI and generative AI? ›

Generative AI vs. AI

Generative AI produces new content, chat responses, designs, synthetic data or deepfakes. Traditional AI, on the other hand, has focused on detecting patterns, making decisions, honing analytics, classifying data and detecting fraud.

Why is AI important in HR for digital transformation? ›

HR. Artificial intelligence is used across the employee lifecycle, from recruitment and onboarding, to managing talent acquisition, boosting employee satisfaction, automating learning and development, and creating an overall better employee experience.

What are the benefits and drawbacks of using AI in HR decision making? ›

Pros of AI for HR Departments
  • A Streamlined Process. ...
  • Less Human Biases. ...
  • Improved Candidate Experience. ...
  • Allows You to Invest In Other Aspects of Your Business. ...
  • Too Dependent On Certain Keywords. ...
  • Less Human Involvement. ...
  • Reduced Accuracy and Reliability. ...
  • Requires an Improved Skillset.
Sep 25, 2019

What are the negative impact of automation on HR? ›

Now let's look at the negative impact of automation in HR. The potential downsides of automating HR management include a less personal, more data-driven process and more invasive use of AI, which some see as factors that erode a unified company culture.


1. LIVE EVENT: Experience Phenom X+ — Generative AI for HR Demonstration
2. The AI Revolution in HR: Preparing for the Future with a Dash of Fun
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3. Investor’s POV: The Impact of Generative AI on the Future of SaaS
(Insight Partners)
4. The Incredible Creativity of Deepfakes — and the Worrying Future of AI | Tom Graham | TED
5. Artificial Intelligence and the Future of Higher Education
(Global Silicon Valley)
6. How Fast is Too Fast? What Generative AI Means for Work
(HR Leaders Academy - Shaping the Future of Work)


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Author: Sen. Emmett Berge

Last Updated: 09/17/2023

Views: 6470

Rating: 5 / 5 (60 voted)

Reviews: 83% of readers found this page helpful

Author information

Name: Sen. Emmett Berge

Birthday: 1993-06-17

Address: 787 Elvis Divide, Port Brice, OH 24507-6802

Phone: +9779049645255

Job: Senior Healthcare Specialist

Hobby: Cycling, Model building, Kitesurfing, Origami, Lapidary, Dance, Basketball

Introduction: My name is Sen. Emmett Berge, I am a funny, vast, charming, courageous, enthusiastic, jolly, famous person who loves writing and wants to share my knowledge and understanding with you.