Artificial intelligence (AI) is transforming industries as organizations leverage the latest technologies to drive efficiencies and make smarter data-driven decisions. A common concern is that AI will replace workers, but, at least so far, these fears haven’t borne out. Rather than replacing workers, AI is reshaping the job market by creating new roles and enabling workers in existing roles to work more strategically.

Deciphering AI’s growth

The term artificial intelligence was first coined by John McCarthy in 1956—the same year the first transistor computer was released. In the years since, the technology has grown to the point that we might have finally achieved artificial intelligence—or something close to it.

In late 2022, a new milestone in AI was achieved and user adoption skyrocketed following the launch of ChatGPT-3.5. AI offers many beneficial capabilities for businesses, including automation, enhanced data analytics, and improved data-based decision-making and problem-solving.

As more companies recognize the benefits of AI, research from Bloomberg Intelligence estimates that generative AI will grow into a $1.3 trillion market by 2032, compared to $40 million in 2022. Given the growth and impact of AI for businesses, it’s no longer a matter of whether to embrace AI, but rather how to maximize business outcomes by using AI.

Key insights on AI and hiring

With more and more businesses embracing AI, recruiting and talent-acquisition teams are increasingly looking for experts in AI who can help incorporate the emerging technology into their systems and workflows. According to data from the Upwork Research Institute, the average number of weekly search queries related to generative AI increased 10 times from the fourth quarter of 2022 to the first quarter of 2023. The data also shows that in the same period, weekly job posts looking for generative AI skills increased by more than 600%.

While some individuals may be concerned that AI will lead to job cuts, Upwork Research Institute data also showed a promising trend with AI’s impact on hiring, with 49% of hiring managers surveyed saying they will hire more independent talent and 49% saying they will hire more full-time employees as a result of generative AI.

Jobs augmented and created by AI

As AI continues to see widespread adoption across organizations and industries it’s proving its ability to create new jobs and help people work more effectively in their current roles.

Improved productivity in existing roles

According to McKinsey, by 2030, activities that account for up to 30% of hours currently worked across the U.S. economy could be automated—a trend accelerated by generative AI. As AI automates manual, repetitive tasks, workers can be more productive and focus on driving improved business outcomes.

Here are a few examples highlighting how AI can be used in business to improve productivity:

• Doctors and other medical professionals. Keeping track of the latest healthcare research and diagnoses can be challenging and time-consuming. AI tools powered by machine learning and natural language processing can quickly analyze medical literature, research, and scans to provide relevant information to doctors. This can help doctors discover and diagnose potential illnesses, explore treatment options, and make better informed decisions about patient care—while freeing up time to spend directly interacting with patients.
• Writers. Writers and other content creators are embracing AI tools to save time and improve the content development process. Tools like ChatGPT, Google Bard, and Jasper enable users to input text prompts to gather research and automatically generate drafts of written content such as outlines, social media posts, emails, and articles. Writers can also use AI tools to generate mockup visuals for their content, which can help provide context and direction before submitting a graphic request to a designer. While AI tools can be used for inspiration and initial drafts, thorough editing and fact-checking should be completed before finalizing any AI-generated content.
• Human resources professionals. Leveraging AI can enable HR professionals to automate routine tasks, work more strategically, and focus more on the “human” side of human resources by engaging with candidates and employees. Some ways AI can be used in human resources include, drafting recruitment content such as job descriptions and interview questions with generative AI tools, automating candidate screening with AI capabilities in applicant tracking systems (ATS), driving candidate engagement with AI-powered chatbots, and centralizing employee documents in human resources information systems (HRIS).

Creation of new roles

In addition to increasing productivity in existing roles, AI is also driving job creation with entirely new roles. According to global research from the World Economic Forum, 50% of organizations surveyed expect artificial intelligence to create job growth in the next five years, compared to 25% who expect AI to lead to job losses. And while some individuals may think AI roles are only a fit for workers with an engineering or related technical background, non-technical roles involving AI are also on the rise.

Examples of new job opportunities that incorporate AI include:

• Prompt engineers. Generative AI applications like ChatGPT require users to enter inputs, known as prompts, to generate desired outputs. Prompt engineers are skilled at developing and refining prompts to help the application better understand the information about the input and, as a result, improve responses. Effective prompt engineering requires creativity, an understanding of the AI application or platform, and knowledge of the latest updates in prompt development.
• Machine learning engineers. Machine learning engineers often have backgrounds in data science, software engineering, or computer science. They’re responsible for building AI systems and models and performing statistical analysis to improve AI model performance. Experts in machine learning leverage large datasets to train models and neural networks to recognize patterns and make predictions, among other functions.
• AI content editors and fact-checkers. While some organizations and professionals are turning to AI tools to generate and improve writing, a human-centered review process is essential to ensuring AI-generated content is accurate, free from biases, and aligns with the organization’s brand and tone. Individuals with traditional writing and editing backgrounds are expanding their client bases by taking on roles or projects as AI content editors and fact-checkers.

Jobs threatened by AI

While AI has proven itself able to improve the productivity of some roles, other roles or specializations may be threatened by automation. However, as is the case with any other technology innovations, many roles will evolve in response to AI, rather than being eliminated.

For people in roles likely to be threatened by AI, they should look for ways to embrace AI tools and include them in their workflow. Or, they might identify and develop new skills to advance their careers or continue to show their value in their organization.

Data collection and processing

Data from the Pew Research Center shows that workers who focus on basic data collection are among the most vulnerable to automation by AI. These roles may include data entry jobs, basic research positions, and preliminary data analysts. Many data entry tasks are manual and highly repetitive, tasks that AI can complete at unprecedented speeds, while minimizing the risk of human errors.

Instead of eliminating jobs in this field, AI can boost data entry productivity and enable team members to focus on more strategic, value-added tasks and skills, such as data analysis and critical thinking. This can help them position themselves for new career opportunities in their organizations.

Basic customer service

Several AI-powered tools have emerged in recent years to automate and improve customer service.Embracing AI for customer service can help support faster, round-the-clock response times and tailored solutions that align with customers’ specific needs.

AI-driven customer support tools include:

• Chatbots. Using natural language processing and machine learning, AI-powered chatbots automatically answer customer questions, offer personalized recommendations, provide support, and, when necessary, direct more complex questions to customer service team members.
• Automated phone systems. Also known as interactive voice response (IVR) systems, automated phone systems interact with customers using voice prompts and keypad responses to answer simple inquiries and route calls to the right department.
• Self-service and knowledge-base systems. These systems feature advanced search functionality and include resources such as frequently asked questions (FAQs), tutorials, troubleshooting guides, and interactive tools, to help customers find answers on their own.

While AI has the potential to automate basic customer service tasks, the latest technology can also empower customer service professionals to be more productive and take more of a consultative approach to customer interactions. A survey from DialPad of more than 1,000 customer service professionals found that almost 60% of respondents believe that AI helps them save time or work faster.

Individuals who work in customer service can embrace AI-powered analytics from chatbot logs, phone call recordings and transcripts, emails, and customer reviews, to identify pain points and opportunities to improve the customer experience.

Low-level finance and accounting tasks

AI is also impacting entry-level roles in the finance and accounting sector. An Intuit survey of 2,000 accountants found that 48% of respondents plan to invest in automation tools and AI in the next year

Some of the accounting tasks that can be automated using AI include data collection, data entry, categorization, reconciliation, and invoicing. On the finance side, AI tools can automatically process high volumes of data and identify financial patterns and trends to help make data-driven decisions related to vetting borrowers, calculating risk, and managing investments.

The good news for early career finance and accounting professionals is that AI can empower them to accelerate career growth. For example, research published by Fortune shows that at KPMG, one of the largest consulting firms, AI is enabling recent graduates to complete tax work that was previously intended for staff with at least three years of experience.

Entry-level legal work

AI capabilities can also automate many tasks associated with entry-level legal work. According to research from LexisLexus, 36% of lawyers surveyed have used a generative AI tool either personally or professionally.

Ways AI is used in entry-level legal work include:

• Document automation. Generative AI tools can help create initial drafts of standard legal documents, such as contracts, nondisclosure agreements (NDAs), wills, and leases.
• Contract review. Manually reviewing lengthy legal documents can be time-consuming and presents the risk for human error. AI tools with machine learning capabilities can review and analyze contract language to flag information that may have otherwise been overlooked during an initial review by a legal team member.

Similar to how AI is helping accounting professionals level-up in their roles, the Fortune article cited above also shows that at law firm Macfarlanes LLP, AI is enabling junior lawyers to interpret complex contracts that were previously the responsibility of their more experienced peers, which can help-fast track the timeline to becoming a partner.

Upskilling and AI adaptation

Looking ahead to the future of work, AI will likely continue to create new jobs and increase automation in others. Research from McKinsey estimates that at least 12 million U.S. workers will change to another field by 2030, largely due to the impact of generative AI.

Even among individuals who don’t need to completely pivot their careers in response to AI growth, AI will have an impact on most roles across industries and focus areas. As stated by Harvard Business School professor Karim Lakhani, “AI is not going to replace humans, but humans with AI are going to replace humans without AI.” Because of this, upskilling and learning about the latest AI technology are essential to ongoing career relevance and growth.

Continuous learning

A global report from the World Economic Forum estimates that 44% of workers’ core skills are expected to change in the next five years. Top organizational priorities or skills training include analytical thinking, creative thinking, and the ability to use AI and big data. The research also shows that while six in 10 workers will require training and reskilling before 2027, only half of workers have access to adequate training opportunities today.

Individuals and organizations can both play a role in prioritizing continuous learning, which can help ensure workers possess the most in-demand skills and can drive positive business outcomes as technology and business priorities evolve.

Some of the ways individuals can focus on continuous learning include:

• Completing courses and earning certifications about AI and other in-demand skills through online platforms like Coursera, edX, Skillshare, and Udemy
• Listening to podcasts and reading books, news articles, and research papers on AI and other disruptors relevant to their jobs
• Joining and participating in professional AI-focused communities
• Gaining firsthand experience with AI by experimenting with tools directly

Organizations can support ongoing learning and development by offering resources such as:

• An overview of available AI and other technology tools during onboarding
• Online learning platform access
• Skill assessments
• Stretch assignments and experiential learning
• Mentorship opportunities
• Stipends for professional development events and courses

Preparing for an AI-augmented future

As AI continues to have a significant impact across industries, organizations that proactively integrate AI into their business strategies—rather than being resistant to AI—are most likely to stay ahead of their competition and remain relevant as customer demands and priorities shift.

Redefining business models

According to research from UKG, 78% of C-suite leaders surveyed said their company is currently using AI. Additionally, 71% of C-suite leaders indicated that increasing and advancing their use of AI is a priority for their organization, underscoring the competitive advantage AI can bring.

Many organizations are embracing AI tools to help their teams work more effectively, while others are also integrating AI directly into their business models to improve the customer experience.

Here are some examples of creative ways companies have incorporated AI into their business models:

• Amazon. As one of the largest companies in the world, Amazon integrates AI across the business, with one of the most well-known examples being the virtual assistant Alexa. Like many retailers, Amazon also uses AI to identify customer patterns and trends and offer personalized products recommendations. One of the more innovative ways Amazon leverages AI is by deploying 750,000 collaborative robots to automate manual tasks so employees can focus more on customer interactions. In 2022, one billion packages were sorted by Amazon’s AI- and machine learning-powered robotic handling system, called Robin.
• Coca-Cola. In early 2023, Coca-Cola launched a contest inviting digital artists to create original artwork on an AI platform using iconic assets from the brand’s archive. The platform, “Create Real Magic,” was created by OpenAI and Bain & Company and combined the capabilities of GPT-4 for text creation and DALL-E, which generates art and images based on text inputs. More than 120,000 images were created in eight days with no paid media spending. Following the initial contest in March, Coca-Cola launched another iteration of the platform in November 2023, enabling individuals to create holiday cards using the same technology and iconic brand assets.
• Johnson & Johnson. Neutrogena, a Johnson & Johnson cosmetics and skincare brand, partnered with Nourished, a 3D-printed dietary supplements company, in early 2023 to print personalized skincare gummies for customers. The process uses existing AI-powered Skin360 technology from Neutrogena, which enables users to scan an image of their face on the mobile website for a digital skincare assessment and personalized product recommendations.

Debunking common fears and misconceptions about AI

Despite the significant benefits AI has to offer, many individuals are concerned about the potential of AI. In fact, according to a report from Pew Research Center, 52% of Americans surveyed say they feel more concerned than excited about the increased adoption of artificial intelligence. One of the top reasons some people may be apprehensive about AI is that they have misconceptions about the technology and its impact.

Common misconceptions about AI include:

• AI is similar to human intelligence. While AI-powered conversations may seem realistic, these conversations simply show AI-powered algorithms at work. AI doesn’t possess human emotions, can’t learn on its own like the human brain, and some outputs created by AI tools are inaccurate or biased. Because of this, taking a collaborative approach that includes both technology and human workers is essential to successful AI adoption. In fact, research from Workday found that 93% of business leaders surveyed believe humans should be involved in AI decision-making.
• AI is unbiased. Because people create AI tools and systems, and because these systems are largely trained on material created by people, biases can be incorporated into AI technology. When bias makes its way into a tool during AI development—even unintentionally—the tool can skew results toward or against certain groups. This can introduce implicit biases and microaggressions into a product, which can undermine customer confidence in a brand, and have a negative impact on people’s lives.
• AI can only be used by technically skilled people. Some individuals may be concerned about falling behind in their careers because they lack the technical skills to embrace AI. However, AI tools such as ChatGPT, Midjourney, and Jasper make it easy for any user to input conversational prompts and experiment with AI. Additionally, some of the emerging AI-related roles, including AI ethicists, AI researchers, and AI policy specialists, are non-technical.

Addressing global challenges and improving lives with AI

As companies identify ways for AI to drive business growth, AI also has the potential to solve global challenges. A survey of 2,000 U.S. adults conducted by The Verge found that 74% of respondents believe AI will have a significant impact on society as a whole, a higher percentage than any other emerging technology such as augmented reality or autonomous vehicles.

The survey also found that while many are concerned about AI’s potential impact, about half of respondents believe AI will have a positive impact on addressing challenges such as developing new medical treatments and economic empowerment.

To maximize the ability of AI to address global challenges, the United Nations launched an advisory board specifically aimed at harnessing AI for the common good.

Here are two ways AI has the potential to address global challenges:

• Disaster relief and humanitarian aid. AI can analyze data from social media, satellite images, and other relevant sources to pinpoint areas affected by natural disasters. It can then direct aid to those in need, which can help save lives and improve recovery efforts. xView2, a machine learning system developed by the U.S. Department of Defense and Carnegie Mellon, combines algorithms with satellite imagery to identify damage in disaster areas, such as recent earthquakes in Turkey and Syria, and prioritize relief efforts.
• Food insecurity. As the global population increases and climate change presents challenges with growing food, AI can help support food security around the world. Charlie Li, a professor at the University of Florida, uses AI to combat food insecurity in a few ways, including analyzing large datasets to develop more resilient crops, using sensors, robots, and drones to collect data on crop and soil conditions, and detecting crop diseases and pests early with image-recognition algorithms.

This article originally appeared on Upwork..com Resource Center (Upwork is a company that helps businesses find talent and people find work) and was syndicated by MediaFeed.org. 

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