Could you tell if I’d written this article with ChatGPT right now? Most people by now have used generative AI to produce some form of content for them such as a blog, an email, a resume, or to analyze applications. What would have taken time and effort to do manually can be completed in seconds with Artificial Intelligence (AI). This is the hope—and possibly the hype—around generative AI and productivity.
But if we drill down into the data since ChatGPT’s launch in late 2022, has generative AI been the transformative force we thought it would be?
As someone who has seen firsthand how technology shapes business strategies, I believe the truth lies somewhere in between. While generative AI can support productivity, it also introduces new challenges and frustrations for employees that organizations should navigate thoughtfully.
Examples of AI in the Workplace
Large Language Models (LLMs) can scan huge amounts of text from online sources and generate text on a topic to meet your brief – quickly. There are many AI applications available for organizations to use across their different departments and functions.
The main use cases are:
After two years of access to some cost-effective applications, many industries have used generative AI to speed up their processes, in what really does look like productivity.
AI in Healthcare
In the healthcare industry, generative AI is having a huge impact where the stakes are the highest. For example, AI-powered tools can assist doctors by analyzing:
After two years of access to some cost-effective applications, many industries have used generative AI to speed up their processes, in what really does look like productivity.
Which can all lead to the faster identification of health issues. And there are medical imaging AI applications that can detect abnormalities the human eye would miss. AI is also reducing the administrative burden on healthcare staff by automating appointment scheduling, billing, and patient record management.
AI in Retail
In retail, the adoption rate of AI is expected to reach 34.8% by 2040, with 1.3 million eCommerce businesses using AI technologies. Retail and eCommerce have embraced AI to:
- 1
Improve Search Capabilities: AI-driven recommendation engines analyze customer data to suggest products based on individual preferences, browsing history, and purchasing patterns. We’ve all noticed our search results getting smarter and smarter, our ads becoming more targeted!
- 2
Streamline Inventory Management: Retailers use AI to predict demand, manage inventory, and create pricing in real-time, reducing overstock and ensuring that popular products are available when needed
- 3
Improve Customer Experience: AI-powered chatbots are providing customer support around the clock, answering questions, and assisting with orders
AI in Professional Services
In professional services, including consulting, finance, and talent acquisition, generative AI is being used to improve crucial processes. In consulting and financial services, AI can analyze market trends, forecast business outcomes, and provide data-driven recommendations. In human resources and talent acquisition, AI is streamlining the hiring process. AI can screen large volumes of candidates, schedule interviews, and even assess talent based on resumes and interview performance, improving both speed and quality in hiring.
Pros and Cons of AI in the Workplace
From the quick run through of the industry applications of AI in the section above, it seems clear that there’s a link between generative AI and productivity. And if tasks are being completed quickly and productivity is high, then there are other clear benefits of integrating generative AI into the workplace, including:
Pros of AI in The Workplace:
- 1
Increased Productivity: AI automates repetitive tasks, freeing employees to focus on strategic, creative, or more complex work
- 2
Cost Savings: By reducing the time spent on routine tasks, businesses can lower operational costs and potentially achieve better outcomes with fewer resources
- 3
Innovation: AI enables companies to prototype, iterate, and innovate faster, bringing new products and services to market more quickly
- 4
24/7 Operations and Communications: AI doesn’t need to sleep. So tasks like customer service or data processing can continue around the clock, enhancing operational efficiency
However, it’s important to note that LLMs in AI are using the internet to build a statistical model of next word prediction. Which has nothing to do with whether or not the sentence or fact is true, just that it occurred the most online. This can cause a lot of problems for employees and companies alike, including:
Cons of AI in The Workplace:
- 1
Quality Control: While AI can be incredibly efficient, it is not infallible. Errors in AI-generated content or decisions can lead to reputational risks and financial losses
- 2
Perpetuating Mistakes: SHRM gives a great example of the dangers of how authoritive AI-generated content can seem. In an employee handbook, which are usually only scanned, it would take a long time to recognize a mistake in one
- 3
Homogeneity of Communications: LLMs need regular updates to their training models. And when elements like brand, tone of voice, or company culture evolve, they might not be reflected in LLM outputs. Additionally, LLMs tend to reinforce the status quo, which can alienate some communities in a diverse workforce
- 4
Data Privacy Concerns: Ensuring privacy and security can become challenging, particularly in industries like healthcare or finance
Arguably, all of the above cons would undo the value of the productivity achieved through AI. Additionally, AI can also cause:
- 1
Employee Dissatisfaction: We can’t forget the cons on employees when it comes to generative AI. What would once have been celebrated as dedicated hard-work and attention to detail, is now undermined as “working hard, not working smart”, which can lead to feelings of disillusionment that credit is going to people taking shortcuts
- 2
Job Displacement: As AI takes over more tasks, there is a real concern about job displacement, especially in roles heavily reliant on repetitive or routine work
- 3
Improve Customer Experience: AI-powered chatbots provide customer support around the clock, answer questions, and assist with orders
What Does The Data Say About the Impact of Generative AI on Employment and Labor Productivity?
With only a few years of evidence, it’s hard to determine the relationship between generative AI and productivity.
So far, the data suggests that employer expectations are high. According to Forbes, 72% of businesses have adopted AI for at least one business function and 64% of businesses believe that artificial intelligence will help increase their overall productivity. McKinsey has even estimated that LLMs and generative AI applications could increase corporate profits by $4.4 trillion every year due to their impact on productivity.
However, the dangers of misinformation from generative AI could have a negative impact on productivity long-term. For example, in 2023 two New York lawyers were sanctioned and fined $5,000 for using ChatGPT to create a legal brief that had six made up case citations. The time it saved them to produce the brief was outweighed by the efforts the court had to go to to identify the fictional cases, create a precedent for judgment, and then go through the legal proceedings to sanction them.
Additionally, the threat to people’s jobs cannot be ignored. According to the World Economic Forum, AI is expected to displace 85 million jobs. The tech industry is leading the way in replacing workers with AI. Notable examples include MSN who terminated dozens of journalists early in 2020 in favor of AI-generated content, and IBM announced plans to replace 30% of its back-office roles with AI.
My Takeaway On Generative AI and Productivity
In my opinion, the question around generative AI and productivity, whether it’s the magic ingredient we’ve been searching for, is both fact and fiction.
Generative AI is just one part of the productivity puzzle and needs to be weighed against other workforce planning initiatives like incentive schemes, internal talent mobility, equitable practices, and career development. While AI is effective for handling repetitive tasks, the human touch remains essential for improving service levels beyond what AI alone can achieve.
We won’t live in a world where robots run everything anytime soon. So we still need motivated people to keep businesses operational. RPO providers like Pierpoint can help you shape your people strategy to create a productive workforce that’s adaptable to future innovations. Book a call with one of our experts today to discuss your needs.
Greg Vaughn, Sr. Director of Program Delivery at Pierpoint International, is an accomplished leader in global RPO and talent acquisition with over 20 years of experience. He has led recruitment teams supporting Fortune 500 companies with over 4,500 hires annually, as well as small to mid-sized organizations with more targeted hiring needs.
Greg’s expertise includes designing and managing complex, end-to-end recruitment solutions that optimize talent acquisition processes and tools, integrate recruitment marketing and social media strategies, and provide talent mapping and executive placement services across EMEA, LATAM, and North America. His approach emphasizes team collaboration and a strong customer focus, consistently achieving high levels of client satisfaction.
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