Let’s Chat About ChatGPT: What Business Leaders Should Know About AI and the Future of Work


As AI-based innovations like ChatGPT gain momentum, it’s never been more important for businesses to invest in the data literacy of their teams.

By now, you’ve probably heard about ChatGPT, the new large language model (LLM) from OpenAI that uses advanced artificial intelligence algorithms to generate human-like responses to natural language questions and prompts. The tool has gone viral, astonishing users with its ability to do everything from writing sonnets to summarizing essays to debugging computer code.

The potential of ChatGPT and similar AI-driven innovations  goes beyond a fun party trick—these technologies are already being implemented in workplaces around the world. Media companies are using AI to help produce content. Software companies are incorporating AI features into their customer support functions. Microsoft is adding “new, AI-powered capabilities” into products like Microsoft Teams and Bing. We leveraged ChatGPT and other AI-powered writing tools in the creation of this blog post, and we’re hosting an internal competition to explore additional applications ChatGPT could have for our business. 

For example, here was ChatGPT's response when we asked it to write a paragraph from the perspective of a digital transformation leader assessing the impact that AI-driven technologies like ChatGPT will have on the future of the workforce: 

ChatGPTdigitalliteracy

While it’s impossible to tell the future with 100% certainty, one thing seems clear: artificial intelligence is poised to transform the way we work in the coming decades. In a recent Forbes article, Bill Gates called AI “every bit as important as the PC, as the internet.” And if AI is as important as the PC or the internet, then knowing how to interact with AI tools is as important as knowing how to type or do a Google search.

For business leaders, the question that follows is: “What does this mean for me and my business?” Below, we unpack a few of AI’s implications for businesses—and what leaders should be doing to set their teams up for success.

AI makes data literacy more important than ever 

AI is powered by data; without data, even the smartest algorithms are nothing but a jumble of equations. For business leaders, this means that investing in the data literacy of their workforce is more important than ever.

In order to take full advantage of the data-driven insights AI can offer, employees need to understand the fundamentals of data: how to interpret it, how to communicate it, and how to use it to inform decisions. For example, a marketing team could use AI to analyze customer preferences in order to create more targeted campaigns—but first they have to be able to understand, process, and interpret the data. 

The data shows there’s work to be done on this front. According to research from data analytics firm Qlik, only 11% of employees “feel fully confident in their data literacy skills.” This data literacy skills gap is already costing businesses and their employees valuable time, money and opportunity—and the cost will only increase as AI and other automation innovations permeate the workplace. 

Investing in data literacy starts at the top. Leaders need to be able to explain the value of data-driven decisions to their teams, and manage AI-driven projects effectively. There’s work to be done on this front as well: only 43% of executives and 38% of managers at the average-performing company report a strong understanding of data concepts, according to research by McKinsey. If they’re going to spearhead an AI-driven transformation within their workforce, leaders will need to begin by investing in their own data comprehension. 

Equally important to understanding how to leverage AI innovations is understanding the limitations of the technology. While AI’s capabilities are rapidly expanding, there are still tasks it can't—and shouldn’t—perform. To return to ChatGPT as an example, it may provide incorrect information, especially when it has not been trained on the latest information or data. The data sets that ChatGPT was trained on contain biases and stereotypes, which may be reflected in its responses. And while it can generate human-like text, it lacks the creativity and imagination of a human.

Ultimately, AI is a tool, and like any tool, its usefulness depends on how well it’s used. It’s important for leaders and their teams to understand the advantages as well as the limitations and pitfalls of AI technology, so they can make educated decisions about how best to leverage it. And that starts with an investment in data literacy.

Upskilling and reskilling are mission-critical

As AI capabilities expand, so does the skill set required to operate these tools. Businesses need employees who are able to interact with the technology, understand the data, and create AI solutions that help the business achieve its goals. That means that upskilling and reskilling employees will become increasingly important as AI’s applications in the workplace continue to evolve.

There is currently a wide delta between those who feel the need for training to empower them in the new digital world and those who are receiving it. According to Salesforce’s Digital Skills Index, more than 75% of respondents “do not feel ready to operate in a digital-first world”—but only 28% are “actively involved in digital skills learning and training.” 

There are real outcomes at stake in investing in the skills of your workforce: organizations reporting successful automation efforts are nearly twice as likely to cite addressing automation-related skills gaps as a top-five priority at their organization compared with all other organizations, according to research by McKinsey.

Leading enterprises are already investing billions of dollars toward developing the workforce of the future. In 2021, Amazon pledged $1.2 billion to upskill 300,000 of its workers for high-paying, in-demand jobs by 2025. AT&T pledged $1 billion to retrain as many as half of its employees for the jobs of the future through an initiative called Future Ready. And in 2023, Cisco announced a goal to train ten million people across Europe, the Middle East, and Africa (EMEA) in digital skills over the next ten years.

The training needs of the workforce will vary based on where they sit in the current economy. McKinsey has estimated that as many as 100 million workers across 8 focus countries may need to switch occupations by 2030 as a result of automation. These workers will need to be equipped with completely new skill sets so they can compete in the AI-powered labor market of the future. Meanwhile, many other workers will require upskilling—the addition of new skills to their existing skill sets—to take full advantage of the new technologies becoming available. For these employees, upskilling will also help alleviate corporate employees’ anxieties about the safety of their own jobs, as it equips them to better understand how these emerging technologies can augment, rather than replace, their own work.   

While it’s true that AI has the potential to replace some jobs, it also has the potential to create many more. According to the World Economic Forum, technology will create at least 12 million more jobs than it destroys by 2025. Specifically, AI will create huge demand for positions like data scientists, AI engineers, algorithm designers, and machine learning experts. Business leaders need to invest in and develop these skill sets, and create pathways to these opportunities for workers of all backgrounds.

Upskilling and reskilling efforts start with a comprehensive understanding of the organization’s current workforce. What skills and competencies do existing team members possess? What new skills and competencies will they need going forward? After taking stock of the organization’s current skill set, leaders can begin to identify training opportunities and invest in programs to ensure their employees are ready to tackle the changing demands of the marketplace.

Training must be scalable, semi-synchronous and customized

We’ve established that data literacy will be an essential skill in the AI-driven future, and that businesses need to invest in upskilling and reskilling their workforces to prepare them for the shift that AI will enact. The next question becomes: What should that training look like? 

Broadly speaking, there are two pathways an organization can consider: self-directed, asynchronous training in the style of Massive Open Online Courses (MOOCs) and instructor-led, synchronous training. The former entails employees taking online courses or participating in virtual learning sessions at their own pace. Meanwhile, synchronous training involves employees working with an instructor on a given schedule. 

Organizations that opt for the fully asynchronous model should be aware of its limitations. One of the main challenges is the high dropout rate—as high as 96% by some estimates—as many learners struggle to stay motivated and engaged without the structure of a traditional classroom setting. MOOCs often lack the personalized support and feedback that students receive in a face-to-face course, which can hinder learning and progress. And MOOCs can be limited in their effectiveness for teaching certain subjects, such as those that require hands-on experience—as learning to operate AI and other automation innovations in the workplace inevitably will.

Importantly, AI-related training doesn’t have to be either synchronous or asynchronous—it can (and should) be both. Organizations should think of their training initiatives as a mix of synchronous and asynchronous learning—with a focus on scalability. The training should be tailored to each individual employee, and should be able to flex as the organization’s needs change and as the technology evolves. There should also be an emphasis on creating customized, tailored training programs to address the specific needs of the organization and the specific scenarios workers are likely to encounter within the context of their own work. For example, if a business is adopting a specific AI technology, it should design a program to ensure that employees are able to use the technology effectively, and understand its full capabilities. 

Diversity, equity and inclusion are non-negotiable

Any time a new technology emerges, questions emerge with it: who is this technology for? Who has access to it? Who has the opportunity to benefit from it—and who has the potential to be harmed? 

Questions like these become even more important in the context of AI. Over the past several years, the news has been full of stories about bias and discrimination in the use of AI-based tools in areas like recruiting and housing. Bad actors have used AI to perpetuate scams and misinformation.

The more ubiquitous these technologies become in the workplace and beyond, the more important it becomes for business leaders to ensure that their AI-powered processes are equitable and inclusive. This means looking honestly and critically at the data sets the AI is being trained on; ensuring that algorithms don’t perpetuate bias or discrimination; and constructing inclusive teams with diverse backgrounds and perspectives that reflect the world that AI-driven technologies are acting in.

By investing in the development of diverse teams and technologies, business leaders can reduce the risk of AI-related bias—and set their organizations up for long-term success in an increasingly AI-powered world.

Invest in human potential 

At the end of the day, AI tools are only as valuable as the people and the vision that drive them. That means investing in human potential in order to develop the skill sets and capabilities needed to effectively leverage AI. From providing training on data literacy to fostering an environment of inclusivity and collaboration, leaders must take an active role in creating a workplace where employees feel empowered rather than threatened by AI technologies.That way, when the time comes to use AI to drive business decisions, processes and outcomes, the team will have the skills and perspectives necessary to accelerate the business’s success.

At Correlation One, we're committed to helping business leaders forge a path to a data-driven, AI-enabled future by investing in their most valuable asset: their workforce. Through our enterprise-scale data literacy upskilling and reskilling programs, we've helped thousands of workers prepare for the workplace of tomorrow. Curious how Correlation One can help you invest in the future of your workforce? Reach out to learn more