ChatGPT and Artificial Intelligence (AI) transform the workforce

by Yara El-Sabagh

 OUT NOW im #ConfareBlog with EY’s IT profis:
ChatGPT and Artificial Intelligence (AI) transform the workforce

The hype surrounding ChatGPT has managed to make AI thrive as a leading topic in the eyes of CEOs and CIOs. In this #ConfareBlog, we discuss this topic with EY’s team of experts in Switzerland: Aakash Deep, Partner, Data & Analytics Consulting, Marco Pizziol, Senior Manager, Data & Analytics Consulting and Esther Van Laarhoven Smits, Partner, Data & Analytics Lead.

In this interview, you will read more on what CIOs need to consider when using artificial intelligence and how it affects companies today.

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How important are the topics of data and artificial intelligence (AI) in companies today?

AIThe ability to use data and analytics has become a key differentiator that separates a leading company and a laggard.

Companies are generating immense amounts of data (e.g., Google alone processes 7+ exabytes a year). Companies need to make use of AI to transform data into insights. AI is also a key factor for automation, increasing efficiency, making better, faster decisions. In addition, AI allows companies to predict and manage risks across the enterprise.

Furthermore, in our present era, no company can ignore the topic of data and AI if they want to be a leading organization.

ChatGPT shows that automation could go much further in communication than we have experienced to date. AI always receives intense attention. Did you expect this development?

AI and automation have been developing rapidly for the last two decades. A lot of investment (in 2021, Al global funding doubled to $67 billion) has gone into making this a success. Therefore, the emergence of ChatGPT is not a surprise.
However, it did not appear out of the blue: development of ChatGPT had started in 2015, but has its roots in the early natural language processing (NLP) programs, such as ELIZA, in the 1960s, followed by NLP expert systems in the 1980s. We had to wait until the early 2010s to have the first successful NLP/AI assistant (Apple Siri).


Has the hype surrounding ChatGPT changed companies’ perception of AI?

ChatGPT’s arrival is one of those events in which a technology moves from an experimental or limited use to a mainstream technology. Not many products have proven as effective as ChatGPT. This puts an increased emphasis on how this technology can totally alter business models, for example, in the interaction with the customer.

Indeed you can say there is some hype around ChatGPT. However, the focus on finding use cases will bring additional investment, thereby improving the technology. It will dissolve many preconceptions and help push AI into day-to-day use at companies.

Will AI actually turn into the announced job killer?

While new jobs in the AI field are emerging, the introduction of AI aiming at increasing efficiency and reducing effort could possibly lead to reduced employment in some domains.

However, these kinds of questions have often been asked in the past, but each time the arrival of new technologies has just transformed the workforce. For example, since the introduction of computers with microprocessors in companies in the early 1970s to the early 2000s, the US unemployment rate has not changed significantly, while the number of people using computers at work in the US has risen to more than 50%.

We expect that AI will also transform the workforce, with some jobs being lost and others gained.

Which new career paths are emerging from data- and AI-related fields?

AI is impacting society and raising new jobs that did not even exist 10 years ago, such as data engineers, data evangelists, analytics translators, machine learning engineers and AI ethicists.

Also, the use of AI has been promoting new types of artists and arts, such as generative art (that starts from AI-generated images, music or poetry), collaborative arts and augmented reality art.

Which tools and options should we familiarize ourselves with to keep up with recent developments in the field?

Tools related to the AI field are evolving very quickly, so it is always important to remain up-to-date on new trends.

Today, it is important to be familiar with the big data technologies (e.g., Apache Spark and Hadoop) and the main cloud computing platforms (MS Azure, AWS and Google Cloud Platform). These technologies did not even exist two decades ago.

It is also crucial to have a good understanding of programming languages used in this field, mainly Python and R.

What role should AI now play in a company’s digital strategy?

AI will be the key differentiating factor that distinguishes the leading companies who are able to harness the power of artificial intelligence from the laggards who are not able to use its capabilities well. For example, companies like Amazon, Walmart or P&G are able to use AI to run their companies efficiently and deliver a high-value impact on a regular basis.

In particular, it is used to make the customer experience faster, more efficient and to introduce the “wow” factor. Moreover, AI is and should be used to enable employees and optimize operations.

It should be included in every touch point present in the customer and employee journey to maximize revenue, curb costs and increase end-customer satisfaction.

What contributions can corporate IT make? How should a company’s internal distribution of roles look like to support this transformation?

Corporate IT teams need to transform in a way that allows them to contribute to the AI-led digital transformation of companies. They can help lay down solid foundations on which scaled AI tools can be easily implemented.

At the same time, corporate IT teams can support these developments by becoming more agile and setting up proper data management processes and AI governance policies.

Internal distribution of roles will depend heavily on the digital strategy the company adopts. But in general, they need to define some specific roles (data scientist, data analyst, data engineer, machine learning engineer, agile coach, cloud solutions architect and data architect) that can facilitate the development and adoption of AI solutions.

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