The conversation about AI and the workplace is understandably dominated by the downsides – after decades of automation eliminating manufacturing jobs, people in the service sector are worried about being replaced by "robots". But every technological shift creates as well as destroys jobs. Artificial intelligence – at least in its current iteration, which uses large language datasets to create text, audio and video – is no different. What is, perhaps, surprising is the type of jobs it will create. The most visible and obvious new roles are for those with the coding and development skills to help build AI models or adapt them for particular purposes.

The development of ChatGPT began in 2021 when OpenAI researchers first introduced the GPT-3 language model. This model, which is based on a neural network architecture, was designed to generate human-like text based on a given prompt or input. The success of GPT-3 led to the development of ChatGPT, which was specifically designed to enable more natural and human-like communication between humans and machines. Since its development, ChatGPT has been used in a wide range of IT applications, including chatbots, customer service agents, and automated content generation. Its ability to generate accurate and contextually appropriate responses to natural language inputs has made it a valuable tool for companies looking to streamline and automate their IT processes. Overall, ChatGPT is a revolutionary technology that is changing the way we think about artificial intelligence and human-machine communication. Its impact on the IT industry is sure to be felt for years to come.

IDC recently released the IDC Worldwide Artificial Intelligence Spending Guide. Data shows that total global IT investment in artificial intelligence (AI) in 2021 was US$92.95 billion, expected to increase to US$301.43 billion in 2026, and the compound annual growth rate (CAGR) was about 26.5%. As for the China market, IDC predicts that China's AI investment is expected to reach US$26.69 billion in 2026, accounting for about 8.9% of global investment, ranking second in the world among other countries. In recent years, more and more enterprises have become involved in the Digintelligence Era and started the deployment of digital transformation (DX) and intelligent upgrading, which has thus spawned more demand for AI. Driven by policies, technologies, and markets, AI empowering industries is becoming a mainstream development trend.

Were you unable to attend Transform 2022? Check out all of the summit sessions in our on-demand library now! Technology venture capital deals may be slowing down, but investment in artificial intelligence (AI) companies continues to boom. Investments in AI research and applications are set to hit $500 billion by 2024, according to research firm IDC, while PwC predicts AI will contribute $15.7 trillion to the global economy by 2030. So, it's no surprise that among the 206 new 2022 "unicorns" – that is, privately held startups with a value of over $1 billion – a boatload are in artificial intelligence and machine learning.

Business analytics is an increasingly powerful tool for organisations, but one that is associated with steep learning curves and significant investments in infrastructure. The idea of using data to drive better decision-making is well established. But the conventional approach – centred around reporting and analysis tools – relies on specialist applications and highly trained staff. Often, firms find they have to build teams of data scientists to gather the data and manage the tools, and to build queries. This creates bottlenecks in the flow of information, as business units rely on specialist teams to interrogate the data, and to report back.

We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 - 28. Join AI and data leaders for insightful talks and exciting networking opportunities. Technology venture capital deals may be slowing down, but investment in artificial intelligence (AI) companies continues to boom. Investments in AI research and applications are set to hit $500 billion by 2024, according to research firm IDC, while PwC predicts AI will contribute $15.7 trillion to the global economy by 2030. So, it's no surprise that among the 206 new 2022 "unicorns" – that is, privately held startups with a value of over $1 billion – a boatload are in artificial intelligence and machine learning. Join us at the leading event on applied AI for enterprise business and technology decision makers in-person July 19 and virtually from July 20-28.

Customer service holds a prime spot in a no-see, essential online world. You decided to eat out after a hard day at work. As soon as you enter the restaurant, you find the menu hard to interpret, and the support team has no knowledge. When you finally manage the order, you see the service is slow, and there is no one to help you. You vow never to revisit the restaurant.

We love it when people exceed expectations. Whether it's an athlete who steps up to replace an injured starter or a team that pulls together to deliver exceptional results, it is inspiring to see long-held assumptions about potential turned upside down. Now, service organizations have an opportunity to exceed traditional expectations in the same way. Instead of being considered simply a means of connection and cost containment post-customer purchase, intelligent service teams can become a strategic driver to direct value back to the business. Focusing on speed, insights, and accuracy, SAP Service Cloud resolves customer issues at unmatched speed -- protecting the brands promise and securing future growth.

While some surveys show that people prefer to talk to a human as opposed to a chatbot, whether they're shopping online or dealing with a customer service issue, that hasn't dissuaded companies from adopting them. A 2019 Salesforce report found that 53% of service organizations expected to use chatbots within 18 months. According to Statista, the size of the global chatbot market could surpass $1.25 billion by 2025, a steep climb from $190 million in 2016. A customer's satisfaction -- or lack thereof -- with a chatbot ultimately depends on the scenario and the capabilities of the chatbot in question. Obviously, a chatbot that fails to answer basic questions will lead to frustration.

A recent study from Göttingen University found that "chatbot disclosure has a negative indirect effect on customer retention through mitigated trust for services with high criticality." Although chatbots are in wide use and provide material benefits for consumers such as 24/7 support, customers may still be suspicious of whether automated responses can get them the help they need. These findings, and others like them, are making some companies reconsider how they are going about implementing chatbot technology into their customer service – can they continue to "pretend" chatbots are real? Can customers handle the truth about chatbots? How do conversational AI chatbots change the game?